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39915241 | PMC11907387 | pmc | 7,998 | {
"abstract": "Abstract Biological membranes achieve selectivity and permeability through protein transporters and channels. The design of artificial compartments with permeable membranes is essential to facilitate substrate and product transfer in enzymatic reactions. In this study, an E. coli outer membrane protein OmpF fused to a modular adaptor was integrated onto a DNA origami skeleton to control the number and polarity of the OmpF trimer. DNA origami skeleton‐guided nanoliposomes reconstituted with functional OmpF exhibit pH‐responsiveness and size‐selective permeability. This approach highlights the potential to construct artificial compartments that incorporate membrane proteins of defined number and polarity, allowing tunable substrate fluxes.",
"conclusion": "Conclusions The bacterial outer membrane protein OmpF was fused to the modular adaptor ZF‐SNAP (ZSO) to control the number and polarity of OmpF trimers within the membrane of liposomes with an internal DNA origami skeleton. Despite the effect of urea denaturation during the purification of ZSO, which resulted in incomplete recovery of SNAP‐tag activity after refolding, ZSO still exhibited a loading yield of 42±3% with a single binding unit (for one trimer) and 58±5% with two binding units (for two trimers). As a result, liposome‐coated WS with one binding unit for ZSO contained an average of 0.4±0.03 OmpF trimers per nanoliposome, while those with two binding units contained an average of 0.8±0.02 OmpF trimers per nanoliposome. Furthermore, the functionality of the membrane protein OmpF was confirmed by the response to external pH and by the size‐selective transport of DNA intercalators into the interior of the liposomes, showing that fusion with ZF‐SNAP does not affect its function. Using the intercalators, faster transport kinetics were observed for the liposome compartments with more OmpF incorporated. By controlling the number of OmpF in the compartments, the transport kinetics of substrates or reaction intermediates can be regulated, which is of great importance for the regulation of enzyme reactions, especially cascade reactions, in the compartments. Although it is known that the orientation of OmpF does not significantly affect its function of transporting molecules and ions, using OmpF as a first example opens further possibilities for the construction of a wider range of modular adaptor‐fused membrane proteins. This work provides a potential approach to control the number and polarity of channels in artificial compartments, providing insight for future developments in membrane protein engineering.",
"introduction": "Introduction Biological membranes serve as excellent separators by providing both controlled permeability and precise solute selectivity, which is attributed to specific membrane protein channels. \n [1] \n These channels possess unique pore geometries that are critical for the targeted separation of small molecules essential for cellular functions.[ \n 2 \n , \n 3 \n , \n 4 \n , \n 5 \n ] Some membrane proteins, such as porins, are constantly open, allowing non‐selective molecule diffusion, while others open in response to external stimuli such as ions, temperature, or voltage changes. Reconstitution of these membrane proteins into lipid membranes of liposomes or polymersomes of various compositions and sizes has been reported. \n [6] \n For example, the outer membrane protein OmpF, a highly abundant trimeric porin of E. coli that facilitates general diffusion and is critical for the transport of antibiotics and colicins across the outer membrane, \n [7] \n has been used extensively in the synthesis of artificial filters, \n [8] \n sensors \n [9] \n and reactors. \n [10] \n The dimensions of the pore formed by the trimer of OmpF are approximately 7×11 Å, allowing the passage of molecules smaller than 500 Da. \n [11] \n When solubilized with detergents, OmpF can be reconstituted into artificial bilayers and retains its functionality as a trimeric ion‐conducting porin with the same properties as its in vivo function. \n [12] \n However, achieving precise control over the number and polarity of these membrane proteins in lipid membranes of artificial compartments remains a challenge. Rationally designed DNA nanoscaffolds have been decorated with lipid molecules at specific positions on their surfaces, enabling the construction of artificial membranes.[ \n 13 \n , \n 14 \n , \n 15 \n ] Advances in various assembly methods allow precise placement of proteins of interest (POIs) on DNA scaffolds \n [16] \n including DNA hybridization with covalently conjugated POIs \n [17] \n and noncovalent interactions such as biotin‐avidin,[ \n 18 \n , \n 19 \n ] antibody‐antigen[ \n 20 \n , \n 21 \n ] and DNA‐binding proteins. \n [22] \n These methods provide flexible and reversible binding, but often result in low assembly yields. Our group has developed a modular adaptor method using sequence‐specific DNA‐binding proteins (zif268, AZP4, GCN4) and protein tags (SNAP‐tag, Halo‐tag, CLIP‐tag) to precisely position proteins on DNA scaffolds in nearly quantitative yields.[ \n 23 \n , \n 24 \n , \n 25 \n , \n 26 \n ] This approach achieves high binding efficiencies, precise control of the number of proteins on the scaffold, and minimal interference with protein activity. Recently, we reported a DNA origami skeleton‐guided liposome embedded with OmpF that exhibited a size‐selective molecular transport function as an artificial compartment. The artificial compartment transported ions and molecules with a molecular weight below 600 Da. \n [27] \n \n In this study, we designed a modular adaptor (ZF‐SNAP)‐fused OmpF for assembly onto the DNA origami skeleton constructed in our previous work. \n [27] \n This facilitated precise control over the number and polarity of ZF‐SNAP‐OmpF (ZSO) within the membrane of artificial compartments. After expression and purification, ZSO was refolded into lipids. The functional state of ZSO was confirmed by fluorescence microscopy, where a pH‐sensitive fluorophore located on the internal DNA origami skeleton within the artificial compartments showed a response to pH changes in the external buffer. In addition, the size‐dependent permeability of ZSO was investigated by introducing DNA intercalators of different molecular weights (EtBr, SYBR Green II, and GelRed). These intercalators either passed through or were blocked by the resulting pore of the ZSO trimer, allowing selective binding to the DNA origami skeleton inside the liposomes. Interestingly, we found that when the molecular weight of the DNA intercalator was around 450 Da, its rate of transfer into the interior of the nanoliposome increased with increasing number of OmpF inserted into the liposome. This observation suggests that this method has the potential to regulate the substrate exchange rate in the construction of artificial compartments.",
"discussion": "Results and Discussion Anchoring of the Membrane Protein ZF‐SNAP‐OmpF (ZSO) on the DNA Origami Skeleton To specifically locate a membrane protein to the wireframe DNA origami skeleton (WS), the membrane protein OmpF was genetically fused to the adaptor ZF‐SNAP, which consists of both the DNA binding protein zif268 and a self‐ligating protein tag SNAP‐tag at the N‐terminal, through a flexible GGS linker to yield ZSO (Figure 1a and Figure S1). To assemble the membrane protein, the DNA origami skeleton was designed according to our previous work. \n [27] \n A total of three binding sites for the ZF‐SNAP adaptor were designed as the binding unit for assembly with the ZSO trimer (Figure 1b ) to prepare WS containing either one or two binding units. The number of parents OmpF inserted into liposomes was found to be three trimers per WS liposome (LWS) in our previous study. \n [27] \n The modular adaptor was designed to regulate the number of ZSO on LWS. The binding sites for ZSO were designed as hairpin DNA sequences. These sequences consist of the zif268‐specific binding sequence in the stem region and the tag substrate BG in the loop region. In previous work, we determined that the diameter of LWS is approximately 76 nm, while the diameter of WS is 56 nm, resulting in a gap of 8.5 nm between the liposome and WS. To provide flexibility for ZSO binding and to adjust the distance between the N‐terminal portion of OmpF and the edge of the WS surface, the hairpin DNA sequences were extended to a total length of 8.5 nm. Importantly, the modular adaptor is non‐hydrophobic, which is critical for the polarity control of ZSO. Since it cannot spontaneously cross the membrane, it dictates that the membrane protein can only be inserted into the liposome in a specific orientation, thereby ensuring effective regulation of the number and polarity of OmpF trimers within the liposome membrane. This design feature provides a basis for the construction of artificial compartments with precisely controlled membrane protein properties. After ZSO binds to the DNA skeleton WS through the modular adaptor ZS, it can only be inserted into the membrane of the subsequently constructed liposome with a unique polarity, allowing control over the orientation of OmpF with respect to the DNA skeleton WS (Figure 1b ).\n Figure 1 Design of modular adaptor‐fused OmpF and binding sites on a DNA origami skeleton. (a) Illustrations showing the structure of the modular adaptor‐fused OmpF monomer (ZSO). The modular adaptor‐fused OmpF consists of the DNA‐binding protein zif268, the self‐ligating protein tag SNAP‐tag and the membrane protein OmpF. (b) Schematic representation of the binding unit for ZSO assembly on the DNA skeleton (designed diameter of 58 nm). One binding unit contains three ZS binding sites, allowing the assembly of one ZSO trimer. WS‐ZSO1 contains one binding unit, allowing assembly of a ZSO trimer, while WS‐ZSO2 has two binding units at equatorial poles, allowing assembly of two ZSO trimers. After assembly with ZSO, lipidated ODN was attached to WS in a surfactant solution and combined with surfactant‐lipid micelles to form liposomes (designed diameter of 80 nm) around WS (LWS‐ZSO1 and LWS‐ZSO2) by dialysis to remove excess surfactant. Preparation and Characterization of OmpF Anchored Nanoliposomes Since the expressed ZSO had very low solubility in the lysis buffer, urea was used to denature the protein to prevent digestion and improve solubility. Increasing the urea concentration in the lysis buffer improved the solubility of ZSO, with optimal solubility observed at 6 M urea (Figure S3). Inclusion body pellets of ZSO were solubilized in 6 M urea and 20 mM Tris‐HCl, pH 8.0. Ni/NTA affinity purification was performed on an AKTA system using HisTrap HP columns. The purity of ZSO with the expected molecular weight (71.3 kDa) and purity >98 % is shown in Figure 2a .\n Figure 2 (a) The 12 % SDS‐PAGE image of purified ZSO (over 95 % purity) and ZSO refolded in 10 : 0 PC. In 6 M urea, ZSO exists as a monomer. After refolding in 10 : 0 PC without heat denaturation, it appears as a trimer on SDS‐PAGE. (b) The binding efficiency of ZSO and ODN‐BG increases with the refolding time of ZSO, reaching a maximum binding efficiency of up to 80 % after 12 hours of refolding. (c) TEM images of LWS‐ZSO‐1. Scale bar: 20 nm or 100 nm. (d) Histograms show that the diameters of LWS‐ZSO1 and LWS‐ZSO2 measured from TEM images are 80.8±11.5 nm (N=182) and 81.9±9.8 nm (N=242), respectively. After purification, ZSO was refolded by dilution in large unilamellar liposome (LUV) formed by 5 mM 1,2‐dioleoyl‐sn‐glycero‐3‐phosphocholine (DOPC) or 1,2‐didecanoyl‐sn‐glycero‐3‐phosphocholine (10 : 0 PC) in folding buffer containing 1 M urea and 20 mM Tris‐HCl buffer (pH 8.0). SDS‐PAGE analysis was used to determine the fraction of protein that refolded under these conditions (Figure S4a). When ZSO was solubilized in SDS and then boiled, ZSO lost its native β ‐content and migrated to its expected molecular weight on polyacrylamide gels. \n [28] \n Non‐boiled samples of folded ZSO retained a high content of β ‐structure as well as its activity to form oligomers and migrated to a different position than the unfolded form. Therefore, SDS‐PAGE was used to distinguish between the folded and unfolded populations. From the SDS‐PAGE shown in Figure 2a and Figure S4b, when incubated with a 10 : 0 PC LUVs, over 75 % of ZSO folded into trimers, 15 % formed dimers, and 10 % remained unfolded. In contrast, no folding was observed when incubated with DOPC LUVs and Tris‐HCl buffer. As a control, native OmpF and ZSO were also expressed and refolded in 5 mM 10 : 0 PC in folding buffer. SDS‐PAGE analysis revealed that over 80 % of native OmpF folded into trimers, 12 % formed dimers, while 8 % remained unfolded (Figure S5, left). These results strongly suggest that the refolding of ZSO is dependent on acyl chain length and bilayer thickness. \n [29] \n \n The DNA binding ability of ZSO to the ODN containing its target zif268‐binding sequence modified by a SNAP‐tag substrate benzylguanine (ODN‐BG) (Figure S2c) was analyzed by gel mobility assay (Figure S6). The formation of a covalent bond between ZSO (100 nM) and ODN‐BG (1 μM) resulted in a slower migrating band compared to free ZSO. ZS‐XR (100 nM), a ZS modular adaptor fused to xylose reductase previously reported by our group, \n [25] \n and ZS‐XR modified ODN‐BG formed by ZS‐XR (100 nM) and ODN‐BG (1 μM) were used as control samples. By comparing the band intensity observed between free ZS‐XR and ZS‐XR modified ODN‐BG, it was estimated that over 95 % of the ZS‐XR formed the complex. At 6 M urea, only 55±2% of the unfolded ZSO formed a complex with ODN‐BG, consistent with previous reports (Figure 2b ). Similarly, Gautier et al . reported that the urea concentration required for 50 % inactivation of the SNAP‐tag ([urea] 1/2 ) was 6.3±0.1 M. \n [30] \n However, after refolding for 2 hours in folding buffer (1 M urea and 20 mM Tris‐HCl buffer, pH 8.0) containing 5 mM 10 : 0 PC LUVs, the binding yield increased to 69±6%. Furthermore, the yield reached 80±3% after 12 hours of incubation. The observed binding yield of ZSO, which was lower than the 95 % observed for ZS‐XR, could be attributed to the influence of urea on ZF‐SNAP. To assemble OmpF on the DNA origami skeleton, 20 nM WS with one or two binding units was incubated with 1500 nM ZSO at 4 °C for 2 hours. Purification by gel filtration (TOYOPEARL HW55F) removed unbound proteins, resulting in purified ZSO‐modified DNA skeleton (WS‐ZSO1 and WS‐ZSO2). Due to the relatively low molecular weight of ZSO compared to that of WS, no significant band shift was observed for ZSO‐modified WS on the agarose gel after binding with ZSO (Figure S7). The binding of ZSO to WS was observed in the AFM image (Figure S8). However, due to the 3D shape of WS, it was difficult to accurately calculate the actual number of ZSO molecules bound to the target sites of WS based on the AFM image. This will be discussed in a later section. The WS‐ZSO was combined with DOPC containing 0.8 % rhodamine‐modified lipid to reconstitute a lipid bilayer by dialysis for 48 hours. The dialyzed solution was then loaded onto an iodixanol gradient and ultracentrifuged to isolate liposome‐coated LWS‐ZSO1 and LWS‐ZSO2 (Figure S9). The isolated LWS‐ZSO1 and LWS‐ZSO2 fractions were then analyzed by TEM (Figure 2c , Figure S10). The outer membrane diameter of LWS‐ZSO1 and LWS‐ZSO2 was determined by TEM images to be 80.8±11.5 nm and 81.9±9.8 nm, respectively, each having a diameter similar to the designed diameter (80 nm) \n [27] \n (Figure 2d ). Microscopic Characterization of OmpF Anchored to the Skeleton of Liposomes The LWS‐ZSO compartment was immobilized on a slide coated with biotin‐BSA and streptavidin. \n [27] \n At pH 8.0, strong spots of fluorescence emission were observed from the CF fluorophore located within LWS, LWS‐ZSO1 and LWS‐ZSO2.[ \n 27 \n , \n 31 \n ] The overlapping of fluorescence signals from CF, Rho, and A647 at the same positions in the fluorescence image confirmed the successful and nearly quantitative construction of LWS‐ZSO1 (Figure 3a ). When the external buffer was changed from pH 8.0 to pH 6.0, 42±3% of LWS‐ZSO1 showed a decrease in CF fluorescence intensity to 33±3% of the initial value (Figure 3b and S11, N=82). For LWS‐ZSO2, which contains two binding units for ZSO, the decrease in intensity was observed in 58±5% of the liposomes (Figure 3c , 3d and S12, N=74). This is in marked contrast to the result obtained for LWS in the absence of OmpF. In this case, the fluorescence intensity of the CF fluorophore within the LWS showed no significant change (Figure S13 and Table S3, N=59). These results indicate the successful incorporation of ZSO into the nanoliposomes and demonstrate that the adaptor‐fused membrane protein ZSO assembled on WS was reconstituted into the artificial LWS‐ZSO compartments in an active form.\n Figure 3 An illustration of buffer diffusion through the ZSO‐embedded membrane of LWS‐ZSO. Fluorescence images of LWS‐ZSO1 (a) and LWS‐ZSO2 (c) immobilized on a biotin‐BSA and streptavidin‐coated surface were taken at the CF channel, Rho channel, and A647 channel at pH 8.0 and 6.0, respectively. Scale bar: 100 μm. Plot of fluorescence intensity ratio (CF/A647) of individual LWS‐ZSO1 (b) (N=22) and LWS‐ZSO2 (d) (N=18) under each indicated pH condition. Evaluation of the Activity of Liposome‐anchored OmpF using Intercalators The size‐dependent permeability of liposome‐ anchored OmpF was evaluated using DNA intercalators (EtBr, SYBR Green II, and GelRed) of different molecular weights (Figure S14). In our previous work, we reported that the average number of OmpF trimers inserted into LWS was 3.0 per compartment (LWS‐O3). \n [27] \n Therefore, LWS‐O3 was compared with LWS‐ZSO containing one (LWS‐ZSO1) or two binding units (LWS‐ZSO2). Because the molecular weight of GelRed (985.3) is much larger than the cut‐off of OmpF (500 Da), \n [11] \n the increase in GelRed fluorescence signal during incubation with liposome‐coated WS is attributed to its binding to WS that is not fully encapsulated by the liposome (Figure 4a ). This allowed us to calculate the encapsulation yield of LWS, LWS‐ZSO1, LWS‐ZSO2 and LWS‐O3 by comparing the fluorescence intensity of GelRed at the same WS concentration. The encapsulation yields of LWS, LWS‐O3, LWS‐ZSO2, and LWS‐ZSO1 are 89±3%, 88±4%, 92±6%, and 90±4%, respectively (Figure 4b and Figure S15). The lack of significant differences between them further demonstrates that this method is applicable to encapsulate the DNA skeleton with or without the anchored proteins. When the encapsulating liposomes were disrupted by adding SDS, the fluorescence intensity of GelRed binding with liposome‐encapsulated WS (LWS‐ZSO1, LWS‐ZSO2, and LWS‐O3) reached that of WS, confirming that each sample contains the same concentration of WS.\n Figure 4 Size‐dependent permeability of ZSO evaluated using DNA intercalators (EtBr, SYBR Green II, GelRed) of different molecular weights. (a) A scheme illustrates that the molecular cutoff size of OmpF is approximately 480, indicating that EtBr (molecular weight 314.4) can completely pass through OmpF and bind to the DNA duplex of WS. SYBR Green II (molecular weight 454.6) can partially and slowly pass through OmpF and bind to the DNA duplex of WS. In contrast, GelRed (molecular weight 985.3) is unable to pass through OmpF. (b) The encapsulation yields of LWS, LWS‐ZSO1 and 2, and LWS‐O3 were estimated using GelRed. The increase in GelRed fluorescence intensity can be attributed to the presence of incomplete liposomes, as GelRed is unable to pass through OmpF. (c) The binding yield of ZSO to WS was estimated from the fluorescence intensity of EtBr bound to the DNA duplex of WS. (d) The changes in fluorescence intensity of EtBr when mixed with WS (red), LWS (blue), LWS‐O3 (purple), LWS‐ZSO2 (green), and LWS‐ZSO1 (brown), followed by the addition of SDS. After the addition of SDS, which disrupts the liposomes, the fluorescence intensity of EtBr reaches saturation, indicating that the WS concentrations of all samples are the same. (e) The changes in fluorescence intensity of SYBR Green II when mixed with WS (red), LWS (blue), LWS‐O3 (purple), LWS‐ZSO2 (green), and LWS‐ZSO1 (brown), followed by the addition of SDS. (f) The magnified image shows that SYBR Green II can partially pass through OmpF, and the rate of passage increases as the number of OmpF trimers increases. The dashed line indicates the time when the fluorescence intensity reaches its maximum value. (g) T \n 1/2 values of WS (red), LWS (blue), LWS‐O3 (purple), LWS‐ZSO2 (green), and LWS‐ZSO1 (brown) were measured at different concentrations of SYBR Green II ranging from 2.5 nM to 40 nM EtBr is smaller than GelRed with a molecular weight of 314.4, which allows it to rapidly pass through OmpF in the lipid membranes and bind to the DNA duplex of WS inside the liposome, as we have previously reported. \n [27] \n Here, the increase in EtBr fluorescence intensity can be used to determine the loading yield of ZSO to WS on the liposome (Figure 4c and 4d ). After incubation with EtBr, the fluorescence intensity of EtBr with LWS increased by 12±2% compared to the increase with WS, indicating that 88±2% of LWS is well coated with liposomes. This result is consistent with the encapsulation yields estimated from the GelRed experiment above. The fluorescence intensity of EtBr with LWS‐ZSO1 and LWS‐ZSO2 increased by 48±4% and 68±2%, respectively, compared to its increase in WS. Considering that 12±2% of the liposomes are not well coated, the loading yield of ZSO to one binding unit is 36±2%, while its loading yield to two binding units is 56±2%. These results are consistent with those observed by fluorescence microscopy (Figure 3 ). It can be calculated that with one binding unit (LWS‐ZSO1), each liposome contains an average of 0.4±0.03 ZSO trimers. For WS containing two binding units (LWS‐ZSO2), loading of one or two ZSO trimers is possible. With a loading yield of 40 %, the probability that only one ZSO trimer will bind to the two binding units is 48 %, while the probability that two ZSO trimers will bind is 16 %, resulting in a total probability of 64 %. This calculation is close to the experimental result of 58±5% (Figure 3d ) and supports the estimation that each liposome contains an average of 0.8±0.02 ZSO trimers when two binding units are present. The results with GelRed and EtBr shown above confirmed that the size‐dependent permeability of ZSO in the membrane and fusing with the modular adaptor does not affect the intrinsic function of OmpF. The cut‐off of ZSO was further investigated with intercalators of similar molecular weight. SYBR Green II (molecular weight 454.6) and SYBR Green I (molecular weight 509.7). Interestingly, despite its molecular weight of less than 500, SYBR Green II could not rapidly pass through the OmpF‐embedded membrane to bind to WS like EtBr (Figure 4e and Figure S16 and S17). In contrast, SYBR Green I did not pass through the OmpF‐embedded membrane (less than 5 %) (Figure S18). This result is consistent with previous reports that for small molecules with molecular weights above 480, approximately 90 % of them are unable to pass through OmpF‐embedded biomimetic membranes. \n [8] \n \n Furthermore, the binding rate increased with the number of OmpF trimers on the liposome (Figure 4f and 4g ). 10 nM SYBR Green II binds the internal WS of the liposome‐encapsulated WS containing three native OmpF trimers (LWS‐O3) at a rate similar to its binding rate to WS without liposome encapsulation, with T \n 1/2 of 31±7 s and 12±6 s, respectively, where T \n 1/2 is the time required for half saturation of fluorescence intensity (Figure 4f ). In contrast, for LWS‐ZSO containing one or two binding units with an average of 0.4±0.03 OmpF trimers and 0.8±0.02 OmpF trimers, the T \n 1/2 values were 112±17 s (LWS‐ZSO1) and 36±12 s (LWS‐ZSO2), respectively. Subsequently, T \n 1/2 values were measured with different numbers of OmpF at different concentrations of SYBR Green II ranging from 2.5 nM to 40 nM. The T \n 1/2 values increased as the number of OmpF trimers on the liposomes decreased and also increased as the concentration of SYBR Green II decreased (Figure 4g ). The diffusion of EtBr into OmpF‐embedded liposomes was also investigated. Since the molecular weight of EtBr is much smaller than the cut‐off of OmpF, the binding rates observed for liposomes with different numbers of OmpF trimer (LWS‐ZSO1, LWS‐ZSO2 and LWS‐O3) were similar to each other. As the EtBr concentration decreased from 100 nM to 10 nM, the T ₁ / ₂ values increased from 16±4 s to 36±7 s for LWS‐ZSO1 (Figure S19). No significant changes were observed for LWS‐ZSO2 and LWS‐O3. These results suggest that by controlling the number of OmpF trimers on the liposome, it is possible to regulate the rate at which molecules of appropriate molecular weight, i. e. near the cut‐off molecular weight, are transported through the liposome."
} | 6,250 |
36860699 | PMC9969067 | pmc | 7,999 | {
"abstract": "Methyl methacrylate (MMA) is an important petrochemical with many applications. However, its manufacture has a large environmental footprint. Combined biological and chemical synthesis (semisynthesis) may be a promising alternative to reduce both cost and environmental impact, but strains that can produce the MMA precursor (citramalate) at low pH are required. A non-conventional yeast, Issatchenkia orientalis , may prove ideal, as it can survive extremely low pH. Here, we demonstrate the engineering of I. orientalis for citramalate production. Using sequence similarity network analysis and subsequent DNA synthesis, we selected a more active citramalate synthase gene ( cimA ) variant for expression in I. orientalis . We then adapted a piggyBac transposon system for I. orientalis that allowed us to simultaneously explore the effects of different cimA gene copy numbers and integration locations. A batch fermentation showed the genome-integrated- cimA strains produced 2.0 g/L citramalate in 48 h and a yield of up to 7% mol citramalate/mol consumed glucose. These results demonstrate the potential of I. orientalis as a chassis for citramalate production.",
"conclusion": "5 Conclusion Bio-based organic acids are important chemical building blocks for the production of commodity chemicals and materials with diverse applications. The non-conventional chassis I. orientalis has an extraordinary ability to tolerate diverse industrially relevant stresses (e.g., low pH and inhibitors in lignocellulosic biomass hydrolysates), and it as a chassis for the production of organic acids could potentially reduce the cost and environmental footprint of organic acid production by 30% compared with using conventional species as chassis. For non-model strains, genetic engineering tools are limited, and the Design-Build-Test-Learn cycle tends to be slow. Therefore, we decided to use the piggyBac transposon system to identify optimal integration loci and copy numbers for citramalate production. We used the M. jannaschii cimA , which performed the best in I. orientalis according to our initial screening. Four strains, SB814 through SB817, showed high citramalate production after random integration of this cimA gene using the piggyBac system. Further characterization indicated that these strains contain 2 to 6 copies of the cimA gene in their genomes, and their integration sites were diverse. We demonstrated that SB814 and SB816 produced the highest amount of citramalate, 2 g/L, which was 6-fold higher than that of their plasmid counterpart. These results demonstrated the efficacy of the piggyBac transposon system for rapid exploration of integration sites and copy numbers of important metabolic genes, which allowed us to create high-production strains.",
"introduction": "1 Introduction Methyl methacrylate (MMA) is a building block for poly MMA (PMMA), which is a transparent material known as acrylic glass or plexiglass with the trade names Acrylite® and Plexiglas® ( Mahboub et al., 2018 ). PMMA is an economical alternative to polycarbonate (PC) and has diverse industrial applications (including paints, coatings, electronics, and modifier for polyvinyl chloride [PVC]) ( Dixit et al., 2009 ; Lebeau et al., 2020 ; Mahboub et al., 2018 ). PMMA is also commonly used in making prosthetic dental applications, including dentures, denture bases, and artificial teeth (implants) ( Frazer et al., 2005 ; Zafar, 2020 ). Because of MMA's versatility, its global market demand is expected to grow to USD 8.16 billion by 2025, with a compound annual growth rate of 8.4% ( Grand View Research, 2019 ). MMA is currently produced from petroleum using chemical processes. The dominant commercial process for MMA is the acetone cyanohydrin (ACH) route. The use of toxic hydrogen cyanide and concentrated acid is a primary concern for the ACH route, as are the negative impacts of co-product waste (ammonium bisulfate) generation and disposal. ( Lebeau et al., 2020 ; Mahboub et al., 2018 ; Nagai and Ui, 2004 ). Although the industry has improved the process significantly, even the safer and more-sustainable alternatives recently developed are still energy-intensive, and therefore contribute excessively to greenhouse gas emission. For example, the LiMA process, milder than others, emits 2.6 t-CO 2 /t-MMA ( Mahboub et al., 2018 ). Producing MMA from renewable resources may be a more attractive alternative. Semisynthesis (a combination of biological and chemical processes) may be the best strategy for MMA production, as MMA is toxic to cells because of its lipophilicity and reactivity with cellular components, and no enzyme is currently known to directly catalyze the formation of MMA ( Curson et al., 2014 ; Webb et al., 2018 ). Diverse metabolites have been proposed as precursors for MMA production ( Lebeau et al., 2020 ). Among them, the most promising approach may be to use di- and tricarboxylic acid metabolites as precursors. In particular, we selected citramalate, a dicarboxylic acid, as a target for semisynthesis because it can easily be converted to methacrylic acid (MA), a precursor for MMA, via base-catalyzed decarboxylation and dehydration in hot pressurized water ( Johnson et al., 2015 ; Wu and Eiteman, 2016 ). MA is then converted into MMA through esterification in the presence of methanol and an acid catalyst ( Lebeau et al., 2020 ). Citramalate is a common metabolite found in diverse organisms as an intermediate of the isoleucine biosynthesis pathway ( Risso et al., 2008 ; Sugimoto et al., 2021 ). The key enzyme for citramalate synthesis is citramalate synthase (CimA, EC 2.3.1.182), which catalyzes condensation of the central metabolites pyruvate and acetyl-CoA to generate citramalate ( Howell et al., 1999 ). An E. coli strain has been engineered to produce citramalate. This strain carried an exogenous citramalate synthase gene ( cimA ) with the genes for lactate dehydrogenase ( ldh ) and pyruvate formate lyase ( pfl ) deleted. The low toxicity of citramalate compared to many other organic acids helped increase its production significantly. Fed-batch fermentation using this E. coli strain achieved a titer of 82 g/L, a productivity of 1.85 g L −1 hr −1 , and a conversion yield of 0.48 wt% ( Webb et al., 2018 ). One major bottleneck for this process, however, is that a neutralization step is required. At a large scale of production, a cheap alkali source, lime (CaCO 3 ), is generally used for the neutralization, which results in high CO 2 emission. Additionally, the media must be reacidified with H 2 SO 4 to convert the salt form to the undissociated form of citramalate, resulting in formation of a large amount of gypsum (CaSO 4 ) as a byproduct that needs to be properly disposed. The technoeconomic assessment and life cycle assessment for organic acid production suggest that neutralization and acidification steps increase both process cost and environmental footprint by 30% ( Bhagwat et al., 2021 ). Low-pH fermentation using acid-tolerant microbes are therefore a better process for citramalate production. Acknowledging the benefits of low-pH fermentation, the US Department of Energy's Center for Bioenergy and Bioproduct Innovations (CABBI) selected Issatchenkia orientalis as its flagship strain for organic acid production because of its ability to tolerate extremely low pH. I. orientalis has already been engineered to produce some organic acids, including D-xylonic acid ( Toivari et al., 2013 ), succinic acid ( Xiao et al., 2014 ), D-lactic acid ( Park et al., 2018 ), itaconic acid ( Sun et al., 2020 ), and 3-hydroxypropionic acid ( Bindel, 2016 ). With recent advances in genetic and genomic engineering tools (e.g., plasmid, promoters, terminators, and CRISPR-Cas9 system) ( Cao et al., 2020 ; Tran et al., 2019 ) and a genome-scale metabolic model, iIsor 850 ( Suthers et al., 2020 ), I. orientalis is becoming a more amenable strain for metabolic engineering. In this study, we attempted to engineer I. orientalis for production of citramalate. We first screened cimA genes and identified a more active variant in I. orientalis . To stably integrate this cimA gene variant into I. orientalis 's genome, we employed a hyperactive piggyBac transposase system ( Li et al., 2013 ; Wagner et al., 2018 ; Yusa et al., 2011 ) and generated a cimA integration library. This system allows us to explore the effect of both various cimA integration locations and different numbers of cimA integration copy on citramalate production. Subsequent screening of this library identified a citramalate producer that was drastically better than its plasmid-based counterpart.",
"discussion": "4 Discussion 4.1 Identification of optimal CimA variants for citramalate production in I. orientalis Since citramalate synthase (CimA, EC 2.3.1.182) was identified from a thermophilic methanogenic archaea, M. jannaschii ( Howell et al., 1999 ), only a few CimA variants have been evaluated in an E. coli heterologous expression system for citramalate biosynthesis ( Webb et al., 2018 ; Wu and Eiteman, 2016 ). With the rapid increase in the abundance of protein sequences in public databases, we sought to identify more efficient CimA from nature. We therefore built a CimA SSN to investigate this possibility and guide target gene selection. In our SSN ( Fig. 2 B), sequences sharing over 80% identities were grouped into the same cluster. By selecting candidate genes from different clusters, we were able to avoid synthesizing genes with high similarities. In this way, we identified five cimA genes that are active in I. orientalis . Their origins are Archaeoglobus fulgidus (gene #02), M. jannaschii (gene #03), Geobacter sulfurreducens (gene #07), S. coelicolor (gene #08), and Arabidopsis thaliana (gene #09). Among them, the cimA genes from M. jannaschii and G. sulfurreducens were previously functionally expressed in E. coli. Whereas the other three were verified in I. orientalis for the first time. We did not identify CimA variants that resulted in higher citramalate yields than that from M. jannaschii . Although it has only 31.2% sequence identity to CimA from M. jannaschii, CimA from S. coelicolor enabled to the production of a similar level of citramalate ( Fig. 2 C). Supplementary Table S6 shows the sequence identity among different CimA genes. These CimA variants generally show only 30–50% identities at the protein level. This result shows that the sequence diversity of CimA is high; no obvious trend for sequence-function relationships was found. Another factor that impacts citramalate production is the level of functional CimA expression. Codon optimization is a common strategy to increase the expression level of proteins ( Plotkin and Kudla, 2011 ). We therefore used two different codon optimization parameters offered by the JGI BOOST; one is “balanced” and the other is “mostly used.” In “balanced” codon optimization, BOOST selects the most-used and second-most-used codon for each amino acid as evenly used as possible during the process ( Oberortner et al., 2017 ). This mitigates the sequence complexity that may arise by using only the most-preferred codon, as is done when using the “mostly used” optimization strategy. Since low-complexity DNA reduces the occurrence of repeats, secondary structure, and sequence stretches with extreme GC content, we expected DNA to be readily manufactured, and could potentially avoid mRNA secondary structure that might affect protein expression. Although we did not evaluate the CimA protein level in this study, the \"balanced\" codon-optimized cimA genes generally produced more citramalate ( Fig. 3 C). This difference between “balanced” and “mostly used” in the plasmid expression system is subtle. Access to multiple cimA variations is helpful because eventually, numerous copies of cimA genes need to be integrated into the genome to enhance the production level of citramalate, and the potential instability factor such as recombination among identical sequences needs to be mitigated. 4.2 cimA genome integration by piggyBac transposase system Plasmid expression systems are typically unstable and not favorable for metabolic engineering. In contrast, genome integration is a better approach to stably maintain heterologous genes. The gene numbers and integration locations are also known to be crucial for heterologous gene expression ( Da Silva and Srikrishnan, 2012 ; Flagfeldt et al., 2009 ). Our top producer, SB814, has the most (six) cimA copies in the genome. Compared with the other three strains, which have only two copies (SB815, SB816, and SB817), SB814 had the highest citramalate production in both SC and YPD medium ( Fig. 4 , Fig. 5 A). However, one of the strains with only two cimA copies, SB816, had a production level similar to that of SB814 in the SC medium ( Fig. 4 A), and had only a slightly lower production level than SB814 in the YPD medium ( Fig. 5 A). This may be because the integration site in SB816 allows a high-level gene expression or expression dynamics more suitable for citramalate production. Although the difference in gene expression level requires further verification, the result suggests the potential of these integration loci providing more choices for future strain engineering. In general, we only recommend using GFP expression and flow cytometry to facilitate the screening of integrants rather than as a guide to report the production of a target compound. This is because a high titer is a result from collective factors such as enzyme concentration and activity, substrate availability, depletion of important central metabolites, toxicity of intermediates and products, and key enzyme expression dynamics. In our previous study with optimization of shikimate production in a different yeast host, the correlation between GFP expression and high production was also not observed ( Zhao et al., 2020 ). Considering random integration could accidentally disrupt coding regions, the fatality of the disruption needs to be examined. In our case, although the integration sites in three cimA -integrated I. orientalis strains disrupted genes ( Table 1 ), including a hypothetical protein gene in SB814, a myosin protein heavy chain (MHC) gene in SB816, and an AAA family ATPase gene in SB817, the strains' growth showed that no fatal effects had occurred. Their growth rates were also not dramatically different than that of SB815, which did not have any genes disrupted ( Fig. 4 , Fig. 5 C). The MHC gene was labeled non-essential for cell survival under laboratory growth conditions in S. cerevisiae ( Rodriguez and Paterson, 1990 ). The AAA family ATPase contains many genes with similar functions. According to the annotation data of Pfam (PF00004) in the JGI's MycoCosm database, I. orientalis has 32 AAA family ATPases ( Grigoriev et al., 2014 ). The disrupted gene in SB817 was likely compensated by other ATPases, so no fatal effect occurred. Although the growth rates of all four cimA -integrated I. orientalis strains were slower than that of the wild-type and the strain expressing cimA in a plasmid, those four strains still reached the late logarithmic phase at 24 h. The slower growth might also have been caused by the extra expenditure for producing a foreign product or LEU2 auxotroph. Recently, a study describes a Hermes transposon-mediated random integration method in Scheffersomyces stipitis by transforming a nonreplicable circular DNA allows the skip of the plasmid curing step and efficiently removes false positive clones ( Zhao et al., 2020 ). We transformed a nonreplicable circular DNA containing the ITR flanked GFP-CimA-LEU fragment and PiggyBac cassette but were only able to get very few colonies on the plate. The number of colonies was too few for effective library construction and screening. Previous studies have shown that Nonhomologous-End-Joining (NHEJ) is involved in the double-stranded DNA break repair in transposition ( Yant and Kay, 2003 ; Yu et al., 2004 ). However, I. orientalis is a homologous recombination-dominant strain ( Cao et al., 2020 ), and the transient expression of PiggyBac in the nonreplicable carrier may not be sufficient for transposition. Future studies to identify important NHEJ-related proteins and overexpress these proteins may help streamline the protocol via a nonreplicable circular DNA in I. orientalis . 4.3 Citramalate production from cimA-integrated I. orientalis strains and future optimization The much higher production yielded by the cimA -integrated strains in general than the one expressing cimA in a plasmid and distinctly different levels of citramalate production among the four integration strains ( Fig. 4 , Fig. 5 A) support the validity of using the piggyBac transposase system to integrate the heterologous gene directly into the I. orientalis genome and exploring the impacts of integration loci and copy numbers on citramalate production. In general, we observed higher citramalate production from cultures using the SC medium ( Fig. 4 A) than from those using the YPD medium ( Fig. 5 A). In the YPD medium, cells quickly consumed glucose and mainly diverted the carbon to their growth and to ethanol production ( Fig. 5 C and F). In both medium conditions, post glucose depletion, the strains shifted their metabolism to consume ethanol for growth ( Fig. 4 , Fig. 5 F). However, ethanol consumption did not lead to further citramalate production. Deletion of pyruvate decarboxylase ( PDC ) and/or downregulation of the TCA cycle have been shown to reduce efflux to ethanol synthesis ( Webb et al., 2018 ; Wu and Eiteman, 2016 ; Xiao et al., 2014 ). However, it is known that the deletion of PDC will negatively affect the cytosolic synthesis of acetyl-CoA. To increase cytosolic acetyl-CoA level, expression of pyruvate dehydrogenase ( Nielsen, 2014 ), and/or non-oxidative glycolysis (NOG) pathways ( Meadows et al., 2016 ) may be considered. Alternatively, it is also conceivable to express CimA in the mitochondria, where both pyruvate and acetyl-CoA are accessible through pyruvate dehydrogenase activity. The engineered strains, in particular the cimA -integrated strains, accumulated glycerol more than the wild-type strain in the SC medium ( Fig. 4 E), suggesting that the expression of citramalate synthase may also cause metabolic imbalance ( Vemuri et al., 2007 ). Conversion of glucose into citramalate yields excess reducing co-factors, which might be offset by the production of glycerol. Production of acetyl-CoA through pyruvate oxidase and the NOG pathway may also mitigate the redox imbalance caused by citramalate production and help increase citramalate yield. Combining the above strategies to further increase the yield of citramalate should be considered for future strain engineering."
} | 4,722 |
34021084 | PMC8166188 | pmc | 8,000 | {
"abstract": "Significance Using food web models that account for juvenile and adult individuals of species, I show that commonly observed differences between juveniles and adults in foraging capacity and predation risk result in larger, more complex communities than predicted by models without stage structure. Based on their species interaction networks these complex and diverse communities would be expected to be unstable, but these destabilizing effects of species interactions are overruled by stabilizing changes in juvenile–adult stage structure. Differences between juvenile and adult individuals hence offer a natural resolution to the diversity–stability enigma of ecological communities."
} | 171 |
31360397 | PMC6566298 | pmc | 8,001 | {
"abstract": "A water insoluble peptide-hydrogel that shows unique compartmentalization by not allowing any exchange to and from the hydrogel and can protect enzymes from denaturation.",
"conclusion": "Conclusions In summary, a unique supramolecular hydrogel is reported which remains insoluble in water and other aqueous or water soluble systems. Importantly, unlike polymeric cross-linked gels, no exchange of solute or solvent is allowed from and to the hydrogel. The hydrogel remained insoluble for a prolonged time in bulk aqueous medium as well as in a variety of other solutions. Notably, the hydrogel showed unusual confinement properties as none of the tested solutes or solvents could be exchanged to and from the hydrogel. Experimental evidence along with theoretical calculations reveals that the gelator molecule dimerizes and the dimers pack themselves to form a layer of PyKC and water which leads to the formation of a tightly knitted network of thin fibres and consequently the hydrogel. The unique confinement ability of the hydrogel emerged due to the combined effect of π–π stacking of pyrene rings and hydrogen bonds in peptide conjugates and confined water. The insolubility of the hydrogel in water can potentially originate from the sub-diffusive behavior of the water molecules which continuously remain confined within the core of the PyKC layer via hydrogen bonds and the hydrophobic barrier by the pyrene rings. The tight packing of the fibres within the hydrogel network and the unusual compartmentalizing properties of the hydrogel are efficiently used to confine and protect enzymes from denaturation in the presence of various denaturing agents and stimuli. The presented system is one of its kind and the insolubility property goes against the present understanding of supramolecular hydrogelation of small molecules. The unique confinement property opens many new doors toward future biomedical applications which are not possible with the present set of such soft materials.",
"introduction": "Introduction Hydrogels are an important class of soft materials owing to their widespread applications. 1 – 4 Classically, in a hydrogel, cross-linked networks are formed by covalent linkages within natural or synthetic polymers where water molecules get trapped through cohesive forces. 5 – 8 The entrapment leads to immobilization of the solvent molecules which eventually results in self-supporting hydrogels. The monomers used to construct cross-linked polymeric networks no longer retain their original physicochemical properties as they get covalently modified. Thus, though the monomers are water soluble, a cross-linked polymeric hydrogel, when dispersed in water, may not get dissolved in bulk water. Similarly, a xerogel (dried gel) of a polymeric hydrogel swells back to its original shape and size in the presence of water. Moreover, solvent molecules of these hydrogels remain in dynamic motion with the solvent outside and both solvent and solute can pass through the gel. 7 Over the last few decades, supramolecular hydrogels of small molecules have emerged as an attractive alternative to polymeric hydrogels. 6 , 8 – 10 In this case, hierarchical self-assembly of small molecules utilizing non-covalent forces results in fibrous structures. These fibres further crosslink through supramolecular interactions to form the gel-network where water molecules get entrapped to form the hydrogel. Unlike polymeric hydrogels, owing to the non-covalent nature of the interactions, each constituent molecule (monomer/gelator) in the network retains its physicochemical characteristics. 6 , 8 Thus, in contrast to polymeric hydrogels, dissolution of supramolecular hydrogels in bulk water can easily be achieved. Dissolution of a supramolecular hydrogel results in a gain in the entropy of the overall system and thus is a thermodynamically favourable process. 8 Supramolecular hydrogels especially the small peptide based ones have major advantages over polymeric hydrogels as these systems are in general non-toxic and biodegradable in nature. 3 , 11 – 18 However, a drawback for bio-medical application comes from the poor stability of such systems. It is important to clarify the term “stability” for this particular report: by stability we mean that the gel remains in the gel state without getting dissolved and retains its rheological properties when immersed in bulk water, buffer, solvent or bio-fluid for a long time. Since dissolution in bulk aqueous medium is a thermodynamically favourable process for small molecule hydrogels, when used as a localized drug delivery system, there is a possibility of easy dissolution of the gel in the bloodstream. Prolonged and sustained use of these hydrogels is thus difficult inside the human body. 14 Although the stability of such hydrogels in buffers and cell culture medium is reported in the literature, it is not clear whether they can fulfil the above-mentioned criteria since no quantitative analysis is available. 19 – 21 An attractive alternative could be a water insoluble and highly stable supramolecular hydrogel which may get dissolved slowly by a biomolecule (stimuli to break the gel) present in the bio-fluid and thus result in sustained and prolonged application. A supramolecular hydrogel made of small molecules has not been reported so far, where the gel does not get dissolved in bulk solvent systems and exchange of solutes as well as solvents with an external bulk medium is highly restricted. Herein, we report a small peptide based ( PyKC , 22 Scheme 1A ) water insoluble supramolecular hydrogel. When immerged in water and various other solutions, the hydrogel did not dissolve and remained insoluble for more than a year. The underlying mechanism behind this exceptional property is revealed with a combination of various analytical experiments and theoretical calculations. Moreover, the unique confinement property is efficiently used to trap and protect protein molecules from external denaturing agents for a long period. Scheme 1 Chemical structures, aggregation pattern and enzyme encapsulation. (A) Chemical structures of peptides used in this study. (B) Pictorial presentation of hydrogelation of PyKC in water through dimerization and the insolubility of the formed hydrogel in water. (C) Schematic representation of the encapsulation of proteins and prevention from denaturation in the presence of various denaturing agents.",
"discussion": "Results and discussion \n PyKC forms a self-supporting hydrogel in Tris buffer (20 mM, pH 8.0) with a minimum gelation concentration (MGC) of 1 wt%. The hydrogel was thermo-reversible and the gel to sol transition temperature ( T g ) was measured to be 75 ± 0.5 °C. The rheological analyses ( Fig. 1A ) showed that the storage modulus ( G ′) of the gel was found to be considerably higher than the loss modulus ( G ′′) over a range of applied angular frequencies. 23 ESI-MS analysis of the hydrogel disclosed the presence of only the disulfide linked dimer of PyKC . Time dependent analytical HPLC analyses of the solution of PyKC revealed that complete conversion to the dimer takes ∼12 h at room temperature ( Fig. 1B ). In the presence of a well-known disulfide bond breaker, dithiothreitol (DTT) (0.1 equivalent), no hydrogelation was observed confirming the critical role of the dimer in gelation. To further verify the actual time required for gelation, time dependent rheology was performed which shows that sol-to-gel transformation takes ∼8 h (Fig. S18 † ) while the equilibrium was obtained at around 12 h when no further change in the G ′′ and G ′ values was observed. The similar completion time for the dimerization process and the equilibration time suggest a critical role of the dimer formation in the gelation process. Fig. 1 (A) Changes in the storage and loss modulus as a function of shear strain and (inset) angular frequency for a 1 wt% hydrogel of PyKC . (B) Time dependent chromatographic analysis of a 0.01 wt% aqueous solution of PyKC showing the formation of a disulfide linked dimer. Interestingly, when a small portion of the hydrogel was added to water and stirred vigorously, no dissolution of the hydrogel in that bulk water was observed ( Fig. 2A and ESI Video S1 † ). The sample was found to be as it was for more than 18 months when kept at room temperature. This observation is unprecedented for any supramolecular hydrogel and prompted us to quantify the dis-solution/insolubility of the hydrogel. A 1 wt% hydrogel of PyKC was added to bulk water and incubated with slow shaking at room temperature (for details, follow the Experimental section). Analyses of aliquots from the bulk water taken at different time intervals showed up to 5% dissolution of the hydrogel within the first seven days and it remained constant thereafter for more than 1 year (Fig. S19 † ). The initial small dissolution of the PyKC dimer can be attributed to the residues which connect the hydrophobic layers to form the fibre as seen from the molecular dynamics simulations discussed later. These residues could easily get dissolved in water at the initial stage. However, no further dissolution of the hydrogel proved the insolubility of the hydrogel in water. The rheological properties of the hydrogel remained unchanged even after keeping the hydrogel in water for seven days. Fig. 2 (A) Photographs of a portion of the 1 wt% hydrogel prepared from PyKC and immerged in bulk water. Photographs taken at different times to show the insolubility of the hydrogel even after 12 months. (B) Photographs of vials containing different aqueous solutions where small portions of the hydrogel (1 wt% PyKC ) containing rhodamine B were immerged and stirred for 10 min. It is worth mentioning that, for a cross-linked polymeric hydrogel, though the network remained insoluble, the water molecules inside the network can move out and that is why their xerogels swell in water to form the hydrogel reproducibly. 1 , 7 , 24 Interestingly, in the present case, the xerogel remained insoluble and unable to swell when water or buffers up to pH 12 were added. Six different dyes (two of each cationic, anionic and neutral category) were separately entrapped in the gels while preparing the hydrogel and the release profiles of the dyes showed very similar results as only ∼5% release (within the first hour) over seven days was observed for all these dyes (Fig. S20 † ). A reverse experiment of incubating the hydrogel (without any dye) in an aqueous solution of methylene blue for seven days showed no incorporation of dye into the hydrogel (Fig. S21 † ). Interestingly, a similar test with perylene (a fused π-system) in acetonitrile also resulted in similar observation (Fig. S22 † ). These results clearly demonstrate that passage of the tested solutes to and from the hydrogel is highly restricted. The observations also raised the question about the exchangeability of the gel entrapped water molecules. To get an insight into that, we took the help of 1 H NMR experiments. Hydrogels prepared in water were added to D 2 O, NaOD and DCl solutions and incubated while shaking. The amount of water exchanged from the hydrogels was estimated from 1 H NMR spectra of the supernatant deuterated solvents after different time intervals (see the Experimental section for details). As can be seen from Fig. 3 and S22, † only ∼3% water molecules could come out of the hydrogel within the first day and no further noticeable change was observed after that. The initial increase can be attributed to the loosely bound water molecules at the surface of the hydrogel. To further confirm this fact, a reverse experiment was carried out where a portion of the hydrogel prepared in D 2 O was suspended in water and the amount of external water that entered the hydrogel was monitored. No noticeable increase in the H 2 O content was observed in that case as well (Fig. S23 † ). Similar studies were performed with two of our previously reported hydrogels. 25 , 26 However, in both cases, the hydrogels get dissolved in bulk H 2 O/D 2 O and all the H 2 O molecules were found in the NMR samples. These results demonstrate that the self-assembly creates a system where both the gel-network and the water of gelation are inaccessible to the surrounding environment. Neither the solvent nor the solute could pass through the envelope created by the hydrogel. This unique confinement property is unprecedented in the literature. Fig. 3 \n 1 H NMR spectra of D 2 O containing glycine before and after incubating the PyKC hydrogel inside the solvent for different time periods to determine the extent of exchange of water of gelation. Buffers (20 mM) of different pH also failed to solubilize the hydrogel ( Fig. 2B , 4A and S24 † ). Several water-miscible organic solvents and aqueous solutions were tested to find the solubility of the hydrogel. The results from all these tests are shown in Fig. 4A (also Fig. S25 † ). Interestingly, though DMF and DMSO could dissolve the hydrogel within 5 min, other solvents showed 4–8% dissolution within the first 24 h with no further changes thereafter up to seven days. When exposed to some extreme conditions like 2 M NaOH, 12 N HCl, and 6 M urea (well-known chaotropic agent), only the acid could solubilize the gel ( Fig. 4A and S26 † ). It is interesting to find that though 6 M urea or 2 M NaOH solutions were unable to dissolve the gel, DMSO, DMF and 12 N HCl dissolve the gel efficiently. At this point, the reason behind such observation is not clear to the authors. The gel also remained insoluble in biological fluids like human blood serum (HBS) ( Fig. 4A and S27 † ). Next, the hydrogel was dispersed in bulk water and the sample was heated at a particular temperature for 1 h with constant shaking and then cooled to room temperature before analysing the bulk water. As can be seen from Fig. 4B , even at 80 °C, only ∼8% dissolution was recorded. Interestingly at 80 °C, which is above the T g of the hydrogel, though the gel melts, the network structure and the insolubility remain intact (Fig. S28 † ). Bringing that sample to room temperature brings back the gel state. Fig. 4 (A) Percentage dissolution of a 1 wt% PyKC hydrogel (20 mM Tris-buffer, pH 8) in different media after 168 h. (B) Percentage dissolution of a 1 wt% hydrogel prepared from PyKC in Tris-buffer (20 mM, pH 8) in bulk water at different temperatures. Though concentrated acid can dissolve the hydrogel, such extreme conditions are not a good choice for future applications. During the search for a suitable system which can break/dissolve the hydrogel, we found that aqueous solutions of disulfide breakers, tris(2-carboxyethyl)phosphine hydrochloride (TCEP), DTT or glutathione (GSH) can do so effectively ( Fig. 4A and S29 † ). When subjected to dissolution with a proteolytic enzyme, trypsin, the gel dissolves and smaller fragments of the peptide were observed in the ESI-MS spectrum of the solution indicating the breakdown of the peptide ( Fig. 4A and S30 † ). Being biomolecules, both trypsin and GSH could be interesting options to break the hydrogel during biomedical applications. The insolubility of this hydrogel is fascinating and it is important to evaluate the gelation process. Densely packed thin fibres (diameter ∼ 9 nm) with an average length of ∼500 nm were observed from FETEM ( Fig. 5A ) of the hydrogel while no such network structure could be found from DTT treated solutions of PyKC . Notably, the fibrous network structure was retained by the hydrogel even after keeping it in water for more than 12 months ( Fig. 5B ). Interestingly, even at a very low concentration of 0.005 wt%, an intense pyrene excimer band (∼475 nm, Fig. 5C ) was observed in the emission spectra of PyKC . 27 The unusually high intensity of the pyrene excimer band can be attributed to possible strong π–π stacking. Further insight into the π–π stacking is obtained from 1 H NMR and PXRD analyses. A PyKC solution in DMSO- d 6 was titrated with H 2 O and the 1 H NMR spectrum was monitored for the aromatic region. In DMSO, the molecule remains in a non-aggregated state and as the water content increased, the aggregation starts. With increasing amount of water, the protons corresponding to the pyrene group showed a clear up-field shift ( Fig. 5D ). The up-field shift is confirmatory evidence for π–π stacking of the pyrene rings. PXRD of a dried film of the hydrogel showed a π–π stacking distance of 3.4 Å (Fig. S31 † ) representing strong π–π stacking. The stacking distance is in agreement with the distance found from electronic structure calculations (2.97 Å) and from the MD simulations (3.9 Å) discussed later. Additionally, to quantify the pores formed within the gel network, gas-adsorption/desorption analysis of the lyophilized hydrogel sample was performed and an average pore diameter of 3.05 nm was observed. The extremely small pores could possibly justify the confinement properties of the hydrogel. Fig. 5 (A) FETEM images of the 1 wt% PyKC -hydrogel in 20 mM Tris buffer pH 8 (inset: zoomed-in picture of the same sample showing the diameter of a fibre). (B) FETEM image of the hydrogel after incubating in bulk water under ambient conditions for 12 months. (C) Concentration (0.001–0.05 wt%) dependent emission spectra of 24 h matured PyKC solution (in 20 mM Tris buffer pH 8) with an increase in concentration ( λ ex = 337 nm). (D) 1 H NMR spectra of 24 h matured samples of PyKC in DMSO- d 6 with varying amounts of water showing strong π–π interaction between the pyrene rings. Though the hydrogel forms via dimerization of PyKC , a separately synthesized PyKC -dimer failed to form the hydrogel. Buffers of pH 7–11 were tested but no gelation was observed under any condition. There are some literature reports which also demonstrate that both the aggregated structure and the gelation highly depend on the method used. 19 , 28 The failure of the dimer to form a gel suggests that, here, dimerization and aggregation proceed simultaneously leading to a network structure. During this process, the water molecules get entrapped within the network. The entrapment is strong enough to prevent the water molecules from exchanging with the exterior. In order to obtain information regarding the importance of the peptide sequence, some control molecules ( Pep-2–6 , Scheme 1A ) were tested for their gelation ability. Only Pep-3 , 5 and 6 were able to form hydrogels but all these hydrogels were found to be spontaneously soluble in water. Hence, it can be concluded that the insolubility is an exclusive property of the PyKC -hydrogel and the molecular structure certainly plays a significant role in providing this property. To understand the molecular origin of the insolubility and unique confinement ability of the PyKC -hydrogel, the molecular packing of the most stable building block of the hydrogel is analyzed. As a first step, to obtain the most stable conformer, the dispersion energies, total energies and binding energies of the geometry optimized PyKC molecules were evaluated using electronic structure calculations. The binding energies for the open and folded conformers were found to be –57.92 and –78.5 kcal mol –1 respectively (Table S1 † ). This signifies that the stacking of the folded dimer of PyKC is energetically more favorable than that of the open dimer. The coordinates of the most stable folded dimer and the charges on each atom are summarized in Table S2. † The snapshot of the geometry optimized folded PyKC dimer with atom labels is shown in Fig. S33. † \n Fig. 6A and B show the optimized geometry of the folded dimer and the stacked dimer respectively. The closest inter-planar distance in the stacked dimer was found to be 2.44 Å which is consistent with the PXRD results (Fig. S31 † ). The stability of the stacked folded dimer is attributed to both T-type and H-type π–π interactions of the pyrene rings as shown in Fig. 6B . Fig. 6 (A) Optimized geometry of a folded PyKC dimer showing a parallel stacking of the pyrene rings. (B) Optimized geometry of two stacked folded PyKC dimers. Pyrene rings are shown in magenta color. (C) Snapshot of the PyKC layer in the presence of water for system (c) from the all-atom MD simulation after 42.5 ns run-length. PyKC is shown in licorice representation. Color code: pyrene – magenta, water – green. Distinct interfaces of PyKC –water are visible showing compartmentalization of water and the hydrogel. The inset shows that the intra-molecular hydrogen bonds in the peptide conjugate and π–π stacking across pyrene rings stabilize the self-assembly of PyKC in the hydrogel. The most stable folded conformer of PyKC was chosen as the initial structure for Molecular Dynamics (MD) simulations. A snapshot of the final configuration of the system (c) from the MD simulation (as mentioned in simulation details) is shown in Fig. 6C (the equilibration of the system is examined by calculating the potential energy and SASA shown in Fig. S34(a) and (b) in the ESI † ). 29 We find that PyKC -dimers self-assemble into a layer-like structure with two distinct interfaces of water and PyKC layers (shown in Fig. 6C ). The inset in the figure demonstrates the molecular structure of the interior of the aggregated PyKC phase. The pyrene–pyrene distance falls within the π–π stacking distance where the nitrogens (N) and oxygens (O) of the peptide conjugates form intramolecular hydrogen bonds with each other stabilizing the conformer. To understand the molecular arrangements of water, pyrene rings and PyKC in the self-assembled structure, we determined density profiles across PyKC layers (shown in Fig. 7A ) where the direction across the layers is considered as the direction of the normal vector. Distinct interfaces between water and PyKC layers are observed demonstrating compartmentalization of water molecules and PyKC . Interestingly, there is a strong overlap between the locations of the pyrene rings and the N/O atoms of the peptide. This clearly confirms that the significant part of the hydrophilic atoms of the peptide conjugates is buried in the core region of the hydrophobic aromatic pyrene rings unlike the arrangements of lipids/surfactants in biological membranes/vesicles. 30 – 33 The hydrophilic peptide conjugates are stabilized by the intra-molecular hydrogen bonds between N–H and O as shown in the inset of Fig. 6C . The number of intramolecular hydrogen bonds of PyKC is calculated using the widely accepted geometric criteria where the distance between the donor and the acceptor is ∼0.35 nm and the angle between the donor–H–acceptor is 30°. 34 – 37 The number of such intra-molecular hydrogen bonds (between N–H···O) is shown in the inset of Fig. 7A for the production run-length. The inset in Fig. 7A shows the radial distribution function (RDF), g ( r ), of the pyrene rings calculated using the equation, 1 where r ij is the distance between two particles i and j , and N is the total number of particles. ρ denotes the mean particle density and the angular bracket denotes time averaging. The RDF of the pyrene rings from the MD simulation reveals that the nearest distance between pyrene rings is ∼0.42 nm across which π–π stacking can operate. Unlike the geometry optimized dimer from electronic structure calculations, aromatic pyrene rings in water form the hydrophobic cluster from both open and closed conformers of PyKC as evident from the intra-molecular distance between individual PyKC in the layer (data not shown). On the other hand, the N/O atoms of the peptide conjugates bring very few water molecules inside the PyKC layer. These water molecules get trapped within the cluster due to two reasons: (a) the hydrogen bonds between the trapped water and (b) the hydrophobic barrier by the pyrene rings. We identified water molecules which were trapped inside the PyKC layers based on the geometric criteria. If a water molecule continuously resides in the core region of PyKC (indicated in the density profile by region (a)) for the entire production run-length of 60 ps, that water is considered as trapped water (TW). TW molecules (shown in Fig. 7A ) follow sub-diffusive dynamics (Fig. S35 † ) demonstrating the extent of confinement and form hydrogen bonds with each other as shown in the inset of Fig. 7A . We calculated the intermittent hydrogen bond auto-correlation function for TW and bulk water (BW) using the following equation, 38 – 40 \n 2 where h TW–TW ( t ) represents the hydrogen bonds between the trapped water (TW) molecules and is 1 if there is a hydrogen bond, otherwise 0. Fig. 7B shows that the TW molecules relax much more slowly than the BW molecules. The change in activation free energy for breaking of the hydrogen bonds is evaluated using reactive flux correlation analysis. 34 , 48 The activation energy (Δ G #break) for hydrogen bond breaking for the TW is higher than that of the bulk water (mentioned in Fig. 7B ). The intermittent hydrogen bond relaxation time of TW is much slower than that of the BW and the relaxation time-scales of TW are comparable to the hydrogen bond relaxation time of confined water near biomolecules. 41 These results clearly indicate that the extremely slow dynamics of the trapped water molecules are due to the confinement of water within the PyKC layer and are consistent with the experimental observations of the least water transport across the hydrogel. Therefore, the insolubility and the unique compartmentalization ability of the hydrogel are attributed to the specific molecular packing of PyKC , where peptide conjugates are stabilized by the intramolecular hydrogen bonds and the aromatic pyrene clusters are stabilized by the π–π interactions. Fig. 7 (A) Density profile of the PyKC layer across the normal from MD simulation. Distinct interfaces of PyKC –water are visible showing the compartmentalization of the hydrogel and water. The N/O atoms of the peptide conjugates stay within the layer and bring few water molecules inside the core of the layer. Water molecules residing continuously in the core region are shown within the vertical lines denoted by the area (a) and labelled trapped water (TW). Inset: RDF ( g ( r )) of pyrene–pyrene shows the first peak located at 0.4 nm where π–π stacking of pyrene rings operates. The number of intra-molecular hydrogen bonds between N and O of the peptide conjugate is shown for the production run. These hydrogen bonds contribute to stabilizing the molecular packing of the PyKC hydrogel. The number of hydrogen bonds among trapped water (TW–TW) molecules is shown for the time for which TW remains confined within the core of the PyKC layer. (B) Intermittent hydrogen bond auto-correlation function of TW and bulk water (BW) showing very slow relaxation of the TW. The slow hydrogen bond relaxation time ( τ HB ) and high activation energy (Δ G #break) of hydrogen bond breaking of TW compared to those of BW indicate the possibility of less water transport across the hydrogel. Thus PyKC forms dimers through a disulfide linkage and the dimers self-assemble to form a water insoluble hydrogel. The self-aggregation is stabilized through the strong π–π interactions of the pyrene rings and intramolecular hydrogen bonds between the nitrogen and oxygen atoms of the peptide conjugates. Since peptide conjugates are hydrophilic in nature, they bring few water molecules. These water molecules remain confined via hydrogen bonds among trapped water (TW) molecules. The hydrogen bonds among the trapped water molecules and the hydrophobicity of the pyrene rings slow down water transport across the PyKC layer resulting in an unusual confinement in the system. The insolubility of the hydrogel and its exceptional compartmentalizing ability can be utilized in various fields like regenerative medicine, tissue engineering, materials science, etc. As a preliminary application, we envisioned that the very tight packing of the nano-fibres can be used to create a protective envelope for proteins from denaturation. Proteins are prone to get denatured even due to minute changes in the environment and thereby lose their activity. Protecting proteins and biomolecules from the environment as well as from various denaturants is a challenging task. Various methods, including immobilization of proteins on a solid support, chemical modification, using molecular chaperons or polymeric hydrogels, etc. have been applied for this purpose. 42 – 49 However, the reported methods are usually low in efficiency and could not provide a long life to the proteins under antagonistic conditions. We realized that, if a protein can be entrapped in the PyKC -hydrogel, (a) it can be protected from any external denaturant due to the confinement properties of the hydrogel, and (b) because of the tightly knitted network, there may not be enough space for the entrapped proteins to unwind themselves in response to external stimuli like heat. Based on this hypothesis, as a proof of concept, two different enzymes, viz. , Chromobacterium viscosum lipase (CV-lipase) and Candida rugosa lipase (CR-lipase), were tested. The enzymes were carefully chosen based on the facts that (a) the protein sequences do not contain any cysteine residue, (b) treatment with TCEP/GSH/DTT did not affect their activity, and (c) they are non-proteolytic in nature. Enzymes were trapped inside the hydrogels and dispersed in required buffers. The FETEM image of the hydrogel containing the enzyme showed the presence of the enzyme molecules trapped in the gel network ( Fig. 8A ). After seven days, the gels were re-dissolved in TCEP and the released proteins showed very similar CD to the native protein ( Fig. 8B and S36 † ) which demonstrates that the proteins could retain their folded conformation inside the hydrogel. In order to overrule the possibility of any leakage of the trapped enzymes from the hydrogel, a BODIPY-labelled lipase was prepared, trapped in the hydrogel and subjected to release study by placing the hydrogel in bulk water as in the case of the other dyes described before. Similar to the dye release results, only ∼5% leakage was observed during the initial hour which remained unchanged for at least 7 days (Fig. S37 † ). For enzyme activity studies, several enzyme trapped hydrogel samples were prepared for each of these enzymes and as controls, similar samples of the free enzymes were also prepared in the absence of the gelator. At different time intervals, the enzyme activities of the gel-entrapped enzymes and the control samples were measured. Interestingly, the activity of both free lipases decreased significantly with time and they lost their activities completely within 6 days. However, for the gel trapped enzymes, there is an initial loss of activity (∼7–10%) in the first 24 h and thereafter no significant change was observed up to 7 days ( Fig. 9A ). Importantly, they retained up to ∼80% of their activities even after 30 days. Fig. 8 (A) FETEM image of a 1 wt% hydrogel prepared from PyKC in 20 mM Tris buffer (pH 8) containing CV-lipase. The yellow arrows indicate the enzymes embedded in the network. (B) CD spectra of CV-lipase under free and gel-trapped conditions to identify any denaturation due to encapsulation and incubation at room temperature for 7 days. Fig. 9 (A) Retention of the catalytic activities (%) of the gel-trapped and free enzymes at different time intervals when incubated at room temperature. (B) Retention of the catalytic activities (%) of CV and CR lipases as a function of temperature under PyKC hydrogel-trapped and free conditions. (C) Retention of activity (%) at different time intervals by the gel-trapped CR-lipase when dispersed is methanol or 6 M urea solutions. (D) Comparison of retention of activity by the CR-lipase under free and gel-trapped conditions when exposed to buffer solutions of different pH for 1 h. Similar experiments were performed for both enzymes where each sample was heated at a particular temperature for 1 h prior to cooling to room temperature and activity measurements. As expected, the free enzymes lost their activities drastically with increase in temperature and at 60 °C, only ∼10% activities were observed while the gel-trapped enzyme retained 75% activity even at 70 °C ( Fig. 9B ). Moreover, maintaining the temperature at 40 °C for seven days resulted in only ∼18% loss in activity for the gel-trapped CR-lipase (Fig. S38 † ). Exposure to other denaturing agents like 6 M aqueous urea solution or methanol (alcohols are known inhibitors for lipases 50 ) could not impart any significant changes on the activities of the enzymes as only 10–15% loss was noted after seven days of exposure while the free enzymes were found inactive in the presence of these external agents ( Fig. 9C ). Moreover, suspending the hydrogel in buffers of different pH for 1 h did not make any difference in the activity of the trapped-enzyme ( Fig. 9D ). However, the free enzymes showed the typical pH response of lipases with the highest activity at pH 7. 50 These results prove our hypothesis and show that the hydrogel can be used as an effective protecting envelope for biomolecules. We are in the process of expanding the methodology with other biomolecules and results will be reported in due course."
} | 8,360 |
33426883 | null | s2 | 8,002 | {
"abstract": "Efforts to expand the scope of ribosome-mediated polymerization to incorporate noncanonical amino acids (ncAAs) into peptides and proteins hold promise for creating new classes of enzymes, therapeutics, and materials. Recently, the integrated synthesis, assembly, and translation (iSAT) system was established to construct functional ribosomes in cell-free systems. However, the iSAT system has not been shown to be compatible with genetic code expansion. Here, to address this gap, we develop an iSAT platform capable of manufacturing pure proteins with site-specifically incorporated ncAAs. We first establish an iSAT platform based on extracts from genomically recoded "
} | 168 |
34791832 | PMC8787393 | pmc | 8,003 | {
"abstract": "Abstract In flexible electronics, appropriate inlaid structures for stress dispersion to avoid excessive deformation that can break chemical bonds are lacking, which greatly hinders the fabrication of super‐foldable composite materials capable of sustaining numerous times of true‐folding. Here, mimicking the microstructures of both cuit cocoon possessing super‐flexible property and Mimosa leaf featuring reversible scatheless folding, super‐foldable C‐web/FeOOH‐nanocone (SFCFe) conductive nanocomposites are prepared, which display cone‐arrays on fiber structures similar to Mimosa leaf, as well as non‐crosslinked junctions, slidable nanofibers, separable layers, and compressible network like cuit cocoon. Remarkably, the SFCFe can undergo over 100 000 times of repeated true‐folding without structural damage or electrical conductivity degradation. The mechanism underlying this super‐foldable performance is further investigated by real‐time scanning electron microscopy folding characterization and finite‐element simulations. The results indicate its self‐adaptive stress‐dispersion mechanism originating from multilevel biomimetic structures. Notably, the SFCFe demonstrates its prospect as a super‐foldable anode electrode for aqueous batteries, which shows not only high capacities and satisfactory cycling stability, but also completely coincident cyclic voltammetry and galvanostatic charge–discharge curves throughout the 100 000 times of true‐folding. This work reports a mechanical design considering the self‐adaptive stress dispersion mechanism, which can realize a scatheless super‐foldable electrode for soft‐matter electronics.",
"conclusion": "3 Conclusion Introducing the self‐adaptive stress dispersion mechanism into the structure design, this work reports a universal approach to fabricating super‐foldable conductive electrode that can bear 100 000 time true‐folding without structure damage and conductivity degradation. The biomimetic strategies for both the preparation method and material structures were verified to be effective for achieving super‐foldable properties. Through the real‐time SEM observation of the folding process and their mechanical simulations, the relationship between biomimetic structures and super‐foldable performance is visually revealed. More importantly, a set of universal principles for constructing super‐foldable composite electrodes is identified as follows. (1) The electrode had better possess layered network structures in which nanofibers are slidable, and the layers are microseparable. (2) The electroactive substances on nanofibers should have special structures to cope with a certain bending. (3) Under a true‐folding state, the crease should be capable of forming “ \n ε \n ”‐like structures containing bulged layers, dispersed arcs, and slidable microtraces for 3D stress dispersion. In summary, the high‐performance electrode, exceptional folding properties, and revealed mechanism identify key materials and techniques for fabricating super‐foldable devices even assembled electronic equipment.",
"introduction": "1 Introduction Foldable electronics has drawn increasing attention from concept to market. [ \n \n 1 \n , \n 2 \n , \n 3 \n , \n 4 \n , \n 5 \n , \n 6 \n \n ] It has become evident that the conventional bendable pattern cannot satisfy the high requirements in the practical application of flexible electronics owing to reliability and safety issues at unintentional extreme deformation of flexible electronic products. The increasingly functional requirements, such as wearability, implantability, and portability, of flexible products also promote the eager for super‐foldable electronic materials capable of sustaining multiple true‐folding tests (Figure S1 , Supporting Information). [ \n \n 7 \n , \n 8 \n , \n 9 \n \n ] Flexible electronic materials are widely known to be the key components of flexible devices. Typically, they present the structures of functional matters inlaying on flexible conductive bases, which have been extensively studied for flexible electrodes, sensors, triboelectric nanogenerators, etc. [ \n \n 10 \n , \n 11 \n , \n 12 \n , \n 13 \n , \n 14 \n , \n 15 \n , \n 16 \n \n ] To improve the flexibility to foldability, great effort has been made from the structural design of both flexible conductive bases and composite structures. Unfortunately, the super‐foldable performance are so challenging that it has not been attained thus far. This is because the local stress generated at the crease under true‐folding extremely exceeds that under bending or pseudo‐folding by several orders of magnitude (Figure S1 , Supporting Information). Considerable stress definitely causes damage to chemical bonds, eventually leading to fracture during the repeated folding of conductive bases without special structural design. This is attributed to the short‐range‐force nature and incapability of chemical bonds to sustain large deformations ( Figure \n 1 a ; Note S1 , Supporting Information). [ \n \n 17 \n , \n 18 \n \n ] In addition, the realization of high functional performance while maintaining the super‐foldability of electronic materials must also be considered. In view of these, at least four problems must be solved in their design. (1) Super‐foldable conductive bases must be prepared. (2) How can a firm bond that prevents detachment between functional materials and super‐foldable bases be achieved? (3) How can the super‐foldability of bases be protected from the negative effect of inlaying functional materials? (4) The electrochemical/electronic performance based on the foregoing must be maximized. Consequently, the attainment of super‐foldable and high‐performance electronic materials remains extremely problematic. Figure 1 Super‐foldable SFCFe and its design principle. a) Schematic of short‐range force limit of chemical bonds in conventional conductive materials incapable of bearing repeated true‐folding. b–e) Biomimetic structural design of SFCFe enabling numerous true‐folding. f–m) Mechanical simulations showing the relationship between structure and stress at different hierarchies: (f, g) stress distributions in different 3D folding structures at crease, (h, i) stress distributions in bent 2D layers of different link types, (j–m) maximum stress values and stress distributions in bent nanofibers of different composite structures. To improve the flexibility of electronic materials, different hierarchical structures have been designed. Pore engineering is a widely adopted strategy for improving flexibility. For example, macropores have been introduced into carbon web nanofibers, and the resultant bamboo‐like and golden‐toad‐egg‐like nanofiber webs have been demonstrated to have high flexibility and even foldability over a limited times. [ \n \n 19 \n , \n 20 \n \n ] The presence of numerous micropores and mesopores has also been proved to enable materials to sustain multiple folding. [ \n \n 21 \n \n ] The adjustment strategy for interlaminar interactions is also found effective in boosting flexibility. Some studies have indicated that the increase in interlaminar interactions can result in considerable tensile strength, and provide materials with good mechanical flexibility. These materials include cross‐linked N‐doped carbon nanofiber/Polyaniline networks, graphene films with sequential ionic and π bridging, and MXene/graphene films. [ \n \n 22 \n , \n 23 \n , \n 24 \n \n ] While other studies have demonstrated the effectiveness of using separable layers, such as lamellar porous carbon stacks and expanded porous graphene films, to allow folding hundreds of times. [ \n \n 25 \n , \n 26 \n , \n 27 \n \n ] The assembly strategy is also important for promoting flexibility. For instance, the assembly of graphene oxide platelets into honeycomb‐like macroporous structures can increase their mechanical flexibility. [ \n \n 28 \n \n ] A carbon nanotube film with an aligned arrangement of few‐walled nanotubes can bear severe bending even folding for a hundred times. [ \n \n 29 \n \n ] The current understandings of the relationship between structure and folding is limited and biased, just like the blind touching the elephant. Consequently, an integrated design of hierarchical structures to achieve super‐foldability has not been proposed and implemented. After millions of years of evolution, nature has endowed organisms with rich structures and functions that provide remarkable inspiration for developing new materials. [ \n \n 30 \n , \n 31 \n , \n 32 \n \n ] For example, cuit silkworm cocoons have super‐flexible features after reeling cocoon processing. Moreover, the Mimosa leaf possesses reversible and scatheless foldable capability when subjected to external stimulus (Figure 1b,c ; Figure S2a , Supporting Information). If the combined mimicking of the super‐flexible hierarchical structures of cuit cocoons and the scatheless‐folding composite interfaces of Mimosa leaves can be achieved, then a super‐foldable composite may be manufactured (Figure 1b–e ; Figure S2 , Supporting Information). Silkworms produce cocoons by spinning and cocooning, but the resultant raw cocoons are rigid and possess cross‐linked structures (Figure S3a,b , Supporting Information). However, a facile reeling cocoon process can transform rigid cocoons into cuit cocoons with excellent foldable features. In this process, structural changes including unfastened junctions, slidable fibers, separable layers, and compressible networks are generated (Figure S3c,d , Supporting Information). Our further study for the first time revealed that these structural changes could result in intelligent deformation according to the bending degree, and form a layered nanofiber network “ \n ε \n ” structure at the crease under true‐folding, which performs a key function in super‐foldable performance (Figure 1e ; Figure S4 and Note S2 , Supporting Information). Under normal conditions, Mimosa leaves are open; however, they rapidly fold upon stimulation. [ \n \n 33 \n \n ] Such a sensitive change is due to the important role of the pulvinus, which is composed of a vascular tissue as the core and parenchyma tissue formed by thin‐walled cells as the shell. Under normal conditions, parenchymal cells on both sides are filled with water. Once a stimulus occurs, one side of the parenchymal cells loses water and shrinks, resulting in leaf folding (Figure 1c ). The adjustable intervals due to shrinking and stable interfaces ensure the intactness of cells. To quantitatively verify the role of the aforementioned biological structures during folding, mechanical simulations were implemented using three extracted hierarchies (Figure 1f–m ). At the 3D assembly hierarchy, the stresses of biomimetic separable‐layer structures and ordinary block plate structures during folding are calculated. The former can disperse the stress to each assembly hierarchy through ε deformation. The distributed stress is considerably less than that of the latter, which is concentrated at the crease (Figure 1f,g ). In the 2D layer hierarchy, the bending stress in biomimetic non‐crosslinked and crosslinked layer models was simulated. The results indicated that crosslinked structures rapidly boosted stress until fracture with increasing flexure, whereas biomimetic non‐crosslinked structures could effectively disperse the stress through fiber sliding (Figure 1h,i ). At the 1D hierarchy of composite fibers, the bending stress distributions in three composite structure models, i.e., biomimetic fiber/cones, fiber/pillars, and fiber/dense‐wrapping, were simulated (Figure 1j–m ). The simulation shows that the biomimetic fiber/cone has a better stress dispersion. The maximum stresses in the other two composite fibers reached 1.3 and 4.5 times that of the fiber/cone under the same degree of bending(Figure 1j ). Based on the above analysis, a biomimetic fiber /cone‐array self‐adaptive web structure is proposed to develop super‐foldable composite. To prove the feasibility of this biomimetic design strategy and verify the prospects of super‐foldable electrodes, FeOOH, which has multiple functions in energy, sensor and catalysis, [ \n \n 34 \n , \n 35 \n , \n 36 \n , \n 37 \n \n ] is selected for carbon nanofiber loading to fabricate C‐fiber/FeOOH‐nanocones web nanocomposites. Notably, their structures, functions, and preparation processes were bioinspired (Figure S2 , Supporting Information). Specifically, electrospinning is applied to mimic the silkworm spinning and cocooning processes to obtain polymer webs. In‐situ gradient‐temperature carbonization, followed by liquid deposition, is applied to simulate the reeling cocoon process and biological super‐foldable structures to acquire the fluffy composites. [ \n \n 38 \n , \n 39 \n \n ] Accordingly, composites that are conductive and super‐foldable are produced by the biomimetic process along with artificial control. By combining the biomimetic techniques in terms of process and function, the super‐foldable C‐web/FeOOH‐nanocone material (SFCFe) was successfully prepared. This material can readily bear more than 100 000 times repeated true‐folding without microstructural damage and electrochemical property changes—certainly a breakthrough advancement in flexible electrode materials.",
"discussion": "2 Result and Discussion 2.1 Structural Characterizations of SFCFe The macro and micromorphologies of structures from polymer precursors to the final composite products are displayed in Figure \n 2 \n and Figure S5 in the Supporting Information. The C‐web substrates are first prepared through biomimetic electrospinning and in situ gradient‐temperature carbonization, causing the precursors change color from white to black (Figure 2a,b ). The gradient‐temperature carbonization involves two processes: preoxidation in air for precursor stability and further carbonization in N 2 . The former removes adsorbed water and resident solvent, and starts cyclization and dehydrogenation reactions of PAN. Thus heat‐resistant ladder structures with well‐maintained morphology are produced, which enables morphology retention in the following high‐temperature carbonization. The two combined processes simultaneously achieve four changes including junction unfastening, layer separation, network unloosening, and pore generation similar to reeling cocoon process, and enable the successful preparation of conductive super‐flexible C‐web substrates like cuit cocoon structures (Figures S6 and S7 , Supporting Information). During the subsequent mild liquid deposition, the desired biomimetic composite structures of FeOOH nanocones inlaid on carbon nanofiber surface form through mild‐temperature protection, morphology control, and time adjustment. It proceeds according to the following reactions\n \n (1) \n CO N H 2 2 + H 2 O → 2 N H 3 + C O 2 \n \n \n (2) \n N H 3 + H 2 O → N H 4 + + O H − \n \n \n (3) \n F e 3 + + 3 O H − → Fe OH 3 \n \n \n (4) \n Fe OH 3 → FeOOH + H 2 O \n \n Figure 2 Characterizations of SFCFe. a,b) Optical photographs of PAN film, C‐web, and SFCFe. c–f) SEM images. g,h) TEM images (inset: SAED image). i) HRTEM image. j) XRD patterns. k) Raman spectra. l) EDS mapping images. m–o) XPS high‐resolution spectra of Fe 2p (m), O 1s (n), and C 1s (o). Scanning electron microscopy (SEM) observations show that the obtained SFCFe has hierarchical layer network structures woven by uniform straight nanofibers covered with fuzzy substances; the nanofiber diameter is ≈400 nm, and the mesh is several microns in size (Figure 2c,d ; Figure S8 , Supporting Information). Surface substances were found capable of passing through the mesh and growing firmly on each fiber inside the film because of surface hydrophilicity from pretreatment, contributing to improvement of electrochemical properties (Figure S9 , Supporting Information). Enlarged SEM and transmission electron microscopy (TEM) images indicate that fuzzy fibers are coaxial structures composed of vertically grown FeOOH shells on carbon nanofiber cores (Figure 2e–g ). Each FeOOH shell is cone‐like in morphology mimicking the interface structures of Mimosa leaf, which enables scatheless folding (Figure 2h ). Its length and bottom diameters are ≈100 and ≈20 nm, respectively. Further structural characterizations revealed its polycrystalline structures and good crystallinity as determined from diffraction rings in its selected area electron diffraction (SAED) image and clear lattice spacing of 0.25 nm in its high‐resolution transmission electron microscopy (HRTEM) image, respectively, benefitting fast electrochemical reaction (Figure 2h,i ). Moreover, the grown density and loaded mass of FeOOH nanocones can be well controlled by simply adjusting the reaction time, contributing to the optimization toward both super‐foldable and high‐electrochemical properties. Condition experiments indicate that reaction conditions such as temperature, time, and additive, will influence the FeOOH morphologies and composite constructions, and thus the mechanical flexibility. For temperatures of 30 °C, the reaction nearly does not start (Figure S10 , Supporting Information). With the temperature increase, the reaction begins to accelerate. The temperature of 40 °C only produces large aggregated FeOOH clusters distributed unevenly on fiber surface, and their further growth causes crosslinks of nanofibers and layers, which are unfavorable for flexibility (Figure S11 , Supporting Information). While the higher temperature of 50 °C leads to the uniform and dense growth of FeOOH nanocones at 6 h, but afterwards they will become overcrowded and stuck the networks, which is disadvantageous for folding (Figure S12 , Supporting Information). When the temperature reaches 60 °C, a too fast reaction speed makes the FeOOH deviate from cone‐like structures and become more crowded, resulting in the composites stiff and brittle like the raw cocoons (Figures S13 and S14 , Supporting Information). Seen from above results, the optimal condition for desired biomimetic structures is reaction at 50 °C for 6 h, because at that time the FeOOH have cone‐like morphologies, and distribute uniformly on fiber surface, and do not cause crosslinks of nanofibers and layers. As for the Na 2 SO 4 additive, comparison experiments show that its addition as a strong electrolyte can accelerate the crystal nucleation and growth (Figure S15 , Supporting Information). Meanwhile, it also controls the cone‐like morphology of FeOOH, because the SO 4 \n 2− ions with cone‐like regular tetrahedral configurations may be able to adsorb on specific crystal planes and induce their anisotropic growth (Figure S16 , Supporting Information). Their structures were further characterized by X‐ray diffraction (XRD) and Raman. The successful formation of these composite structures is proved by the appearance of broadened diffraction peaks of both graphite (JCPDS no. 41–1487) and α ‐FeOOH (JCPDS no. 18–0639) in the XRD patterns, which may be caused by the partially crystalline structures of carbon and the nanosize effect of FeOOH, respectively (Figure 2j ). [ \n \n 40 \n \n ] The Raman spectrum of the C‐web shows two peaks at 1344 and 1590 cm −1 in the blue region, corresponding to the D and G bands of typical carbon materials. A higher ratio of G band to D band (I G /I D = 1.3) indicates the relatively high graphitized structures of the C‐web (Figure 2k ). Seven peaks, i.e., 246, 300, 388, 475, 551, 694, and 990 cm −1 , appear in the Raman spectrum of pure FeOOH in the yellow region; these values well conform with those reports regarding α ‐FeOOH. The SFCFe's Raman spectrum displays peaks of both substances, indicating their successful combination. Their elemental composition and binding states are measured by energy dispersive X‐ray spectroscopy (EDS) and X‐ray photoelectron spectroscopy (XPS). Both the EDS and XPS results show the existence of Fe, C, and O elements that are homogeneously distributed on the nanofiber (Figure 2l–o ; Figures S17–S20 , Supporting Information). The curve fit of Fe 2p spectrum exhibits two major peaks, 711.8 and 725.2 eV, corresponding to Fe 2p 3/2 and Fe 2p 1/2 with shake‐up satellites at ≈718.3 and 731.7 eV, which characterize Fe 3+ in FeOOH (Figure 2m ). [ \n \n 41 \n \n ] The peaks of O 1s spectrum are centered at ≈530.2, 531.7, and 532.8 eV, corresponding to the oxygen element in the Fe–O–Fe, Fe–O–H, and H–O–H bonds, respectively (Figure 2n ). All the above characterizations indicate that the desired composite structures have been successfully obtained. 2.2 Super‐Foldability of SFCFe The folding properties and corresponding structural analysis are shown in Figure \n 3 \n . Figure 3a shows our self‐made folding machine that can automatically conduct folding tests and record folding times. More importantly, it does not only satisfy the true‐folding operation up to the standard, but also ensure folding force uniformity and folding position accuracy (Figure S21 and Movie S1 , Supporting Information). In folding studies, the three requisites above must all be satisfied simultaneously; otherwise, reporting the material as foldable and their folding times is pointless. Figure 3b shows the unfolded, bent, and fully folded states of SFCFe on the folding machine. An optimized super‐foldable SFCFe is eventually obtained through persistent exploration for materials and repeated folding tests. Amazingly, it can sustain more than 100 000 times of true‐folding without microstructure damage or conductivity changes (Figure 3c–h ). However, two microtraces that are invisible to the naked eye appear; they result from nanofiber slide and density change for improving stress dispersion and structural self‐protection (Figure 3c ). Further, the observation and analysis of creases indicate that not only the composite‐nanofibers have no fracture or damage, but also the FeOOH‐nanocones have no detachment from the nanofiber surface, demonstrating the feasibility of inlaying or assembling microdevices on super‐foldable substrates (Figure 3d–g ). The microstructures of SFCFe at different folding times have also been tracked, and results show that they are intact (Figure S22 , Supporting Information). By contrast, the C‐web/FeOOH composites with overcrowded FeOOH loading generate structural damage after one time folding, and the accumulated damage results in material fracture after limited folding times (Figures S23–S25 , Supporting Information). This indicates that their its folding capacity is history‐independent, and they have no fatigue accumulation; consequently, they can be folded numerous times without limit. Besides the above arbitrary folding times, the SFCFe also features an arbitrary directional folding ability, as demonstrated by their different folding forms (Figure S26 , Supporting Information). In addition, the SFCFe sample is tested by severely twisting and rolling it around an ultrathin rod with a 0.5‐mm radius. After removing the applied external force, the sample quickly recovers its original shape and shows no structural fractures (Figure S27 , Supporting Information). Such excellent twisting and rolling properties play an auxiliary role toward attaining super‐foldable performance. The foregoing demonstrates that the super‐foldable property of arbitrarily repeated folding has been realized for the SFCFe. This also means that stable electrochemical performance can be ensured when the SFCFe is subjected to repeated folding. Figure 3 Super‐Foldable characterizations of SFCFe. a) Schematic of repeated true‐folding test on a folding machine. b) Schematic of a complete true‐folding process. c–g) SEM images of SFCFe after 100 000 times folding. h) Conductivity change curves during 100 000 times folding. i–m) Typical states during real‐time SEM observation of folding process. n) Schematic of “ \n ε \n ”‐like structures at crease at 180° true‐folding. o–r) Enlargement and analysis of “ \n ε \n ” structures in (n). 2.3 Working Mechanism of SFCFe To reveal its super‐foldable mechanism, we have also developed a dynamic folding observation system for the real‐time tracking of microstructural changes during folding. Five typical dynamic states are captured and displayed in Figure 3i–m \n . Initially, the SFCFe was flat (Figure 3i ). As the bending degree is increased, stress among adjacent layers is gradually generated, and the layers begin to separate, forming wavy bulges to disperse stress (Figure 3j ). With further bending, stress concentrates at the crease, forming two folding arcs to disperse the stress (Figure 3k,l ). When the SFCFe is folded to 180°, a smooth “ \n ε \n ” structure eventually forms, as shown in Figure 3m . Such constructions are the true root of the super‐foldable property; the structures are virtually the same as those in a folded cuit cocoon. The real‐time unfolding process shows that the “ \n ε \n ” gradually disappears, and the initial flat state of structures is virtually recovered (Figure S28 , Supporting Information). The entire folding and unfolding processes of SFCFe exhibit a self‐adaptive stress dispersion behavior through intelligent deformation according to the bending degree. In general, the above dynamic observation is extremely vivid and reliable for folding mechanism studies; it is possibly the first real‐time SEM record of the folding process worldwide. By analyzing the “ \n ε \n ” folding structure, the stress dispersion functions can be examined in detail (Figure 3n ; Figure S29 , Supporting Information). The “ \n ε \n ” structure contains three typical regions: bulged layers, dispersed arcs, and folded traces. The bulged layers are caused by layer separation, which can disperse the stress along the layer direction (Figure 3o ). The two dispersed arcs with smooth shapes prevent stress concentrations (Figure 3p ; Figure S23g–i , Supporting Information). During arc formation, the inner space of the crease is redistributed, and the layers at the arcs are compressed. As a result, the stress at the top of the two arcs is dispersed. As for the two folded traces, they are just located at the same position as the two dispersed arcs and extend toward the inside, which can disperse the stress in the thickness directions by the sliding of nanofibers (Figure 3q,r ). In summary, the formation of the \n ε \n structure is accompanied by inner space redistribution, which can effectively disperse stress at various levels and directions and eventually realize the super‐foldable property. 2.4 SFCFe as Super‐Foldable Anode Materials The electrochemical properties of SFCFe composites were studied using a three‐electrode system in 6 m KOH ( Figure \n 4 \n ). First, the electrochemical properties of the C/FeOOH composites obtained at different synthesis times (3, 6, and 9 h) were compared. Based on the comparison of geometric areas of cyclic voltammetry (CV) curves and discharge times of galvanostatic charge‐discharge (GCD) curves, the specific capacities of composites were observed to display a volcanic‐shape trend with increasing synthesis time, achieving the peak value at 6 h (Figure S30a,b , Supporting Information). The results of electrochemical impedance spectroscopy (EIS) show that the charge transfer resistance ( R \n ct ) is positively related to the loading mass of FeOOH. However, excessive loading is not advantageous because overdense FeOOH (such as composites obtained at 9 h) limits the transfer of electrons/ions and availability of atoms (Figure S30c , Supporting Information). The SFCFe obtained at 6 h was subsequently selected for examining the electrochemical properties in detail. Its CV curves deviate from the rectangle with a larger potential window of 0 to −1.2 V, which indicates the SFCFe's partly faradaic energy storage behavior (Figure S31–S33 , Supporting Information). The similar shapes of these curves from 2 to 20 mV s −1 indicate satisfactory conductivity (Figure 4a ). Consistent with CV results, the GCD curves are non‐linear with plateaus, also indicating the partly faradaic energy storage feature of SFCFe (Figure 4b ). The calculation results show the SFCFe's high specific capacity and satisfactory rate capability: its maximum capacity (152 mAh g −1 at 1 A g −1 ) is 7, 3, and 1.4 times higher than that of C‐web (22 mAh g −1 ), C/FeOOH at 3 h (48 mAh g −1 ), and C/FeOOH at 9 h (111 mAh g −1 ), respectively (Figure S25 , Supporting Information). It can be charged and discharged at a high current density exceeding 20 A g −1 and still maintained a specific capacity of 45 mAh g −1 at 20 A g −1 (Figure 4c ). Reaction dynamics were further investigated to determine the origin of its outstanding electrochemical performance (Figure 4d–f ). As shown in Figure 4d , for reduction and oxidation processes, the b values are 0.73 and 0.88, respectively, which means its current contains both surface capacitive and diffusion‐controlled processes. The calculated capacitive contribution values indicate a boost with the increase of scan rates, reaching 86% for the total charge storage at 5 mV s −1 (Figure 4e,f ). Thus, the dominant capacitive contributions simultaneously result in high capacity and satisfactory rate capability. Compared with other materials reported in the literature, the SFCFe fabricated in this work exhibits the highest specific capacity among the flexible electrodes of FOOH composites. Moreover, foldable FeOOH electrodes have not been reported, not to mention the super‐foldable ones (Table S1 , Supporting Information). Figure 4 Electrochemical performance of SFCFe as super‐foldable anode materials. a–c) CV, GCD, Cs curves of SFCFe. d) Relationship between peak currents and scan rates. e) Capacitive and diffusion‐controlled contributions for charge storage at 5 mV s −1 . f) Normalized contribution ratios of capacitive and diffusion‐controlled capacities at different scan rates. g–i) CV, GCD, and capacity retention curves at different bent angles. j–l) CV, GCD, and capacity retention curves during 100 000 times repeated folding. m) Cycling property of SFCFe. The super‐foldable properties of SFCFe have been demonstrated from aforementioned three aspects, i.e., of micrology, micromechanics, and electricity, and herein it will be further verified through electrochemistry. The tests are conducted by measuring electrochemical properties at different folding angles and folding times. On the one hand, the SFCFe is in situ bent to different angles, and their electrochemical properties are measured at corresponding angles. Results show that the CV and GCD curves are basically coincident and their corresponding capacities are nearly changeless at different bent angles, respectively (Figure 4g–i ). On the other hand, the electrochemical properties of SFCFe are recorded during 100 000 times repeated folding. Remarkably, its CV and GCD curves are nearly overlapped, and capacities are almost the same throughout the repeated folding process, which is often difficult to achieve (Figure 4j–l ). Besides, the cycling properties of the SFCFes after folding for 100 000 times are tested, and display a capacity retention of 84% after 3000 times (Figure 4m ). The electrochemistry results obtained at the above two folding forms manifest our SFCFe can bear 100 000 times folding without structure damage or material detachment."
} | 7,833 |
35619647 | PMC9128571 | pmc | 8,004 | {
"abstract": "Biofilms are arguably the most important mode of growth of bacteria, but how antibiotic resistance emerges and is selected in biofilms remains poorly understood. Several models to study evolution of antibiotic resistance have been developed, however, their usability varies depending on the nature of the biological question. Here, we developed and validated a microfluidic chip (Brimor) for studying the dynamics of enrichment of antibiotic-resistant bacteria in biofilms using real-time monitoring with confocal microscopy. In situ extracellular cellulose staining and physical disruption of the biomass confirmed Escherichia coli growth as biofilms in the chip. We showed that seven generations of growth occur in 16 h when biofilms were established in the growth chambers of Brimor, and that bacterial death and growth rates could be estimated under these conditions using a plasmid with a conditional replication origin. Additionally, competition experiments between antibiotic-susceptible and -resistant bacteria at sub-inhibitory concentrations demonstrated that the antibiotic ciprofloxacin selected for antibiotic resistance in bacterial biofilms at concentrations 17-fold below the minimal inhibitory concentration of susceptible planktonic bacteria. Overall, the microfluidic chip is easy to use and a relevant model for studying the dynamics of selection of antibiotic resistance in bacterial biofilms and we anticipate that the Brimor chip will facilitate basic research in this area.",
"introduction": "1 Introduction Biofilms are communities of bacteria that are attached either to a surface or to each other and embedded within a self-produced matrix of extracellular polymeric substances (EPS) ( Flemming et al., 2016 ; Flemming and Wuertz, 2019 ). Biofilms are less susceptible to antibiotics and biocides representing a serious challenge for effective treatment of a wide range of infections, and in particular for biofilm-colonized medical devices. Evolution of resistance to antibiotics is dependent on the interplay between genetic and phenotypic resistance mechanisms. Evolution at high antibiotic levels (above the minimal inhibitory concentration, MIC) has been extensively studied and it is only recently that low, non-lethal levels of antibiotics (sub-MIC levels) have been thoroughly examined ( Gullberg et al., 2011 ; Liu et al., 2011a ; Gullberg et al., 2014 ; Lundström et al., 2016 ; Khan et al., 2017 ; Wistrand-Yuen et al., 2018 ). Importantly, antibiotic levels far below the MIC can impose a selective pressure for the development of resistance, thereby contributing to the evolution of antibiotic resistance ( Oz et al., 2014 ). Of relevance in this context is the minimal selective concentration (MSC), which is defined as the lowest concentration of antibiotic at which a resistant bacterium will outcompete its susceptible counterpart and become enriched within a population ( Gullberg et al., 2011 ; Andersson and Hughes, 2014 ). Apart from bona fide antibiotic resistance mechanisms, bacterial biofilms can also show antibiotic tolerance by phenotypic mechanisms such as reduced ability of antibiotics to penetrate biofilms and the presence of dormant cells in the inner regions of the biofilms as well as cooperative behaviors between members of the biofilm population, adding another layer of complexity ( Flemming and Wingender, 2010 ; Nadell et al., 2016 ; Ciofu et al., 2017 ; Koo et al., 2017 ; Arciola et al., 2018 ; Crabbé et al., 2019 ). The properties of bacterial biofilms can generally not be extrapolated from our understanding of planktonic lifestyle ( Flemming et al., 2016 ). Thus, several methods for biofilm studies have been developed, such as the MBEC™ assay (based on the Calgary biofilm device), the rotating disk reactor, the CDC biofilm reactor, and the colony biofilm model and more advanced technologies utilizing high-resolution microscopy, hydrogels and microfluidics. These methods can largely be grouped into three: open-, closed-, or mixed-systems. Closed-systems are commonly used owing their simplicity and ease of use. Single- or mixed-species bacteria are incubated together in microtiter well plates and biofilm formation occur for a certain time under static conditions ( Zaborskytė et al., 2022 ). The system does not have constant supply of fresh nutrients essential for bacterial growth, leading to consumption of nutrients and accumulation of bacterial metabolic waste products. Furthermore, microenvironmental changes in the culture conditions may result in stochastic variations in these systems prompting the recent requirement for a minimum information guideline when using closed-systems ( Kragh et al., 2019 ; Allkja et al., 2020 ). Open-systems address this limitation with continuous supply of fresh nutrients to support continuous growth of biofilms. Typically a flow of culture medium, with or without bacteria, is generated using a peristaltic or syringe pump to for example simulate the conditions during urinary tract infections ( Hong et al., 2012 ; Hol and Dekker, 2014 ; Azeredo et al., 2017 ; Yan et al., 2017 ; Pousti et al., 2019 ; Heyman et al., 2020 ). Mixed-systems combine the ease-of-use of close-systems and address the limitation of nutrient supply by a nutrient replenishment and waste discarding step at specific intervals during biofilm cultivation and propagation ( Poltak and Cooper, 2011 ; Zaborskytė et al., 2022 ). Microfluidic approaches coupled with advanced live imaging provides a platform where it is possible to study biofilms in situ under different hydrodynamic conditions ( Kheyraddini Mousavi et al., 2012 ; Yawata et al., 2016 ; Azeredo et al., 2017 ) and at high-resolution ( Baltekin et al., 2017 ; Wistrand-Yuen et al., 2020 ). Previously developed microfluidic chips for biofilm studies feature straight flow channels ( Benoit et al., 2010 ; Rusconi et al., 2014 ; Liu et al., 2015 ; Siryaporn et al., 2015 ; Massalha et al., 2017 ; Zarabadi et al., 2017 ; Chu et al., 2018 ; Martinez-Corral et al., 2018 ; Wucher et al., 2019 ) or complex geometries to generate intricate flow paths ( Liu et al., 2011b ; Rusconi et al., 2011 ; Coyte et al., 2017 ; Dehkharghani et al., 2019 ). These flow systems suffer from randomness with respect to the location for biofilm formation in the devices, and difficulty in harvesting biofilms with precision. Specifically, there are several microfluidic chips developed for antibiotic resistance studies ( Kim et al., 2010 ; Straub et al., 2020 ; Zoheir et al., 2021 ). However, the current devices are either sensitive towards formation of air bubbles which disrupt the cultivation of biofilms on chip or could be sensitive towards changes in the antibiotic concentration gradient generated as a result of biofilm cultivation. The former is a common burden in most microfluidic applications, as they can severely alter the flow characteristics of fresh nutrient and removal of wastes from the biofilm. The likelihood of this phenomenon increases with prolonged incubation and operation time. Therefore, you can expect a microenvironmental change due to the alternating presence and absence of the air bubbles. The latter has not been explored with the devices proposed. In principle, these chips could be applied for studies of antibiotic resistance selection, however, this is on the basis that (i) the images could be captured over time without influencing the concentration gradient generated in the chip, (ii) the seeded cells are allowed to grow over the entire surface of the chip without any issues of clogging and (iii) biofilm cultivation should not influence the sensitive gradient-generation flow system. Recently, laser capture microdissection was used to extract a small subset of cells at different regions within a cryo-embedded biofilm ( Pérez-Osorio and Franklin, 2008 ), but this particular method kills the cells preventing the generation of new daughter biofilms, which is often needed to address evolutionary questions ( Martin et al., 2016 ; Santos-Lopez et al., 2019 ; Thibault Stalder et al., 2020 ). Here, we describe the development of a new in vitro microfluidic chip called Brimor (the letter B stands for biofilms and rimor is the Latin word meaning to probe, search or explore) which allow for specific and reproducible isolation of distinct biofilm sections whilst maintaining the spatial structure of the biofilm. Single-use, disposable Brimor microfluidic chips were easily fabricated at low-cost using 3D-printed molds (encoding fluidic channels), polydimethylsiloxane (PDMS) casting, and bonding of the resultant PDMS replica piece to a glass slide. Together with the basic components of a microfluidic system, the entire system enabled controlled cultivation of bacterial biofilms. We utilized Escherichia coli for biofilm formation with in situ staining to confirm the presence of extracellular cellulose in the biofilms. By live imaging and alterations in flow-rate, we showed that seeded planktonic cells shift towards a biofilm state in the microfluidic chip. We further demonstrated the novel capability of the system for controlled harvesting of defined layers of the cultivated biofilms. Finally, the new biofilm model was used to measure growth and death rates of E. coli during biofilm formation and to determine the minimal selection concentration in biofilms (MSCB) when E. coli biofilms were exposed to ciprofloxacin. The results showed that exposure to very low non-inhibitory ciprofloxacin concentrations can enrich for resistant mutants in bacterial biofilms.",
"discussion": "4 Discussion and Conclusions The current study describes the design, fabrication, and utility of a new microfluidic chip for detailed in vitro studies of biofilms using time-lapse imaging. We demonstrated the transition of planktonic cells to biofilms, the possibility of controlled partitioning of biofilms, and how the microfluidic chip allows determination of the minimal selective concentration as well as bacterial growth and death rates in biofilms. A novel potential of our system is the possibility to harvest cultivated biofilms for downstream analysis and re-cultivation in a new chip or other biofilm models. Our results suggest that depending on the particular strain, species and maturity of the biofilm studied, individual harvesting protocol would be required. By optimizing the change in flow rate and time exposed at the high flow rate in the microfluidic chip one could achieve even finer partitioning of biofilms in the growth chamber. The simplicity of microfluidic chip allows investigators the possibility, with high resolution, to determine the heterogeneous differences within a single biofilm without the loss of the spatial resolution. In addition, the cultivation time of biofilms in microfluidic models is often a major issue since contamination and over-growth occur ( Subramanian et al., 2020 ). To the best of our knowledge, the system described in this work is the only microfluidic model that allows a cultivation time as long as 144 hours (6 days) without the introduction of air bubbles to the system thereby disrupting the flow characteristics and biofilm formation and cultivation. As different organisms produce different amounts of EPS and because the amount of EPS increases with age of the biofilm, biofilm age is a major factor in influencing the outcome of an antibiotic therapeutic regimen ( Donlan, 2001 ; Donlan, 2002 ; Singla et al., 2013 ; Hall and Mah, 2017 ). Mechanical inputs, such as stress, elasticity or compression play a role in the transition from planktonic to biofilm lifestyles, and fluid shear force has been described to drive marine biofilm formation, affect biofilm spatial structure, and assist in regulating virulence during host attachment ( Stoodley et al., 2002 ; Alsharif et al., 2015 ; Rodesney et al., 2017 ; Thomen et al., 2017 ; Catão et al., 2019 ; Yang et al., 2019 ). As our chip is microfluidic-based, sheer force actively contributes to the environmental cue and initiates the switch from planktonic to biofilm lifestyle. Compared to straight-flow channel fluidic chips (the majority of dental biofilm systems) the angled channel design connected to a growth chamber of our biofilm chip is likely to enhance this switch in the active growing-front of the biofilm. The remaining part of the biofilm at the depth of the growth chamber had already experienced this force and does not experience constant sheer force. Indeed this phenomenon has been described previously ( Rusconi et al., 2010 ; Rusconi et al., 2011 ). Owing to the generation of an ECM that forms the physical foundation of the biofilm structure ( Flemming and Wingender, 2010 ), a localized micro-gradient of growth medium could be generated even with continuous fresh medium supplied ( Flemming et al., 2016 ) within this system. Given the porosity of PDMS in the system set-up, as well as the differences in the ECM produced between different bacterial species and even within different strains ( López et al., 2010 ), extensive characterization would be required to capture the macro- and micro-gradient differences within the growth chamber, which is beyond the scope of this work. Bacteria can become resistant to antibacterial compounds by lateral acquisition of resistance genes or by mutations ( Blair et al., 2014 ). How mutational resistance emerges, spreads and is maintained within a population of bacteria is determined by the interplay of several basic factors, including the biological fitness cost of the resistance gene and the strength of the selective pressure ( Hughes and Andersson, 2017 ). The number of generations and death rate estimations are essential to determine when (i) quantifying the minimal selective concentration, (ii) measuring mutation rates ( Frenoy and Bonhoeffer, 2018 ) and (iii) predicting the evolutionary trajectories of antibiotic resistance ( Gullberg et al., 2011 ). Our experiments demonstrate the possibility to investigate these important parameters in the biofilm chip. Previous work show that the first mutational event during the evolution of ciprofloxacin resistance in E. coli is a mutation in the gyrA gene ( Huseby et al., 2017 ) and that the MSC for planktonically growing bacteria with the same gyrA (S83L) resistance mutation used here is 0.0001 mg/L ( Gullberg et al., 2011 ). This is about 160-fold lower than the MSCB determined in this study The difference in the MSC (planktonic lifestyle) and MSCB (biofilm lifestyle) is not surprising considering that these two growth modes are very different with regard to gene expression, metabolism and physiology ( Azeredo et al., 2017 ). An important future question is to examine the potential generality of this observation, and whether minimal selective concentrations are generally higher in biofilms irrespective of antibiotic class and resistance mechanism. In principle, the microfluidic biofilm chip presented here is not restricted to only antibiotic compounds but can be used to investigate the effects of any bioactive compounds. Notwithstanding the limitations which accompany the use of a microfluidic approach for biofilm studies ( Yawata et al., 2016 ), bacteria are not the only lifeforms which transition into the biofilm lifestyle and any cell type could be placed in the micro-channels ( Flemming and Wuertz, 2019 ) and we anticipate applications in many areas of microbiology where biofilms are common ( Costerton, 1995 )."
} | 3,880 |
18699996 | PMC2572599 | pmc | 8,006 | {
"abstract": "Introduction The limited availability of fossil fuel sources, worldwide rising energy demands and anticipated climate changes attributed to an increase of greenhouse gasses are important driving forces for finding alternative energy sources. One approach to meeting the increasing energy demands and reduction of greenhouse gas emissions is by large-scale substitution of petrochemically derived transport fuels by the use of carbon dioxide-neutral biofuels, such as ethanol derived from lignocellulosic material. Results This paper describes an integrated pilot-scale process where lime-treated wheat straw with a high dry-matter content (around 35% by weight) is converted to ethanol via simultaneous saccharification and fermentation by commercial hydrolytic enzymes and bakers' yeast ( Saccharomyces cerevisiae ). After 53 hours of incubation, an ethanol concentration of 21.4 g/liter was detected, corresponding to a 48% glucan-to-ethanol conversion of the theoretical maximum. The xylan fraction remained mostly in the soluble oligomeric form (52%) in the fermentation broth, probably due to the inability of this yeast to convert pentoses. A preliminary assessment of the distilled ethanol quality showed that it meets transportation ethanol fuel specifications. The distillation residue, which contained non-hydrolysable and non-fermentable (in)organic compounds, was divided into a liquid and solid fraction. The liquid fraction served as substrate for the production of biogas (methane), whereas the solid fraction functioned as fuel for thermal conversion (combustion), yielding thermal energy, which can be used for heat and power generation. Conclusion Based on the achieved experimental values, 16.7 kg of pretreated wheat straw could be converted to 1.7 kg of ethanol, 1.1 kg of methane, 4.1 kg of carbon dioxide, around 3.4 kg of compost and 6.6 kg of lignin-rich residue. The higher heating value of the lignin-rich residue was 13.4 MJ thermal energy per kilogram (dry basis).",
"conclusion": "Conclusion This paper describes the successful up-scaling of the conversion of high dry-matter content LTWS via SSF into bioethanol on a pilot scale. In comparison to conversions obtained in laboratory experiments, we concluded that after 48 hours of incubation, slightly lower fermentable sugar and ethanol yields were achieved at the pilot scale. Tests showed that the produced ethanol was suitable as a transportation fuel. The side streams were quantitatively analyzed. The liquid fraction containing mainly soluble components was valorized by anaerobic fermentation to biogas (methane) and sludge. The remaining solid fraction was assessed as a fuel for conversion by combustion yielding thermal energy and inorganic ashes with the prospective of being utilized rather than being land-filled.",
"introduction": "Introduction The limited availability of oil reserves and growing worldwide energy demands have resulted in increasing energy prices. Furthermore, the utilization of fossil fuels has negative impacts such as air pollution and the generation of the greenhouse gas carbon dioxide (CO 2 ), which is presumed to be one of the main anthropogenic contributors to the global warming effect. These factors stimulate the exploitation of alternative renewable energy sources such as biomass [ 1 ]. According to the Kyoto protocols, many of the industrialized nations need to reduce their CO 2 emissions by around 5% by 2010 as compared with the 1990 level, while a further decrease will be compulsory in the long term [ 2 ]. One strategy to meet the global increasing energy demand and the reduction of CO 2 levels is the substitution of petrochemically derived transport fuels by CO 2 -neutral biofuels such as ethanol [ 3 ]. Bioethanol can be obtained by the microbial conversion of carbohydrates derived from biomass feedstocks such as agro-industrial residues [ 4 - 7 ]. Lignocellulose containing feedstocks are widely available, relatively inexpensive, non-competitive with food applications, sustainable in terms of CO 2 emissions and, therefore, of potential interest for the large-scale production of bioethanol. Lignocellulose consists of a complex fibrous structure of polymeric sugars such as (hemi-)cellulose embedded in a matrix of the aromatic polymer lignin [ 4 , 8 ]. Wheat straw has been studied often as a raw material for microbial ethanol production processes [ 9 - 11 ]. The conventional lignocellulose-to-ethanol conversion consists of: (1) a pretreatment step; (2) a hydrolysis step; and (3) a fermentation step. Various physical and chemical pretreatments have been developed to alter the structure of lignocellulosic substrates [ 8 ]. An example is lime (Ca(OH) 2 ) at mild temperatures (lower than 100°C), which enhances the accessibility of (hemi-)cellulose for the subsequent enzymatic hydrolysis [ 12 - 14 ]. We selected lime pretreatment as a model for further study as this has gained industrial interest because of its perceived advantages over other pretreatment methods, including the use of a low-cost chemical (lime) that is already in use in many agriculture-based, crop processing schemes (for example, sugar refining), lower reactor investment costs, as well as limited potential for the formation of degradation products. The hydrolysis, which is often performed by a mixture of cellulolytic and hemi-cellulolytic activities, results in a hydrolysate containing mainly soluble monosaccharides. Throughout the subsequent fermentation, these monomeric sugars can be converted into ethanol by yeasts or bacteria with a high productivity and efficiency. Alternatively, enzymatic saccharification and fermentation are performed simultaneously at compromising reaction conditions in one reactor. So far only a limited number of reports have been presented on the effects of lime pretreatment on the simultaneous saccharification and fermentation (SSF) of lignocellulosic biomass, including ethanol yield and the quality and valorization of side streams. Chang et al [ 15 ] submitted lime-pretreated switchgrass, corn stover and willow wood to laboratory-scale SSF and concluded that cellulose-derived glucose was extensively used by yeast to form ethanol during SSF, and that the pretreatment did not result in a significant inhibition of fermentation. In a more recent study, we investigated the use of lime-pretreated wheat straw for simultaneous hydrolysis and fermentation to lactic acid by an enzyme preparation and Bacillus coagulans DSM 2314 [ 16 ]. In a related study on the conversion of washed lime-treated wheat straw (LTWS) into ethanol, the optimal reaction conditions were determined on a laboratory scale [ 14 ]. The objective of the present paper is to study the effect of up-scaling on the performance of the lignocellulose-to-ethanol SSF process, quality assessment of the bioethanol and valorization of the by-product streams. In the present study, ethanol was recovered from the fermentation broth via a distillation process and its composition was analyzed to assess its suitability as a transport fuel. The remaining distillation residue, consisting of water, lignin, non-hydrolyzed and non-fermented organic components, minerals from the feedstock, the added process chemicals and other non-ethanol fermentation products, was separated into a solid and liquid fraction. The combustion behavior of the solid fraction, which represents a significant part of the energy input, was studied and tested using a bench-scale experimental fluidized bed combustor (FBC) to assess the suitability of the solid fraction as fuel for combined heat and power generation. The liquid fraction, containing soluble organic components, was tested for its suitability for anaerobic biodegradation yielding biogas (methane). Utilization options for the ashes derived from combustion and sludge derived from anaerobic digestion are briefly discussed. This paper represents, to the best of the authors' knowledge, the first integral assessment of the conversion of lignocellulosic material into bioethanol including the valorization of side streams.",
"discussion": "Discussion Lignocellulosic biomass has great potential with regard to its use as a substrate for the large-scale production of biofuels. The lignocellulose-to-ethanol conversion via SSF is a complex process involving various enzymatic and microbial activities. Results from previous studies showed that the mild-temperature lime treatment (0.1 g Ca(OH) 2 per gram substrate, 16 to 20 hours, at 85°C) enhances the accessibility of polymeric carbohydrates towards hydrolytic enzymes resulting in the release of fermentable sugars and improved ethanol yield [ 14 ]. Nevertheless, these studies were performed at the laboratory and bench scale. This paper describes the pretreatment, enzymatic hydrolysis and microbial conversion of LTWS via SSF into ethanol on a pilot scale. Prior to using the lime-treated substrate for hydrolysis and fermentation, the inhibitor acetic acid was successfully removed by a relatively simple washing procedure. Reaction conditions and enzyme loadings determined in previous optimization studies were used for hydrolysis and fermentation. This resulted in a glucan-to-ethanol conversion (48%), which is lower than the yields obtained in laboratory tests (56%) [ 14 ]. An explanation for this difference in ethanol yield can be found in the higher dry-matter content, which was approximately twice as high in the pilot-scale ethanol fermentation (around 20% by weight), negatively influencing the enzymatic hydrolysis. A possible explanation for the low glucan-to-ethanol yield can be found in the fact that xylose is present in the medium and may inhibit the activity of the cellulolytic complex [ 20 ]. Another possible explanation for the lower yield is that in this study the lime pretreatment was carried out on a pilot scale and without continuous temperature control, thereby leading to lower cellulose digestibility compared with a bench-scale test. Approximately 25% of the glucan in the LTWS remained present as an insoluble polymeric sugar suggesting the presence of crystalline and hardly degradable cellulose and/or inactivation of the hydrolytic system. Our findings support the results of Chang et al [ 15 ] who reported that enzymatically hydrolyzed cellulose from lime-pretreated biomass was utilized extensively by yeast, suggesting that the fermentations were not limited by the glucose metabolism of the yeast. The situation is different in the case of xylan. Owing to the inability of the wild-type baker's yeast to convert pentose sugars, end-product inhibition by xylose possibly occurs resulting in the accumulation of mainly xylo-oligomeric sugars. Previous SSF work with LTWS, hydrolytic enzymes and Bacillus coagulans , a pentose-converting, lactic-acid-producing bacterium, showed that the concentration of xylo-oligomeric sugars and xylose remain low [ 16 ]. This indicates that the presence of xylose monomers in the medium of the pilot-scale ethanol process possibly inhibit the hydrolysis of soluble xylo-oligomeric sugars. In addition, the xylan-to-xylose conversion at pilot-scale SSF (24%) agrees relatively well with the yield obtained in laboratory-scale SSF experiments (28%). Further optimization of the enzymatic hydrolysis and fermentation step can be realized by the use of pentose-converting yeast resulting in a higher ethanol concentration and yield. If a xylose-converting yeast is used, an additional amount of ethanol approximately 1.4 kg (assuming the conversion of 74% of xylan, which is the fraction that was present as a monomer and oligomer after 53 hours of incubation, with an ethanol yield of 0.51 g/g) can be formed from this C 5 sugar. Less dissolved substrate will be available for anaerobic digestion resulting in an approximately 55% reduction of methane to around 0.5 kg. Ethanol was upgraded via two separate distillation processes resulting in a distillate containing 90% ethanol by weight. Tests showed that the ethanol distillate, in comparison with the ethanol fuel specifications of the Detroit Diesel Corporation, seems suitable as a transportation fuel. The fermentation residue was separated into two fractions; one fraction contained mainly solids functioning as a fuel for thermal conversion and the other was a liquid fraction that contained mainly soluble compounds serving as a substrate for anaerobic fermentation to biogas. The liquid fraction had a moderate anaerobic biodegradability of 60% respective to the total COD content and no signs of toxicity could be observed in the accumulation test. The relatively low value is largely a result of the high amount of solid organic matter in the liquid fraction, which was only partly degraded. More efficient removal of the solid matter would contribute to a significant reduction of the COD load. As the dissolved matter has a high anaerobic biodegradability, anaerobic treatment would then be an attractive way of processing this effluent for COD reduction and energy production in the form of methane gas. The solid fraction of the distillation residue appeared to be suitable as a fuel for thermal conversion, although it contained a relatively high ash concentration and relatively high concentrations of sulfur and calcium due to additions in the upstream processes. It is expected that the combustion will show a behavior between the original feedstock wheat straw and (clean) wood. Based on the analyzed residue composition, there is some risk of smelt-induced bed agglomeration. The risk of sinter-induced bed agglomeration is expected to be less than for straw, as a result of the partial removal of potassium (washing) in the upstream processes. The combustion experiments showed no agglomeration and no extensive coating was detected on the bed material that would indicate agglomeration. Long-duration experiments on a larger scale are necessary, however, to provide a more profound assessment of the fuel behavior. With respect to fouling, high ash deposition rates were observed. The composition of both bottom ashes and fly ashes were determined and it is most likely that both could be utilized rather than being land-filled. The main options are utilization as building materials and, in some cases, as fertilizers. A more conclusive assessment of the potential utilization of the ashes requires larger samples that are more representative of the full scale, because the ashes from the pilot-scale test likely have a lower salt content. Details on the assessment of ashes will be presented in a follow-up paper."
} | 3,637 |
30858553 | PMC6411895 | pmc | 8,007 | {
"abstract": "Differentiating biotic and abiotic processes in nature remains a persistent challenge, specifically in evaluating microbial contributions to geochemical processes through time. Building on previous work reporting that biologically-influenced systems exhibit stronger long-range correlation than abiotic systems, this study evaluated the relationship between long-range correlation of redox potential and oxidation rates of circumneutral microaerophilic bacterial Fe(II) oxidation using a series of batch microcosms with bacteriogenic iron oxides (BIOS). Initial detrended fluctuation analysis (DFA) scaling exponents of the abiotic microcosms were lower (ca. 1.20) than those of the biotic microcosms (ca. 1.80). As Fe(II) oxidation proceeded, correlation strength decayed as a logistic function of elapsed reaction time, exhibiting direct dependence on the free energy of reaction. Correlation strength for all microcosms decayed sharply from strong correlation to uncorrelated fluctuations. The decay rates are greater for abiotic microcosms than biotic microcosms. The Δ G m relaxation edges for biotic microcosms were lower, indicating less remaining free energy for Fe(II) oxidation than abiotic systems, with the implication that biologically-catalyzed reactions are likely more energetically efficient than abiotic reactions. These results strengthen the case for employing novel DFA techniques to distinguish in situ microbial metabolic activity from abiotic processes, as well as to potentially differentiate metabolisms among different chemoautotrophs.",
"introduction": "Introduction Deciphering the complex interplay between microbially mediated and abiotic reactions in the biogeochemical cycling of redox active chemical species is crucial to understanding the planetary impact of microbial life 1 – 3 . Among the multitude of redox reactions catalyzed by microorganisms, bacterial oxidation of Fe(II) is of considerable interest as Fe(II)/Fe(III) redox transformations are strongly coupled to the cycling of C, N, O, and S, as well as the environmental fate of trace elements, nutrients, and contaminants 4 – 6 . There is also a growing body of evidence implicating Fe(II) oxidizing bacteria (FeOB) as both causative agents in the formation of ancient banded iron formations on Earth and plausible ecophysiological analogues for life on other planets 7 – 10 . At the same time, the potential significance of these findings is tempered by a cautious appreciation of the fact that Fe(II) oxidation pathways in nature are exceptionally diverse and multifaceted, as concurrent abiotic and microbially-mediated reactions are apt to proceed in tandem with microaerobic, photochemical, and nitrate-dependent oxidation processes 11 , 12 . This reactivity extends additionally to nanoscale heterogenous oxidation processes occurring on bacterial cell and mineral surfaces 13 , further complicating these systems. Overall, distinguishing between biotic and abiotic processes in situ remains a persistent challenge in evaluating microbial contributions to biogeochemical processes 10 . The high standard potential of the O 2 /H 2 O half-cell ( Eh 0 = 1.23V, 25 °C) promotes high rates of spontaneous abiotic oxidation of Fe(II) at atmospheric p O 2 values and circumneutral pH range of most natural waters 12 , 14 . This constrains neutrophilic FeOB to low p O 2 microaerophilic environments where the metabolic oxidation of Fe(II) can outcompete the kinetics of homogenous and heterogenous abiotic reactions 15 , 16 . Subsequent chemical hydrolysis and precipitation of dissolved Fe(III) often gives rise to voluminous mats of flocculent rust-coloured bacteriogenic iron oxides (BIOS) consisting of nanoparticulate hydrous ferric oxides (HFO) intermixed with live and dead bacterial cells 17 – 19 . The mineral precipitates occur as poorly ordered ferrihydrite 20 , 21 . Over time, the accumulation of BIOS serves to increase the relative proportion of heterogeneous surface-mediated abiotic reactions contributing to the abiotic oxidation of Fe(II), thereby confounding the contributions of FeOB 11 . The kinetics of Fe(II) oxidation by neutrophilic bacteria have been examined in a number of studies 14 , 22 – 24 . Inhibition of FeOB using sodium azide as a poison or sterilization by autoclaving clearly demonstrate that rates of bacterial Fe(II) oxidation are faster than abiotic homogenous and heterogenous rates under similar geochemical and low p O 2 conditions. While informative, these results only hint at the underlying mechanisms and bioenergetic capacity of FeOB to catalyze otherwise spontaneous abiotic Fe(II) oxidation rates. More recently, the statistical dependence (i.e., long-range correlation, also known as memory or persistence) of temporal fluctuations in electrochemical measurements of redox potential on a time scale of minutes to seconds were found to distinguish bacterial and abiotic Fe(II) oxidation 7 , 25 . Long-range correlation in a time series implies that any measured value is statistically dependent on preceding values, and can take the form of positive correlation (a past increasing trend will continue to increase into the future) or negative correlation (an increasing trend is likely to be followed by a decreasing trend) 26 , 27 . Such correlative dependence has proven to be consistently more pronounced for bacterial Fe(II) oxidation than abiotic Fe(II) oxidation 25 ; thus, the parameter of correlation strength, measured by detrended fluctuation analysis (DFA) scaling exponents ( α ), can feasibly be used to distinguish microbially-catalyzed Fe(II) oxidation from homogenous and heterogeneous chemical oxidation. This new approach to investigating bacterial Fe(II) oxidation is compelling in light of the fact that the Gibbs free energy (Δ G r ) of an oxidation-reduction reaction is an explicit thermodynamic function of redox potential. The implication is that Δ G r reveals not only which reactions are favored thermodynamically and exist as realistic bioenergetic options, but also constrains essential geochemical conditions, including pH, ionic strength, and concentrations of electron donors and acceptors, that influence the amount of available metabolic energy. To investigate the relationship between (Δ G r ) and correlation strength, we conducted a series of batch microcosm experiments in which Fe(II) oxidation rates and relative concentrations of Fe(II)/Fe(III) changed systematically over time, and experimentally determined the strength of long-range temporal correlation in redox potential fluctuations at several stages of elapsed reaction time. Our results confirm that long-range correlation of redox potential fluctuations in biologically-influenced systems is stronger than long-range correlation in abiotic systems. Furthermore, we discovered that correlation strength dissipates as a logistic function of time and exhibits direct electrochemical dependence on free energies of reaction.",
"discussion": "Discussion The range of Fe(II) oxidation rate constant ( k ox ) estimates in this study (0.004 to 0.141 min −1 ) are in concordance with those determined from previous microcosm investigations, which span from 0.016 to 0.249 min −1 11 , 12 , 23 . Additionally, k ox estimates of 0.141 min −1 for the High BIOS microcosm are about three times that of the Low BIOS microcosm (0.039 min −1 ; Table 1 ), as expected from other studies documenting the dependence of Fe(II) oxidation rates on BIOS concentration 11 , 22 . In tandem, the oxidation rate constants for the two BIOS microcosms are anywhere from three to thirty-five times higher than the Control (0.004 min −1 ) and Autoclaved (0.012 min −1 ) microcosms. These differences re-emphasize the ability of FeOB to outcompete the kinetics of abiotic homogeneous oxidation of Fe(II) in solution, as well as heterogenous Fe(II) oxidation on HFO precipitates 14 , 23 . In keeping with previous work, the initial elevated DFA scaling exponents in the Low and High BIOS microcosms confirm that higher rates of bacterial catalyzed Fe(II) oxidation gives rise to stronger long-range correlations in redox potential fluctuations than slower abiotic reactions. As anticipated from these observations, the long-range correlations dissipated to a random uncorrelated state (i.e., α = 0.5) as rates of Fe(II) oxidation declined over time towards equilibrium in each of the closed batch microcosm. The logistic decay rate constants of scaling exponents for redox potential fluctuations were also more than twice as fast in the Control and Autoclaved microcosms than in their BIOS counterparts, demonstrating that long-range correlations in redox potential fluctuations tend to be more persistent for bacterial Fe(II) oxidation than abiotic reactions. This was particularly evident in the case of the Low BIOS microcosm, which exhibited the longest crossover threshold time of 8.28 min for the transition in from long-range correlation to random uncorrelated fluctuations in redox potential. On the other hand, the High BIOS microcosm displayed not only the shortest crossover threshold time, but also the highest rates of Fe(II) oxidation with consumption of Fe(II) and production of Fe(III) driving towards equilibrium faster than in the Low BIOS microcosm. These counterintuitive results are, in fact, consistent with the dependence of redox reactions on the mutual diffusion and collision frequency of reactants to form close-encounter complexes, with short separation distances more favorable to electron transfers 30 . If the redox reaction rate is high, as is expected under conditions far from equilibrium, then diffusion may become limiting. This situation is consistent with the initial stages of the microcosm experiments when fast Fe(II) oxidation rates yielded DFA scaling exponents symptomatic of long-range correlation in redox potential fluctuations (i.e., α > 0.5). Conversely, diffusion constraints are relieved by slower reaction rates, which diminished over time in the microcosms with a shift to random uncorrelated fluctuations in redox potential as Fe(II) concentrations decreased. Specifically, at the comparable crossover threshold times and sluggish rates of abiotic Fe(II) oxidation in the Control and Autoclaved microcosms, Fe(II) concentrations calculated from Eq. 1 were 0.98 and 0.95 times lower than initial values, respectively. For higher rates of bacterial Fe(II) oxidation in the Low and High BIOS microcosms, the same calculations show that initial Fe(II) concentrations decreased by equivalent factors of 0.72 and 0.69, respectively. These considerations not only add another level of distinction between bacterial and abiotic Fe(II) oxidation, but also offer reconciliation for the wide displacement in crossover threshold times witnessed in the Low and High BIOS microcosms 30 . Transformation of the DFA scaling exponent results from the time domain to Gibbs energies of reaction revealed a hypothesized, but heretofore undocumented, characteristic of bacterial Fe(II) oxidation. The existence of long-range correlations in redox potential fluctuations under conditions far from electrochemical equilibrium (i.e., \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$${\\rm{\\Delta }}{G}_{r}\\ll 0$$\\end{document} Δ G r ≪ 0 ) is evidently more pronounced for the involvement of bacteria than abiotic reactions. Additionally, strong long-range correlations in redox potential fluctuations arising from bacterial activity persist to much lower reaction free energy levels as equilibrium is approached (i.e., \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$${\\rm{\\Delta }}{G}_{r}\\to 0$$\\end{document} Δ G r → 0 ) than is witnessed in abiotic reactions. This is mostly likely explained by the well-documented efficiency of bioenergetic processes in which redox energy is conserved biochemically rather than being lost to the environment through thermal dissipation 31 . Altogether these findings constitute a significant breakthrough in deciphering the complex dynamics of microbial Fe(II) oxidizing systems in natural systems through the fluctuation analysis-based differentiation of biotic and abiotic reaction pathways. While Fe(II) oxidation is an important redox transformation that is tied closely to the biogeochemical cycling of many key elements including C, N, O, and S 10 , 32 – 34 , microbial bioenergetic processes are characterized by an immense degree of diversity of energy sources (i.e., electron donors) and terminal electron acceptors in natural systems 1 , 35 – 38 . In this regard, the potential for using DFA to detect long-range correlation strength of redox potential fluctuations associated with bacterial metabolisms other than chemoautotrophic Fe(II) oxidation remains virtually unexplored and ripe for investigation. Recent estimates of the number of undiscovered microbial species living in refugia and ephemerally on Earth underscore the importance of developing new research methods which are not reliant on physical access and sampling 38 . The in situ nature of the electrochemical DFA method makes it a potentially revolutionary tool in furthering our understanding of microbial contributions to important biogeochemical processes such as Fe(II) oxidation that mediate the flow of energy and matter across our planet’s complex interconnected systems 39 , 40 ."
} | 3,444 |
34917493 | PMC8666517 | pmc | 8,008 | {
"abstract": "Highlights • Electricity production by biocathode containing MFC in long-term operation. • Biocathodes shows overall advantages over abiotic cathodes. • Voltammetric analysis supports a more sustainable electron transfer using biocathodes. • PCR-RFLP analysis identified potential electricity producing organims.",
"conclusion": "4 Conclusions MFC in long-term operation with a aerobic biocathode showed better electrogenesis, power production and substrate degradation than the corresponding MFC with an abiotic cathode. RFLP analysis identified the potential electricity producing organisms such as Acinetobacter, Acidovorax, Pseudomonas, Geobacter, Cupriavidus and Burkholderia . Main advantages of the RFLP method include cost diminishing by reducing the sequencing reactions, and also the easier manipulation allowing lesser skilled personnel to do it. Our findings clearly demonstrated that MFC which contains biocathode has wider potential applications than other more convencional MFCs using abiotic cathodes, in particular due to simpler conditions and the reduction of costs. But, for future routine applications, the biocathode containing MFC need to overcome some limitations, which are mainly caused due to contaminations and biofouling.",
"introduction": "1 Introduction Bioelectrochemical system (BES) is an electrochemical system in which biocatalysts perform oxidation and/or reduction of substrates at electrodes [1] , [2] , [3] . Electrons produced by microorganisms through the substrate degradation are moved to the anode and then to the cathode [ 4 , 5 ]. Microbial fuel cell (MFC) are one of the prominent types of BESs, where microorganisms oxidize organic and inorganic materials to produce energy. The anode of MFC works as electron acceptor and moves the electrons to the cathode through a resistor and produce electricity [6] , [7] , [8] . Abiotic cathode microbial fuel cell (in this work named MFC-1) system has been half biological, because only the anode side consists of electrochemically-active microorganisms. The biocathode system in microbial fuel cell (here named MFC-2) contains microorganisms functioning as biocatalysts in the anode, motivating the degradation of organic substances to produce electrons, which travel to the cathode (also contaianing microorganisms) side through an electric circuit. The presence of free electrons on the cathode of MFC initiates a reduction response of oxygen to produce water. In this case, microorganisms, namely bacteria, will take electrons at the cathode by the reduction of electron acceptors such as nitrate, sulfate, perchlorates and metals [9] , [10] , [11] , [12] . Biodegradable organic matter is, thus, converted into electricity, hydrogen or other value added materials through MFCs [13] , [14] , [15] . In several studies, researchers used human waste [16] , agricultural waste [17] and food waste [18] in MFCs to produce energy or chemicals. Lately, biocathodes in microbial cells gained focus for the removal of different pollutants due to their low cost, use of self-regenerate catalysts, and maintainable power supply [ 19 , 20 ] and developments were made by using diverse microorganisms as biocatalysts also on biocathodes [19] , [20] , [21] , [22] . Studies have reported that MFCs performance can be enhanced by the action of microorganisms present at the cathode [ 21 , 22 , [25] , [26] , [27] ]. Biocathodes which contains biofilms are not only able to catalyze the oxygen reduction at the cathode, but also show comparable or higher performances than abiotic cathode, such as the case of some metal reducing bacteria when in the cathodic chamber [ 28 , 29 ]. Eventhough biocathodes have great potential in MFCs technology, issues such as performance of biocatalysts at terminal acceptor conditions, cathodic activation overpotentials [ 30 , 31 ], biofouling, accumulation and competition of metabolites [ 32 , 33 ] need to be solve aiming its future widely application. For that goal, long-term operation and the scaling-up of biocathodes need to be further discussed to make the biocathode MFCs technology more practicable. In order to understand the structure and function of the ecosystem in an MFCs, the microorganisms should be identified (and quantified). Advanced molecular methods provided new insights, so isolation and cultivation of microorganisms are no longer required to get information about microbial communities [34] . 16S rRNA based sequencing is the most popular method used for the identification of microbial communities present in soil, sea, river, lake and wastewaters [35] . Currently, researchers are using the on-line tools available through the “Entrez Programming Utilities (E-utilities)” https://eutils.ncbi.nlm.nih.gov/entrez/eutils/ ) to compare the sequence from various microorganisms throughout the world. However, only a limited number of researchers worked on the electricity generation using long-term operated biotic MFC together with analysis of microbial diversity using polymerase chain reaction (PCR) based restriction fragment length polymorphism (RFLP) technique. Hence, the objectives of this study is the evaluation of the long-term operation of MFC-2 (containing an aerobic biocathode), regarding its overall performance, including power generation and treatment efficiencies which were analyzed and compared with the conventional MFC-1 (which contains an abiotic cathode). The MFCs performance was evaluated based on the parameters like power density (PD), columbic efficiency (CE), open circuit voltage (OCV), and current density (CD); the substrate degradation was evaluated through chemical oxygen demand (COD) and the organic compounds removal efficiency. The microbial populations present in the long-term operation MFCs reactors were evaluated using PCR based RFLP technique.",
"discussion": "3 Results and discussion 3.1 Power generation Both anodic chambers in MFC-1 and MFC-2, and the cathodic chamber in MFC-2 were inoculated with 90 mL of aerobic activated sludge, and fed with 270 mL of the simulated wastewater. After the bacteria enrichment, a slow increment of the cell voltages were observed, with a stabilization at the 5th day (after 2 fed-batch cycles) and the 16th day (after 5 fed-batch cycles) for MFC-1 and MFC-2 respectively ( Fig. 2 ). The difference in time for achieving cell voltage stabilization was already reported by other authors and interpreted as the biocathode conditions implies more time for the bacterial growth and consequent stabilization [ 21 , 22 , 44 ]. Under stabilized conditions, MFC-2 (biocathode) exhibited an open circuit voltage (OCV) of 439 mV, with an external resistor of 1000 Ω, power density (PD) of 54 mW/m 2 and current density of 122 mA/m 2 . The values are comparable with those observed for MFC-1 (abiotic cathode) ( Table 1 ). The voltage dropped after 150 and 165 days for MFC-2 and MFC-1, respectively ( Fig. 2 ). In the first stage, the voltage dropped to 233 mV with PD of 15 mW/m 2 and current density of 65 mA/m 2 for MFC-2; for MFC-1 the voltage dropped to 330 mV with PD of 30 mW/m 2 and current density of 92 mA/m 2 ( Table 1 ). In the second stage, after 200 days, the values continued decreasing for both MFCs ( Fig. 2 ). This decrease might be due to the reduction of the sinergetic metabolic activity of the microorganisms in the anodic chambers, together with the biofouling of the nafion membrane, subsequently contributing to a diminuished electron transfer efficiency for longer periods of time [ 45 , 46 ]. From the obtained results it is possible to conclude that both the MFCs showed comparable results for the parameters under analysis. Fig 2 Cell voltage with time for the long-term operation of abiotic cathode (MFC-1) and biocathode (MFC-2). Fig 2 Table 1 Consolidated data obtained during operation of both MFC-1 and MFC-2. Table 1 Characterstics Biocathode (MFC-2) Abiotic (MFC-1) BVD AVD BVD AVD Batch mode operation time (days) 150 - 165 - 1 OCV (mV) 439 233 435 330 Power density (mW/m 2 ) 54 15 51 30 2 COD removal efficiency (%) 94 66 90 69 Coulombic efficiency (%) 33 15 31 15 Current density (mA/m 2 ) 122 65 121 92 1 OCV: open circuit voltage;. 2 COD: chemical oxygen demand; BVD: Before voltage drop; AVD: After voltage drop. 3.2 Polarization curves in MFCs Polarization curves (PC) provide information regarding the different type of voltage losses (activation, mass transfer and ohmic drops) in MFCs due to different aspects such as kinetics of the electrochemical reactions and the internal electrical and ionic resistances. Polarization studies were conducted at different external resistances from 15 to 10,000 Ω for both MFCs; the measurements were performed taking the slope of the plot of voltage versus resistance ( Fig. 3 a ).The measured OCV for both MFCs is the maximum voltage that can be obtained within the system. PC and power curves for MFC-1 and MFC-2 were determined. The OCV for MFC-1 was 516 mV (no current, infinite resistance) and the voltage falls to 449 mV at a current density of 194 mA/m 2 , and linearly with the current after that point. The highest power density obtained was 52 mW/m 2 . For MFC-2 the OCV was 521 mV (same conditions) and the voltage falls to 456 mV at current density of 214 mA/m 2 and also linearly with the current after that. In MFC-2, the highest power density obtained was 54 mW/m 2 ( Fig. 3 b ). The PC curves for the two MFCs revealed likely patterns, in which the cell voltage dropped rapidly at low currents and was followed by a slow and near-linear drop in the remaining region. This behavior, may be attributed to the activation and ohmic losses in both MFCs. The voltage behavior in the PC supports the premise of losses during electron transfer in fuel cells [ 44 , 45 , 47 ]. Surface reactions, either oxidizing or reducing compounds, require some activation energy and are associated to those losses [ 44 , 47 ]. Aerobic metabolism at the cathode contributes to lower the activation losses by enhancing the final reduction reaction. Also, ohmic drops are triggered by electrical resistance of electrodes, electrolyte and membranes [ 44 , 47 ]. Mass transfer losses occurs when the substrate is oxidized faster at the anode, producing more electrons than those that can be transported to the cathode. From the results, it can be infered that the biocathode in MFC facilitates the reduction resulting in faster electron capture at the anode. Fig 3 (A) Cell voltage as a function of resistance, and (B) Polarization curve plotted with the voltage and power density against current density. Fig 3 3.3 Wastewater treatment efficiency The performance of both MFCs were also evaluated for the wastewater (substrate) treatment efficiency through the reduction of chemical oxygen demand (COD%) at different time periods. COD removal efficiency were observed in both MFC operations, in the first 3 and 4 fed-batch cycles for MFC-1 and MFC-2, respectively. Both MFCs stabilized in the next 18 fed-batch cycles in which the higher COD removal efficiencies varied between 81% to 90% ( Fig. 4 ). MFC-2 (biocathode) has shown slightly higher COD removal efficiency (94%) with the coulombic efficiency (CE) of 33%, than MFC-1 that showed 90% of COD removal efficiency and 31% of CE ( Table 1 ). The availability of oxygen and convenient redox partners and respective compatible potential values at adjacent neutral conditions in the MFC-2 chamber supports the fast metabolic activities of the bacteria leading to the slightly higher values of COD removal efficiency. Consumption of protons and electrons in the aerobic metabolic process seem to be responsible for the maximum COD removal efficiencies obtained for longer period operations in MFCs [ 5 , 21 , 23 , 24 , 45 ]. Over the tested period when the voltage drops in MFCs, COD and CE removal efficiencies also decrease in both MFCs ( Fig. 4 ). Fig 4 Differences in COD removal (%) and CE efficiency (%) for (A) MFC-1; and (B) MFC-2, at various operating cycles. Fig 4 During the operation, the pH values were measured at the starting and final time of each fed-batch cycle ( Fig. 5 ). The pH was found to be stabilized at neutral condition (7.0) in the anode and cathodic chambers for almost all cycles. In few cycles, the pH at anode chambers was found to have a slight variation between 6.9–7.3. The pH has stabilized in the range of 6.5–7.3 in cathodic chambers. The pH stabilization is due to the bicarbonate buffering mechanism, inspite of the continuous reduction reactions occurring in the cathodic chambers. The in-situ buffering mechanism in the cathodic chamber that prevents the pH drop is vital for the ongoing reduction reactions and for the power generation and the maximum substrate degradation [45] . Fig 5 Variations in pH profiles in each fed-batch cycle for (A) anodic and (B) cathodic chambers of MFCs. Fig 5 3.4.Electrochemical behavior of biotic and abiotic MFC cathodes Cyclic voltammetry (CV) is a helpful tool to elucidate the electrochemical reactions occurring at the electrodes surface. The electrochemical behavior of the MFC chambers was evaluated by CV during operation and current generation, in-situ using the anode or the cathode in each chamber as working electrodes. Cyclic voltammograms obtained using the MFC anodes (anaerobic conditions) as working electrodes demonstrated distinctions between the MFC-1 and MFC-2, although the initial media and electrodes are the same in both anodic chambers ( Fig. 6 ). Around 0 V vs Ag/AgCl a well defined redox process in MFC-2 is visible, where in MFC-1 is almost unnoticeable, and probably results from small contamination from the cathodic chamber (probably though the membrane). As expected, the electrochemical behavior of the MFC-1 and MFC-2 cathodes operating in aerobic conditions are clearly distinct ( Fig. 6 ). Once more, a well-defined redox process, close to 0 V vs Ag/AgCl, is observed in the MFC-2 that also shows lower capacity current. An anodic process around +0.2 V and a counterpart cathodic process at −0.5 V vs Ag/AgCl are observed for both MFC-1 and MFC-2. These processes were already detected in the anodic chambers and were associated to oxygen reactions. MFC-2 (biocathode) presents an enhanced anodic current starting at +0.7 V vs Ag/AgCl, not found at MFC-1 that seems similar to the behavior observed for the anodic chambers and was assigned to microorganisms metabolism. In general, the electroactivity observed in the biotic aerobic chamber is higher than in the abiotic one. The observed redox processes are consistent with the presence of extracellular active redox components, resultant from the microorganisms metabolism [ 48 , 37 ], and a more extended analysis of these components is currently in progress. The electrochemical behavior observed in biocathodes indicates that the microorganisms population in the chamber influences the exchange current density enhancing the electron transfer from and towards the electrode, in agreement with other reports [49] , [50] , [51] . Additionally, in the biocathode the oxygen reduction wave is found around −0.5 V vs Ag/AgCl, being less pronounced and starting at more negative potential values. This may be due to a slowed down diffusion towards the electrode surface due to biofilms’ presence. Yet, in spite of less extent oxygen reduction in the electrode surface, the operation of the MFC-2, as discussed before, is comparable to MFC-1, which points to the active role of microorganisms as electron acceptors, also in agreement with other reports [ 33 , 37 ]. Fig 6 Typical cyclic voltammograms from anodes and cathodes of the two type of MFCs. Fig 6 3.5 Microbial diversity analysis One of the goals of this work is to identify the microbial communities present in the MFC's abiotic and biotic cathode. In conventional methodology, several biological methodologies, such as DNA isolation, PCR amplification, cloning, and sequencing are performed. All these methods are time consuming, so, in here it was decided to perform the cloning and restriction fragment length polymorphism (RFLP) analysis of clones before analyzing their nucleotide sequences, foreseeing the minimization of the time and methodologies. This strategy was already used by Ramos et al., 2010 [35] , as stated before, and is based on the combination of DNA isolation, PCR amplification, cloning, and sequencing of plasmids initially characterized by RFLP using the recurrently cutting restriction enzyme Hae III. Using this methodology, 281 clones were identified, and among these, 104 discrete profiles were observed. 3.5.1 Optimization of PCR conditions After DNA isolation, optimization studies were done for the PCR amplification, to amplify the DNA isolated from the organisms present in MFC-1 and MFC-2 cathodes biofilms used in the long-term operation. Optimization was done by varying the temperatures from 50°C to 72°C by using three pairs of primers as mentioned in Table S1 . Among various annealing temperatures, best amplification was observed at the temperature of 58°C with bacteria and archaea. Amplified PCR products were loaded on agarose gels. To amplify the bacterial domain, two sets of primers were used, both the primers showed good amplification results, but the one set of primers showed more intense bands than other. So, further amplifications were carried out using those primers. The expected size of the amplified products was 605 bp. Moreover, the best temperature to use in the amplification is 58°C for both the domains (bacteria - A) and (archaea- B). 3.5.2 RFLP and sequencing analysis After optimization of experimental conditions, PCR amplification was carried out and expected gene sizes for bacteria and archaea were obtained and confirmed through agarose gel electrophoresis. But, expected PCR amplification results were not obtained with the biofilm collected from the cathode of MFC-1 and MFC-2. The amplified products obtained were purified using a commercial kit and then cloned into the pCR2.1 cloning vector. The resulting ligation mixture was transformed in E.coli DH5α competent cells, and the transformants were spread onto the surface of LB solid medium supplemented with appropriate antibiotics. Therefore, plasmid DNA from the selected clones was purified using the Miniprep plasmid protocol. The presence of plasmid DNA was confirmed trough electrophoresis gel and DNA concentration was estimated using a NanoDrop ND 1000 spectrophotometer ( S Fig. 2 a ). Restriction digestion was carried out with the enzyme Hae III. A total of 281 recombination plasmids were obtained, out of the plasmids showed distinct profile were sequenced ( S Fig. 2 b ). Database searches for homologous sequences were performed using the 16S rRNA encoding genes, 104 matched sequences showed maximum identity of more than 99%, and 18 sequences showed below 99%. Tables 2 and 3 shows the bacteria and archaea identified in MFC-1 and MFC-2. For some samples one has two entries from NCBI, because the first one is a partial sequence or corresponds to uncultured species. Table 2 Bacteria and archaea (anode) identified in the MFC-1 using RFLP analysis. Table 2 Sample Closest relative Accession number Similarity (%) Order/class Phylogenetic affiliation Bacteria A-9 Acinetobacter baylyi AB859675.1 99 Pseudomonadales/γ-proteobacteria Proteobacteria A-12 Rhodocyclaceae bacterium AB723853.1 100 Rhodocyclales/β-proteobacteria Proteobacteria A-28 Uncultured bacterium FJ416412.1 99 – Proteobacteria A-29 Uncultured bacterium KC521781.1 98 – Proteobacteria A- 65 Rhodocyclaceae bacterium AB723853.1 99 Rhodocyclales/β-proteobacteria Proteobacteria A-69 Pseudoxanthobacter sp. DDT-1 FJ587218.1 98 Rhizobiales/α-proteobacteria Proteobacteria A-75 Flavobacteriaceae bacterium 18–10PB JX491324.1 93 Flavobacteriales/Flavobacteriia Bacteroidetes A-85 Acidovorax sp. CSC45 JN541154.1 99 Burkholderiales/β-proteobacteria Proteobacteria Archaea A-9 Methanosarcinales QEBH4ZF091 KF198803.1 99 Methanosarcinales/Methanomicrobia Euryarchaeota A-12 Uncultured archaeon JX000057.1 100 – Euryarchaeota A-16 Methanolinea sp. B1-A-15 JN836394.1 99 Methanomicrobiales/Methanomicrobia Euryarchaeota A-20 Methanomicrobiales 108ZC12 KF198732.1 99 Methanomicrobiales/Methanomicrobia Euryarchaeota A-35 Methanosarcinales QEBH4ZF091 KF198803.1 99 Methanosarcinales/Methanomicrobia Euryarchaeota A-53 Methanomicrobiales 108ZC12 KF198732.1 99 Methanomicrobiales/Methanomicrobia Euryarchaeota A-147 Methanosarcinales QEBH4ZF091 KF198803.1 99 Methanosarcinales/Methanomicrobia Euryarchaeota Table 3 Bacteria (anode and cathode) and archaea (anode) identified in the MFC-2 using RFLP analysis. Table 3 Sample Closest relative Accession number Similarity (%) Order/class Phylogenetic affiliation Bacteria A-1 Pseudomonas sp. X-b2 JX997894.1 99 Pseudomonadales/γ-proteobacteria Proteobacteria A-8 Propionivibriomilitaris MP EU849004.2 99 Rhodocyclales/β-proteobacteria Proteobacteria A-11 Geobacter sp. OSK2A AB762695.1 97 Desulfuromonadales/Δ-proteobacteria Proteobacteria A-13 Cupriavidus sp. B55 KF788067.1 99 Burkholderiales/β-proteobacteria Proteobacteria A-21 Pseudomonas sp. G1–10 KF578422.1 99 Pseudomonadales/γ-proteobacteria Proteobacteria A-22 Geobactersulfurreducens PCA NR_075009.1 99 Desulfuromonadales/Δ-proteobacteria Proteobacteria A-29 Cupriavidus sp. B55 KF788067.1 99 Burkholderiales/β-proteobacteria Proteobacteria A-34 Azospira sp. Tagus KC247691.1 99 Rhodocyclales/β-proteobacteria Proteobacteria A-48 Pseudomonas sp. X-b2 JX997894.1 99 Pseudomonadales/γ-proteobacteria Proteobacteria A-62 Chryseobacteriumkoreense AB681907.1 99 Flavobacteriales/ Flavobacteria Bacteroidetes C-7 Uncultured bacterium JX883006.1 99 – Proteobacteria C-8 Rhodanobacter sp. BJQ-6 EU876661.1 99 Xanthomonadales/γ-proteobacteria Proteobacteria C-26 Methyloversatilis universalis FAM5 NR_043813.1 99 Rhodocyclales/β-proteobacteria Proteobacteria C-33 Rhodanobacter sp. BJQ-6 EU876661.1 99 Xanthomonadales/γ-proteobacteria Proteobacteria C-41 Mesorhizobium sp. DLS-79 FN646688.1 98 Rhizobiales/α-proteobacteria Proteobacteria C-45 Acidovorax sp. Van62 HQ222278.1 99 Burkholderiales/β-proteobacteria Proteobacteria C-57 Terrimonas sp. YJ03 JN848793.1 99 Sphingobacteriales/ Sphingobacteria Bacteroidetes C-67 Terrimonas sp. CR94 FJ772030.2 97 Sphingobacteriales/ Sphingobacteria Bacteroidetes C-74 Nitrosomonas sp. HP8 HF678378.1 98 Nitrosomonadales/β-proteobacteria Proteobacteria C-117 Acidobacteria P105 KJ461654.1 99 Acidobacteriales/ Acidobacteria Acidobacteria Archaea A-15 Methanosarcinales archaeon S4 GU475184.1 100 Methanosarcinales/ Methanomicrobia Euryarchaeota A-21 Methanobrevibactersmithii NR_074235.1 99 Methanomicrobiales/Methanomicrobia Euryarchaeota A-31 Methanomicrobiales KF198732.1 99 Methanomicrobiales/Methanomicrobia Euryarchaeota A-35 Uncultured archaeon KF670358.1 100 – Euryarchaeota A-42 Methanolineatarda NOBI-1 NR_028163.1 98 Methanomicrobiales/Methanomicrobia Euryarchaeota A-50 Methanobrevibacter AZ AY196663.1 99 Methanomicrobiales/Methanomicrobia Euryarchaeota A-63 Nitrososphaera gargensis Ga9.2 NR_102,916.1 98 Nitrososphaerales/Nitrososphaeria Thaumarchaeota A-71 Methanomicrobiales 108ZC12 KF198732.1 99 Methanomicrobiales/Methanomicrobia Euryarchaeota 3.5.3 Dominant bacteria existed in MFC −1 The bacteria Acinetobacter baylyi, Rhodocyclaceae, Pseudoxanthobacter sp. DDT-1, Flavobacteriaceae 18–10 PB, Acidovorax sp. CSC45, Pseudomonas geniculata H10, Pseudomonas sp.a-1–7, Burkholderia sp. CRRI-84 and Aminobacter sp. ZYYR1were observed in the MFC-1 ( Table 2 ) . A. baylyi belongs to the order Pseudomonadales, class γ-proteobacteria, it is a non-pathogenic soil bacterium involved in the degradation of aromatic compounds and the production of triacylglycerols and wax esters [52] . Rhodocyclaceae bacteria belong to the order Rhodocyclales, class β-proteobacteria. Oren, 2014 [53] reported that the family Rhodocyclaceae are anoxygenic photoheterotrophs, can degrade the waste materials; aromatic compounds and also perform propionic acid fermentation. Pseudoxanthobacter sp. DDT-1 belongs to the order Rhizobiales, class α-proteobacteria. Liu et al., 2014 [54] isolated Pseudoxanthobacterliyangensis sp DDT-3(T) from dichlorodiphenyltrichloroethane contaminated soil. Flavobacteriaceae 18–10 PB belongs to the order Flavobacteriales and class Flavobacteria. These bacteria were isolated from municipal wastewater by Allen et al., 200 [55] . Acidovorax sp. CSC45 belongs to the order Burkholderiales and class β-proteobacteria. Vayenas, 2011 [56] reported that Acidovorax bacteria species have been isolated from the mixed cultures in denitrification reactors. Bacteria belongs to Pseudomonas group, P. geniculata H10 and Pseudomonas sp. a-1–7 were identified in the reactor which belongs to the order Pseudomonadales and class γ-proteobacteria. Many reports were available about electricity generation using Pseudomonas group of bacteria. Qiao et al., 2017 [57] used the bacterium P. aeruginosa for the electricity generation. Burkholderia sp. CRRI-84 belongs to the order Burkholderiales and class β-proteobacteria. Hunter and Manter, 2011 [58] reported that Burkholderiacenocepacia released oxidizers into the media to improve the electrical output of MFC. Aminobacter sp. ZYYR1 belongs to the order Rhizobiales and class α-proteobacteria also important strains. McDonald, 2005 [59] isolated the bacterial strains IMB-1 and CC495 from agricultural soil which can grow on methyl chloride and methyl bromide. Presence of all these organisms showed positive influence on electricity generation and substrate degradation in MFCs. 3.5.4 Dominant bacteria existed in MFC-2 The bacteria Propionivibriomilitaris, Geobacter sp., Cupriavidus sp., Azospira sp., Chryseobacteriumkoreense,Rhodanobacter sp., Methyloversatilisuniversalis, Mesorhizobium, Terrimonas sp., Nitrosomonas and Acidobacteria were observed in the MFC-2 ( Table 3 ) . Propionivibriomilitaris belongs to the order Rhodocyclales, class, β-proteobacteria, can use chemoorganotrophic substrates such as acetate and propionate as electron donors for growth [60] . Geobacter sp. belongs to the order Desulfuromonadales and class Δ-proteobacteria. Sun et al., 2014 [61] reported that Geobacter sp. SD-1 produced current of 220±4Am −3 in a highly saline water. Cupriavidus sp. belongs to the order Burkholderiales and class β-proteobacteria. Friman et al., 2013 [62] reported that C. basilensis cells growing in the anode in a defined medium with acetate or phenol produced current of 902 and 310 mA m − 2 respectively. Azospira sp. belongs to the order Rhodocyclales and class β-proteobacteria. Yong et al., 2015 [63] reported that Azospira , Azospirillum, Acinetobacter, Bacteroides, Geobacter, Pseudomonas, and Rhodopseudomonas are active communities present in BES reactor. No reports were found about the role of Chryseobacteriumkoreense in MFC which belongs to the order Flavobacteriales and class Flavobacteria. Rhodanobacter sp. belongs to the order Xanthomonadalesand class γ-proteobacteria. Patil et al., 2009 [64] reported that Rhodanobacterlindaniclasticus was present in the anodic chamber of MFCs. Methyloversatilis universalis belongs to the order Rhodocyclales and class β-proteobacteria, and these strains were facultative methylotrophs that can grow on a variety of C1 and multi carbon compounds [65] . Mesorhizobium belongs to the order Rhizobiales and class α-proteobacteria. Studies found that denitrification bacteria Mesorhizobium was involved in the NO 2 − , NO 3 − reduction process in MFC [66] . Terrimonas sp. belonging to the order Sphingobacteriales and class Sphingo bacteria were also identified in MFC [67] . Nitrosomonas belongs to the order Nitrosomonadales and class β-proteobacteria. Khunjar et al., 2012 [68] used Nitrosomonas europaea , as biocatalyst to utilize ammonia as its sole energy source for growth in a reverse MFC. Acidobacteria belongs to the order Acidobacteriales and class Acidobacteria, these are physiologically diverse, able to utilize different substrates in MFC and produce electricity [69] . 3.5.5 Dominant archaea existed in MFC-1 and MFC-2 Almost similar types of archaea were observed in both MFC-1 and MFC-2. Methanosarcinales , uncultured archaeon, Methanolinea, and Methanomicrobiales were observed in the MFC-1. Methanobrevibactersmithii and Nitrososphaeragargensis were observed in the MFC-2. Methanosarcinales QEBH4ZF091 belongs to the order Methanosarcinales and class Methanomicrobia. Olubunmi, 2016 [70] reported that Methanosarcinales related species are present in sediment and sludge inoculated reactors, and have the ability of using a variety of substrates. These archaea species are dominating and produce methane in the anaerobic digestion process. Kendall and Boone, 2006 [71] reported that these microbes catalyze the terminal step in the degradation of organic matter. Methanomicrobiales are strictly carbon dioxide reducing methanogens and using hydrogen or formate as the reducing agent [72] .Wu et al., 2019 [73] analyzed the abundance of methanogens, Methanomassiliicoccus, Methanoregula and Methanolinea by quantifying and sequencing the mcrA gene. Methanobrevibactersmithii belongs to the order Methanomicrobiales and class Methanomicrobia. Nitrososphaeragargensis is ammonia and nitrite oxidizing organism belongs to the order Nitrososphaerales and class Nitrososphaeria [74] ."
} | 7,406 |
27077014 | PMC4830246 | pmc | 8,009 | {
"abstract": "Oxygen minimum zones (OMZ) are areas in the global ocean where oxygen concentrations drop to below one percent. Low oxygen concentrations allow alternative respiration with nitrate and nitrite as electron acceptor to become prevalent in these areas, making them main contributors to oceanic nitrogen loss. The contribution of anammox and denitrification to nitrogen loss seems to vary in different OMZs. In the Arabian Sea, both processes were reported. Here, we performed a metagenomics study of the upper and core zone of the Arabian Sea OMZ, to provide a comprehensive overview of the genetic potential for nitrogen and methane cycling. We propose that aerobic ammonium oxidation is carried out by a diverse community of Thaumarchaeota in the upper zone of the OMZ, whereas a low diversity of Scalindua -like anammox bacteria contribute significantly to nitrogen loss in the core zone. Aerobic nitrite oxidation in the OMZ seems to be performed by Nitrospina spp . and a novel lineage of nitrite oxidizing organisms that is present in roughly equal abundance as Nitrospina . Dissimilatory nitrate reduction to ammonia (DNRA) can be carried out by yet unknown microorganisms harbouring a divergent nrfA gene. The metagenomes do not provide conclusive evidence for active methane cycling; however, a low abundance of novel alkane monooxygenase diversity was detected. Taken together, our approach confirmed the genomic potential for an active nitrogen cycle in the Arabian Sea and allowed detection of hitherto overlooked lineages of carbon and nitrogen cycle bacteria.",
"conclusion": "Conclusion In this study, we compared the functional diversity in two metagenomes retrieved from the Arabian Sea oxygen minimum zone. Using manually curated reference databases, we screened the datasets for homologues indicative for nitrogen and methane turnover in this ecosystem. We are aware that the presence of genetic potential alone cannot be used to draw conclusions on activity of various processes. However, despite this limitation, the picture that emerges from our analysis is that the vast majority of organisms can contribute to nitrate reduction, probably coupled to degradation of organic matter and release of ammonium ( Kalvelage et al., 2015 ). The nitrite formed by nitrate reduction can be re-oxidized to nitrate in a ‘nitrite loop’ ultimately resulting in removal of additional organic matter and release of more ammonium. The nrf -like nitrite reductase assembled from our dataset is only distantly related to described nrf sequences indicating that a yet unknown organism is responsible for this reaction in the Arabian Sea. The released ammonium can partially be oxidized by a diverse community of microaerophilic archaeal ammonium oxidizers, but in the core of the OMZ, the majority is likely converted by anammox bacteria, which contribute about 5% to the total abundance at the station PA5. Here, we could confirm the presence of a low diversity dominated by a Candidatus ‘ Scalindua arabica ’-like anammox species as observed in previous studies ( Villanueva et al., 2014 ; Woebken et al., 2008 ). Although denitrification was observed as the dominant process in another Arabian Sea study ( Ward et al., 2009 ), our analysis, albeit only based on the genetic potential, does not support this point. Rather, an intricate nitrogen cycle involving many organisms and the exchange of intermediates and connection to other processes, as recently hypothesized for estuary and an aquifer ( Hug et al., 2016 , Baker et al., 2015 ) seems likely. The ultimate removal of nitrogen is most likely mediated by anammox. We found no evidence for methane turnover in the Arabian Sea OMZ, however, the metagenomes revealed the presence of new alkane monooxygenase diversity in this ecosystem.",
"introduction": "Introduction Oxygen is a key parameter for biogeochemical cycling and has major impact on the marine nitrogen and carbon turnover. The vast majority of the global ocean waters is well oxygenated, allowing aerobic micro- and macro-organisms to thrive. However, in several areas, underlying regions of high productivity, dissolved oxygen concentrations drop to very low levels. These regions are referred to as oxygen minimum zones (OMZ). There is not a general agreement on the definition of an OMZ; however, an oxygen concentration of ≤20 µM was proposed ( Lam & Kuypers, 2011 ). Using this threshold, approximately 1% of the total ocean volume can be defined as an OMZ ( Lam & Kuypers, 2011 ). In the eastern tropical North Pacific (ETNP), the eastern tropical South Pacific (ETSP) and the Arabian Sea, the three prominent OMZs, oxygen concentration can even drop below levels detectable by sensitive modern techniques ( Revsbech et al., 2009 ; Thamdrup, Dalsgaard & Revsbech, 2012 ). Despite comprising only a small fraction of the total ocean volume, OMZs contribute 30–50% of the nitrogen loss from the ocean ( Gruber & Sarmiento, 1997 ; Codispoti et al., 2001 ). This can be attributed to a highly active nitrogen cycle in these systems ( Lam & Kuypers, 2011 ). After depletion of oxygen, nitrate is the next most energetically favourable terminal electron acceptor and is present in micro-molar concentrations in OMZs (e.g., Pitcher et al., 2011 ). Nitrate reduction coupled to the oxidation of organic matter releases 16 mole ammonium per mole organic matter oxidized ( Redfield, Ketchum & Richards, 1963 ). In addition to this, ammonium can be produced by dissimilatory nitrite reduction to ammonium (DNRA). Despite being aerobic processes, ammonium and nitrite oxidation occur in OMZs, partially converting the ammonium back to nitrite and nitrate ( Kalvelage et al., 2011 ; Kalvelage et al., 2015 ; Füssel et al., 2012 ). Eventually, nitrogen is lost from the system due to denitrification ( Groffman et al., 2006 ; Ward et al., 2009 ) or anaerobic ammonium oxidation (anammox) ( Kuypers et al., 2003 ; Kalvelage et al., 2015 ). The relative contribution of anammox and denitrification to nitrogen loss from OMZs has been the subject of debate ( Lam & Kuypers, 2011 ). Before the discovery of anammox, denitrification was thought to be the only contributor ( Codispoti & Richards, 1976 ; Lipschultz et al., 1990 ; Devol et al., 2006 ), but the detected ammonium concentrations were lower than expected based on just denitrification. After the discovery of the anammox process in the Black Sea ( Kuypers et al., 2003 ), anammox bacteria were shown to occur in all the major OMZ using marker genes, lipid analysis, FISH and stable isotope pairing (e.g., Kuypers et al., 2005 ; Thamdrup et al., 2006 ; Hamersley et al., 2007 ). In the ETSP OMZ, anammox was the dominant process involved in nitrogen loss ( Lam & Kuypers, 2011 ; Stewart, Ulloa & DeLong, 2012 ). For the Arabian Sea OMZ, evidence for both denitrification and anammox as the dominant cause of nitrogen loss exists ( Ward et al., 2009 ; Jensen et al., 2011 ; Pitcher et al., 2011 ) and the contribution of either process likely varies with season and location. Previous studies on nitrogen cycling the Arabian Sea OMZ focused on one or (a comparison of) a few processes such as ammonia oxidation ( Newell et al., 2011 ; Schouten et al., 2012 ), denitrification ( Jayakumar et al., 2004 ; Ward et al., 2009 ), and anammox ( Jensen et al., 2011 ; Pitcher et al., 2011 ; Villanueva et al., 2014 ). A recent study used metagenomes obtained from samples across the ETSP, ETNP and the Bermuda Atlantic Time-series Station to access the distribution of iron and copper containing nitrogen cycle enzymes in these systems ( Glass et al., 2015 ), but a comprehensive study of the nitrogen cycling potential in the Arabian Sea OMZ is lacking. Furthermore, only very little is known on methane turnover in oxygen minimum zones. Low concentrations of methane have been reported at sites of the ETNP and the ETSP suggesting the possibility of methane cycling in these ecosystems ( Sansone & Popp, 2001 ; Padilla et al., 2016 ). In addition, pmoA genes (encoding the particulate methane monooxygenase, see Table 1 ) have been detected in the water column of the ETSP OMZ indicating the presence of aerobic methanotrophs ( Tavormina et al., 2013 ). In the Arabian Sea, high methane concentrations (up to 227% saturation compared to atmospheric levels) have been measured in the surface waters ( Owens et al., 1991 ; Bange et al., 1998 ; Upstill-Goddard, Barnes & Owens, 1999 ) and elevated concentrations (up to approximately 8 nM) were found at 150–200 m depths ( Jayakumar et al., 2001 ). Not much is known about the processes and the organisms involved in production or turnover, but recently Thaumarchaeota cleaving methylphosphonates have been proposed as a potential source of methane in the oceans ( Metcalf et al., 2012 ). 10.7717/peerj.1924/table-1 Table 1 Overview of nitrogen and methane cycle marker genes and BLAST score ratio cut-off value used for removal of false positive BLAST hits. See Fig. S2 for a graphical overview of the bit-score ratio analysis pipeline. DNRA: dissimilatory nitrite reduction to ammonia. Anammox: anaerobic ammonia oxidation. Process Enzyme name Gene abbreviation BLAST score ratio cutoff (PA2/PA5) Nitrogen fixation Nitrogenase nifH #/# Nitrification Ammonium monooxygenase amoA #/# Hydroxylamine oxidoreductase hao # / 0.75 Nitrate:nitrite oxidoreductase nxrA 0.85*/0.85* Denitrification/DNRA/anammox Nitrate reductase narG 0.5/0.5 Denitrification Copper nitrite reductase nirK 0.55/0.55 Heme cd1 nitrite reductase nirS #/0.6 Nitric oxide reductase norB/norZ 0.8/0.8 Nitrous oxide reductase nosZ 0.8/0.75 DNRA Cytochrome c nitrite reductase nrfA #/# Anammox Hydrazine synthase hzsA #/0.75 Hydrazine dehydrogenase hdh **/** Methanogenesis/anaerobic methane oxidation Methyl-coenzyme M reductase mcrA #/# Aerobic methane oxidation Soluble methane monooxygenase mmoX #/# Particulate methane monooxygenase pmoA #/# Methylphosphonate production Methylphosphonate synthase mpnS #/# Methylphosphonate cleavage C-P lyase phnGHI #/# Notes. # Manually checked. * Subset of narG hits. ** Subset of hao hits after mapping against Scalindua hdh . Metagenomics is a powerful tool to provide an all-inclusive picture of the functional potential of an ecosystem. As sequencing is becoming easier and less expensive, the bottleneck in metagenomics is shifting from data generation to sequence analysis strategies. Here, we developed a new analysis strategy for mining metagenome data, based on curated databases of marker genes for nitrogen and methane cycle processes (see Table 1 for an overview of the used marker genes). We applied this strategy to metagenome data retrieved from two depths along the oxygen gradient of the Arabian Sea OMZ.",
"discussion": "Results and Discussion Metagenomics can be used as powerful tool to gain insights into the functional potential of an ecosystem. As the sequencing procedure itself is becoming easier and less expensive resulting in generation of large amounts of data, sequence analysis strategies are becoming a bottleneck in time and resources. Depending on the diversity and complexity of the dataset, different analysis approaches are needed. In this study, we provide a strategy for the systematic screening of metagenomes for nitrogen and methane cycling potential using curated functional gene reference databases. We applied our strategy to a dataset from the Arabian Sea oxygen minimum zone (OMZ) analysing the genetic potential for nitrogen and methane turnover in the upper limit (station PA2) characterized by low oxygen (approximately 5 µM, Table S1 ) and the core zone (station PA5) in which the oxygen concentration drops below the detection limit (3.4 µM) ( Table S1 ). 10.7717/peerj.1924/fig-1 Figure 1 Overview of microbial 16S rRNA gene diversity in the Arabian Sea oxygen minimum zone. Overview of microbial 16S rRNA gene diversity detected in the suboxic zone (station PA2) and the anoxic core (station PA5) of the Arabian Sea oxygen minimum zone. Sequence reads are shown as percentage of total 16S rRNA read counts. Only phylogenetic groups accounting for more than 1% of the total community in at least one of the two datasets are listed. Taxonomy based on 16S rRNA gene analysis To get insight into the overall microbial community in the Arabian Sea OMZ, we analysed 16S rRNA gene reads retrieved from the metagenomes at station PA2 and PA5 ( Fig. 1 ). At the upper limit of the OMZ (station PA2, Table S1 ), the SAR11 clade ( Alphaproteobacteria ) formed one of the most abundant microbial groups (14%). This clade represents in general one of the most abundant microorganisms in seawater, contributing up to 30% of all bacterioplankton ( Morris et al., 2005 ). Sub-clusters within the SAR11 clade have been linked to ecotypes occupying different niches in the ocean water column ( Field et al., 1997 ; Vergin et al., 2013 ). In the PA2 dataset, most sequence reads clustered within SAR11 subgroup 1, closely related to cultivated strains of ‘ Candidatus Pelagibacter ubique.’ ‘ Ca. P. ubique’ has a small, streamlined genome adapted to rapid heterotrophic growth ( Rappe et al., 2002 ; Giovannoni et al., 2005 ) and is unlikely to directly contribute to nitrogen cycling in the Arabian Sea OMZ. The remainder of the SAR11 reads were distributed across the entire SAR11 clade. Ammonium oxidizing Archaea (AOA) of the Marine Group I (MG-I) Thaumarchaeota were as abundant as SAR11 at station PA2 (14%), confirming previous PCR- and lipid-based analyses showing that Thaumarchaeota were abundant at this location ( Pitcher et al., 2011 ). Both SAR11 and MG-I were less abundant in the OMZ core, but still have a substantial presence of 8.1% and 3.3% respectively ( Fig. 1 ). Reads affiliated with the bacterial SAR86 clade ( Gammaproteobacteria ) and archaeal Marine Group II (MG-II) made up 8% and 7% of the 16S rRNA gene reads at station PA2, but were only marginally present in the OMZ core (1.5 % and 0.4 % of the reads, respectively). This is consistent with an aerobic heterotrophic lifestyle predicted from previously obtained genomes of organisms of both lineages ( Dupont et al., 2012 ; Iverson et al., 2012 ). So far, no metabolic adaptations of these organisms to an anaerobic lifestyle have been characterized. Nevertheless, the persistence, albeit in low abundance, of aerobic organisms in the anoxic OMZ core might be partially explained by the attachment to slowly sinking organic particles, also referred to as marine snow ( Wright, Konwar & Hallam, 2012 ). Formed in the metabolically active photic zone, these particles continuously sink through the water column to the floor of the ocean and thereby also passing the anoxic core of the OMZ. Association to particles has been previously proposed for SAR11 ( Zeigler Allen et al., 2012 ) and demonstrated for the MG-II Archaea ( Orsi et al., 2015 ). The deep-branching bacterial phylum Marinimicrobia (formerly SAR406) ( Fuhrman, McCallum & Davis, 1993 ; Gordon & Giovannoni, 1996 ; Rinke et al., 2013 ) comprised 9% of all 16S rRNA affiliated sequence reads at station PA2 and 20% at PA5. A recent transcriptome study indicates the involvement of these bacteria in extracellular proteolysis and fermentative amino acid degradation in a methanogenic environment ( Nobu et al., 2015 ). These findings of an anaerobic lifestyle agree well with their high abundance in a low oxygen environment (upper OMZ) and their dominance in the OMZ core. The detected Rhodospirillales ( Alphaproteobacteria ) might also contribute to fermentation of organic matter, as this order comprises known acetic acid bacteria. Rhodospirillales were barely detectable at the OMZ upper limit, but comprise 4.1% of the community at the OMZ core. Other abundant lineages include the Deltaproteobacteria SAR324. These bacteria are frequently found in the ocean and seem to be correlated with low oxygen concentrations ( Wright, Konwar & Hallam, 2012 ; Sheik, Jain & Dick, 2014 ). SAR324 representatives have been shown to be able to fix CO 2 ( Swan et al., 2011 ) and are predicted to be capable of autotrophic denitrification with various electron donors ( Sheik, Jain & Dick, 2014 ). Likewise, Gammaproteobacteria of the SUP05 lineage have been implied in autotrophic denitrification with sulphur as electron donor ( Lavik et al., 2009 ; Walsh et al., 2009 ; Russ et al., 2014 ). They furthermore have been associated with cryptic sulfur cycling in the ETSP OMZ ( Canfield et al., 2010 ). Members of both SAR324 and SUP05 have a similar presence at both stations (5% in PA2 and 3.1% in PA5 for the SAR324 lineage, 2.9% and 2.7% for the SUP05 lineage), with SAR324 slightly decreasing in the OMZ core ( Fig. 1 ). Anammox 16S rRNA genes are barely detected at the upper limit of the OMZ, consistent with previous analyses ( Pitcher et al., 2011 ; Villanueva et al., 2014 ), but comprise almost 5% of the community at the OMZ core. Interestingly, a recent study showed that autotrophic denitrifiers oxidizing hydrogen sulphide could form a stable community with anammox bacteria in a reactor system ( Russ et al., 2014 ). Whether this is also the case at the OMZ core remains to be investigated. Although some of the lineages discussed above are abundant, assembly of the complete metagenome reads did not yield any contigs with high sequencing depth, indicating the diversity within each lineage is substantial. To assess the diversity and phylogeny of the detected AOA and anammox bacteria in more detail, reads matching the 16S rRNA gene of either group were extracted and assembled into contig sequences for phylogenetic tree construction. Reads affiliated with MG-I AOA from the OMZ upper limit (PA2) could be assembled into two representative contigs: Contig-1 comprises 41% of all extracted MG-I reads and contig-2 was built from 15% of the reads. Thus, the two contigs represent the majority of the thaumarchaeotal community. Nevertheless, these sequences do not represent a single genotype but represent a hybrid of 16S rRNA reads from multiple closely related organisms ( Fig. S1 ). Contig-1 shows 98% identity to the very recently described ‘ Candidatus Nitrosopelagicus brevis’ ( Fig. 2 ) ( Santoro et al., 2015 ), contig-2 has only moderate identities to isolated or enriched ammonia oxidizers (93% identity to Nitrosoarchaeum limnia SFB1) ( Fig. 2 ). 10.7717/peerj.1924/fig-2 Figure 2 Phylogenetic inference of thaumarchaeal contigs assembled from the OMZ metagenomes. The trees were calculated using the Neighbor Joining algorithm and based on 1,225 nucleotide positions for the 16S rRNA gene (A) and 144 deduced amino acid positions for the ammonia monooxygenase encoding gene ( amoA ) (B). Reads from station PA5 clustering with the Brocadiaceae , the family comprising all known anammox bacteria, were extracted and could be assembled into one representative sequence. Here, diversity was considerably less than for the Thaumarchaeota and the contig represents a single genotype that is 96% identical to Scalindua brodae , the closest sequenced relative ( Speth et al., 2015 ), and 99% identical to ‘ Candidatus Scalindua arabica’ clones previously obtained from the Arabian sea OMZ ( Fig. 3 ) ( Woebken et al., 2008 ). Interestingly, sequences obtained by Ward and co-workers from the Arabian Sea OMZ share only 97% sequence identity to the extracted contig ( Ward et al., 2009 ) indicating a spatial or temporal niche differentiation of different Scalindua -like ecotypes in this system. 10.7717/peerj.1924/fig-3 Figure 3 Phylogenetic inference of Scalindua-related contigs assembled from the OMZ metagenomes. The tree were calculated using the Neighbor Joining algorithm and based on 1,388 nucleotide positions for the 16S rRNA gene (A) and 180 deduced amino acid positions for the hydrazine dehydrogenase encoding gene ( hdh ) (B). Genetic potential for nitrogen and methane cycling To assess the nitrogen and methane cycling potential in the metagenome of both the upper limit and the core of the OMZ, we performed BLASTx searches of the metagenomic reads against curated databases of key genes ( Table 1 ) involved in nitrogen and methane cycle processes. To remove false positive hits while keeping divergent sequences, we used a modified BLAST score ratio (BSR) approach (see methods section). Nitrogen cycling potential Nitrification Marker genes indicative for the first step in nitrification, the conversion from ammonia to nitrite, are the amoA (encoding a subunit of the membrane bound ammonium monooxygenase) and the hao gene (encoding the hydroxylamine oxidoreductase). We found 228 reads matching amoA in the PA2 dataset, 227 of which could be assigned to ammonia oxidizing Archaea (AOA), indicating that they contribute approximately 25% to the total microbial community in this sample ( Fig. 4 ). This estimate exceeds the estimated abundance based on 16S rRNA genes ( Fig. 1 ). Our analysis strategy includes the correction for sequencing depth and gene length, however, no correction for gene copy numbers was applied. This information can only be deduced from genomes and is not known for the vast majority of microorganisms. In the presence of genomes harbouring multiple rRNA operons, the total number of detected organisms is artificially inflated, leading to an underestimation of organisms with a single rRNA operon which would explain the lower 16S rRNA estimates in this dataset. An alternative, albeit less likely, explanation for higher amoA estimates can be the presence of multiple copies of the amoA gene in the detected AOA genomes, but this has not been observed in any previously sequenced AOA species. 10.7717/peerj.1924/fig-4 Figure 4 Nitrogen cycling potential in the Arabian Sea oxygen minimum zone. Read abundances were normalized according to gene length and total read abundance in the metagenome dataset. Normalized abundances are shown as proportion (blue) of total normalized rpoB (RNA polymerase) gene abundance (grey). The description of all marker genes and methane and nitrogen cycling processes is given in Table 1 . The amoA reads could be assembled into 5 major contigs (4 contigs from site PA2 and 1 contig from PA5) that were compared to 16S rRNA phylogeny ( Fig. 1 ). As for the 16S rRNA contig, amoA sequences could not be affiliated with a single MG-I species, but showed a diversity of at least 2 major genotypes. Unlike the 16S rRNA gene analysis, none of the contigs clustered with Nitrosopelagicus -like amoA sequences. Instead two out of the four obtained contigs from PA2 did not cluster with, but between the Nitrosopelagicus cluster and Nitrosoarchaeum limnia SFB1. The two other contigs clustered within an environmental group only distantly related to described MG-I AOA. This environmental cluster also contained the only contig that could be assembled from the OMZ core. A niche differentiation between shallow and deep-water clades of MG-I Thaumarchaeota has also been described before in the Arabian Sea OMZ Villanueva, Schouten & Sinninghe Damsté (2014) , but also in other marine environments ( Beman, Popp & Francis, 2008 ; Santoro, Casciotti & Francis, 2010 ). Besides archaeal amoA , only a single read with low identity (<50% on the amino acid level) to known bacterial amoA reads was detected, indicating ammonium oxidizing bacteria (AOB) likely play only a small role in the Arabian sea OMZ although they were detected in other OMZs ( Molina et al., 2007 ; Lam et al., 2009 ). Consistent with the absence of AOB amoA , only five reads matching hao were detected in the upper limit of the OMZ. In the core, 475 reads matched the hao database, but even after removal of the bonafide anammox hydrazine dehydrogenase hits ( Fig. 3 ), over 90% of the hao matches were affiliated with Scalindua , which is known to encode up to ten paralogs of this protein ( Van de Vossenberg et al., 2013 ; Speth et al., 2015 ). The second step of complete nitrification, nitrite oxidation, is challenging to study using a marker gene approach as nitrite oxidoreductase ( NxrA ) and nitrate reductase ( NarG ) are homologous enzymes. A further complicating factor is the polyphyletic nature of the nxrA gene ( Lücker et al., 2010 ). To account for this, we first extracted all the reads matching a combined narG / nxrA reference set, and then used a second round of BLASTx and BLAST score ratio separation (threshold 0.85–0.95) to distinguish between narG and nxrA . No reads could be confidently assigned to nxrA of the Nitrobacter/Nitrococcus/Nitrolancetus group in either station. Conversely, 33% and 23% of the reads matching narG/nxrA were assigned to nxrA of the Nitrospira/Nitrospina /anammox group in PA2 and PA5, respectively. Further separation between nxrA matches, to distinguish the nitrifier nxrA from anammox, was achieved using iterative mapping. Classification using MEGAN indicated that anammox made up 44% of the reads matching nxrA at station PA2. As all other analyses indicated anammox bacteria were virtually absent from this station ( Fig. 1 and Table S2 ), we explored these reads in detail using iterative mapping and manual curation of the sequences. This led to the identification of a novel lineage of nxrA clustering between anammox and Nitrospina sequences ( Fig. 5 ), which was slightly more abundant than the retrieved Nitrospina sp. at both station PA2 (approx. 2% and 1.5% of the population respectively) and PA5 (approx. 3% and 2% of the population respectively). Interestingly, distinct lineages of both the putative novel nitrite oxidizer and Nitrospina seemed to occupy either station ( Fig. 5 ). The abundance of anammox nxrA in the OMZ core sample correlates well with the abundance as assessed using the 16S rRNA gene ( Table 1 ) and other anammox markers ( Table S3 , discussed below). 10.7717/peerj.1924/fig-5 Figure 5 Phylogenetic inference of nxrA sequences from the OMZ metagenomes. The tree was calculated using the Neighbor Joining algorithm and based on 3,209 nucleotide positions. Bootstrap values represent 1,000 replicates. No other nitrite oxidizing organisms were detected. The detection of a significant abundance of nitrite oxidizers in OMZ ecosystems is consistent with a previous study showing that nitrite oxidation was an active process in the Namibian OMZ ( Füssel et al., 2012 ). Genetic potential for processes contributing to nitrogen loss Nitrite and nitrate resulting from nitrification can be readily used in denitrification, anammox and DNRA. To date, it is still unclear which process is dominating or if a combination of various processes occurs. Most of the recent studies indicated anammox instead of denitrification as prevalent pathway in OMZs ( Kuypers et al., 2005 ; Thamdrup et al., 2006 ; Hamersley et al., 2007 ; Lam et al., 2009 ). However, two reports described high and active denitrification rates in the Arabian Sea OMZ ( Ward et al., 2009 ; Bulow et al., 2010 ). In yet another study, Jensen and co-workers found that anammox coupled to DNRA was the prevalent process in this system ( Jensen et al., 2011 ) and further studies confirmed a high abundance of anammox bacteria at the core of the Arabian Sea OMZ ( Pitcher et al., 2011 ; Villanueva et al., 2014 ). Here, we found that the nitrate reductase is by far the most dominant nitrogen cycle enzyme encoded in the Arabian Sea OMZ core (78% of normalized rpoB gene abundance, Fig. 4 ). This is consistent with observations in the Peruvian oxygen minimum zone ( Lam et al., 2009 ; Glass et al., 2015 ) and in the Eastern Tropical South Pacific OMZ ( Stewart, Ulloa & DeLong, 2012 ). The reduction of nitrate to nitrite is a crucial step as the nitrite forms the starting point for many subsequent processes: nitrite reduction in denitrification, in DNRA and in anammox. Additionally, nitrite can also be re-oxidized to nitrate. The genetic potential for all these processes is substantially encoded in the OMZ core. Consistent with Jensen and co-workers ( Jensen et al., 2011 ), we find the potential for DNRA ( nrfA encoding the penta-heme nitrite reductase as marker gene), approximately in equal abundance to anammox. Upon close inspection 60% of the reads matching nrfA originate from two closely related strains of an unknown organism. The 812 bp hybrid sequence obtained after assembly has 73% identity (AA level) to only two sequences in the database: Coraliomargerita akajimensis ( Verrucomicrobia ) and Pelobacter carbinolicus ( Deltaproteobacteria ). Although the phylogeny of the organisms most likely responsible for DNRA in the Arabian Sea OMZ remains unclear, retrieval of the divergent nrfA emphasizes the potential of our approach for novel microbiological gene discovery. Only few sequences indicative for the process of denitrification were detected. Although many reads matched nitrite reductase encoded by either nirS or nirK ( Table S3 ), 50% of all nirS reads could be classified as Scalindua -related. The nirS contig obtained after assembly of the reads matching Scalindua showed 77% nucleotide sequence identity to Scalindua brodae and 99% identity to unpublished sequences from the Gulf of California and Eastern Tropical North Pacific OMZs (Genbank accession: KC596869 ). It corroborates the 16S rRNA gene analysis indicating the presence of one dominant uncultivated anammox ecotype. Of all detected nirK reads, 70% originated from AOA. These Thaumarchaeota are known to harbour multiple copies of NirK -like copper oxidases encoding genes ( Stahl & De la Torre, 2012 ) explaining their high abundance in the datasets ( Fig. 4 ). It has been previously suggested that nitrifier denitrification accounts for the majority of nitrous oxide observed in the ocean ( Babbin et al., 2015 ; Kozlowski et al., 2016 ). Besides playing a role in nitrifier denitrification, these enzymes are also hypothesized to be the missing hydroxylamine oxidoreductase equivalent in AOA catalysing the oxidation of hydroxylamine to nitrite ( Stahl & De la Torre, 2012 ). Similar to the nirS -type nitrite reductase genes, we found that 40% of all reads matching the norB/norZ reference set (encoding the nitric oxide reductase) at both stations combined were affiliated with Scalindua ( Table S3 ). Potential for the final step of denitrification via nitrous oxide reduction (encoded by the nos genes) was limited with 92 reads at station PA2 and only 27 reads at station PA5 ( Fig. 4 , Table S3 ). We could not find genomic indication for nitrogen loss via the nitric oxide dismutase of NC10 phylum bacteria as recently described for the Eastern Pacific OMZ ( Padilla et al., 2016 ). The abundance of anammox marker genes hzsA (encoding the hydrazine synthase) and hdh (encoding the hydrazine dehydrogenase) coincides well with the abundance estimates based on 16S rRNA, nxrA , and nirS genes consistently indicating that anammox bacteria of the Scalindua genus are present at approximately 5% abundance. The nifH gene, encoding a subunit of the nitrogenase, was used as marker in screening for nitrogen fixation potential in the Arabian Sea datasets. Ocean circulation models have predicted highest nitrogen fixation rates close to zones of nitrogen loss ( Deutsch et al., 2007 ) and were supported by recent studies reporting the presence and transcription of nifH genes in sub-oxic waters of the Arabian Sea ( Jayakumar et al., 2012 ; Bird & Wyman, 2013 ). However, we detected no nifH hits in the PA2 metagenome and only 3 reads matched nifH in the PA5 dataset ( Fig. 3 ). The nifH genes in the above mentioned studies were obtained using PCR amplification with specific primer sets able to detect a much lower abundance of diazotrophs in the environment. Our results indicate a low abundance of diazotrophs that nevertheless would easily be detected by PCR amplification. We can estimate the abundance of diazotrophs from our dataset, assuming an average microbial genome size of 3 Mbp and the nifH gene length of 900 bp. If present in all genomes, 3 reads per 10.000 should contain part of a nifH . However, only 3 reads were detected in the PA5 metagenome (1,6 million reads), which is 160 times lower and thus results in a diazotroph abundance estimate of 0.6% based on the dataset. PCR primers should be able to amplify genes present in organisms with this abundance. Alternatively, the diazotrophic community in our dataset was, for unknown reasons, lower than in other studies from similar ecosystems. Methane cycling potential To examine the methane cycling potential in the Arabian Sea, we selected marker genes targeting methane production and methane oxidation ( Table 1 ). The mcrA gene (encoding the methyl-Coenzyme M reductase) was used as functional marker for methane production and anaerobic methane oxidation. We could not detect any mcrA -like sequences of canonical methanogens or sequences of the very recently described mcrA homologues from Bathyarchaeota ( Evans et al., 2015 ). Also no sequences of anaerobic methane oxidizing archaea (ANME clades) were found. This is consistent with the absence of methanogen 16S rRNA genes and very low abundance (3 reads) of Bathyarchaeota 16S rRNA gene sequences. Thus, methanogenesis does not seem to play a major role in the Arabian Sea OMZ water column. Nevertheless, in marine ecosystems, a second pathway for methane production apart from methanogenesis was proposed ( Karl et al., 2008 ). This aerobic pathway includes the cleavage of methylphosphonate (Mpn). Mpn was shown to be synthesized by the AOA Nitrosopumilus maritimus using the Mpn synthase as key enzyme and a homologue of this enzyme was also found to be encoded in SAR11 genomes ( Metcalf et al., 2012 ). The cleavage of Mpn that results in the release of methane, is catalysed by the C-P lyase multi-enzyme complex ( Daughton, Cook & Alexander, 1979 ). In Escherichia coli , the C-P cleavage is encoded in a 14 gene operon ( Metcalf & Wanner, 1993 ). The composition of the gene cluster is variable among bacteria, however, the phnGHIJKM genes seem to be conserved and essential for activity ( Huang, Su & Xu, 2005 ). We selected the mpnS gene (encoding the Mpn synthase) and the phnGHI genes (encoding components of the C-P lyase pathway) as functional marker genes for aerobic methane production in our datasets. In the PA2 dataset, 45 reads matching the mpnS gene were retrieved, most of which could be affiliated with the MG-I Thaumarchaeota ( Fig. 6 , Table S4 ). Comparing the mpnS read numbers with corresponding 16S rRNA gene and amoA read numbers from Thaumarchaeota results in a far lower abundance of mpnS reads in the dataset. However, this is in good agreement with the observation that not all MG-I Thaumarchaeota encode mpnS in their genome. The dominant MG-I ammonia oxidizer in the Arabian Sea datasets is closely related to Nitrosopelagicus brevis ( Fig. 2 ), which does not possess the mpnS gene ( Santoro et al., 2015 ). In the metagenome from the OMZ core zone, 7 mpnS reads (3 reads matching to MG-I) were detected. 10.7717/peerj.1924/fig-6 Figure 6 Methane cycling potential in the Arabian Sea oxygen minimum zone. Read abundances were normalized according to gene length and total read abundance in the metagenome dataset. Normalized abundances are shown as proportion (blue) of total normalized rpoB (RNA polymerase) gene abundance (grey). Original read abundances are given in addition below or above the pie charts. HEP: 2-hydroxyethylphosphonate. Mpn: Methylphosphonate. The description of all nitrogen and methane cycling marker genes is given in Table 1 . The C-P lyase gene cluster has been found in many genomes of marine bacteria and could also be associated to growth with Mpn as sole phosphorous source ( Dyhrman et al., 2006 ; Martinez, Tyson & DeLong, 2010 ; White et al., 2010 ). In the Arabian Sea datasets, no reads matching the phnGHI genes were detected in PA2 and only 3 phnI sequences affiliated to Rhodobacteriales ( Alphaproteobacteria ) were retrieved from PA5 ( Fig. 6 , Table S4 ). Depending on the dissolved inorganic phosphorous availability, the abundance of bacteria harbouring the gene cluster can vary between as much as 20% and below 1% of all bacteria ( Martinez, Tyson & DeLong, 2010 ), indicating that the presence of the C-P lyase provide an advantage in phosphorous limited environments. We could not find a high abundance of this protein complex in the Arabian Sea OMZ, hence the ability for acquiring phosphorous from Mpn might be less important in this system. In accordance with the absence of marker genes indicative for methane production, only few reads were retrieved that could be affiliated with methane oxidation. For aerobic methane oxidation, we used the marker genes pmoA and mmoX encoding the particulate and soluble methane monooxygenase. In the PA2 dataset, 15 mmoX and 3 pmoA -like reads were detected. However, after closer inspection, all mmoX reads showed moderate sequence identity (up to 71% on amino acid level) to homologous toluene monoxygenases. For the pmoA reads, highest identity (68–97% on amino acid level) was found to the monooxygenase of the SAR324 clade ( deltaproteobacteria ). Based on 16S rRNA gene abundance, the SAR324 clade was found to belong, besides others, to the dominant bacteria in the Arabian Sea dataset ( Fig. 1 ). So far, no enrichment of SAR324 clade bacteria is available and it is not known if this monooxygenase is used for methane or higher alkane oxidation. Whereas the pmoA phylogeny indicates relation to C2-C4 alkane monooxygenases ( Li et al., 2014 ), the genomes of SAR324 members suggest the potential for both, C1 and higher alkane utilization ( Sheik, Jain & Dick, 2014 ). Nevertheless, not all SAR324 genomes contain the alkane monooxygenase gene cluster ( Swan et al., 2011 ). The PA5 dataset revealed 2 pmoA and 2 mmoX -like sequences, again only with moderate sequence identities to known alkane monooxygenases. Consistent with the absence of genes encoding the putative nitric oxide dismutase of NC10 phylum bacteria, we did not find any pmoA genes of these bacteria in the Arabian sea OMZ. Nevertheless, they might be present in a low abundance that could not be retrieved by our approach. Thus, if these bacteria play a role in methane and nitrogen cycling in OMZs, as suggested for the Eastern Pacific OMZ, needs to be investigated in future research ( Padilla et al., 2016 ). In addition, 16S rRNA gene sequences of known aerobic methanotrophs were nearly absent. Only 3 reads clustering within gammaproteobacterial methanotrophs were present (1 read from PA2 and 2 reads from PA5). Although the overall abundance of hydrocarbon monooxygenase encoding reads is low in the Arabian Sea OMZ dataset, our analysis shows the existence of novel sequence diversity only moderately related to known sequences, that is not captured by currently used PCR primers. Conclusion In this study, we compared the functional diversity in two metagenomes retrieved from the Arabian Sea oxygen minimum zone. Using manually curated reference databases, we screened the datasets for homologues indicative for nitrogen and methane turnover in this ecosystem. We are aware that the presence of genetic potential alone cannot be used to draw conclusions on activity of various processes. However, despite this limitation, the picture that emerges from our analysis is that the vast majority of organisms can contribute to nitrate reduction, probably coupled to degradation of organic matter and release of ammonium ( Kalvelage et al., 2015 ). The nitrite formed by nitrate reduction can be re-oxidized to nitrate in a ‘nitrite loop’ ultimately resulting in removal of additional organic matter and release of more ammonium. The nrf -like nitrite reductase assembled from our dataset is only distantly related to described nrf sequences indicating that a yet unknown organism is responsible for this reaction in the Arabian Sea. The released ammonium can partially be oxidized by a diverse community of microaerophilic archaeal ammonium oxidizers, but in the core of the OMZ, the majority is likely converted by anammox bacteria, which contribute about 5% to the total abundance at the station PA5. Here, we could confirm the presence of a low diversity dominated by a Candidatus ‘ Scalindua arabica ’-like anammox species as observed in previous studies ( Villanueva et al., 2014 ; Woebken et al., 2008 ). Although denitrification was observed as the dominant process in another Arabian Sea study ( Ward et al., 2009 ), our analysis, albeit only based on the genetic potential, does not support this point. Rather, an intricate nitrogen cycle involving many organisms and the exchange of intermediates and connection to other processes, as recently hypothesized for estuary and an aquifer ( Hug et al., 2016 , Baker et al., 2015 ) seems likely. The ultimate removal of nitrogen is most likely mediated by anammox. We found no evidence for methane turnover in the Arabian Sea OMZ, however, the metagenomes revealed the presence of new alkane monooxygenase diversity in this ecosystem."
} | 10,325 |
34122890 | PMC8152672 | pmc | 8,010 | {
"abstract": "Stimuli-responsive hydrogels have attracted attention as soft actuators that act similarly to muscles. In this work, hydrogel actuators controlled by host–guest interactions have been developed. The introduction of a 1:1 inclusion complex into a hydrogel is a popular design for achieving a change in cross-linking density. To realize faster and larger deformation properties, the introduction of a 1:2 inclusion complex is effective because the alteration in cross-linking density in a hydrogel with 1:2 complexes is larger than that in a hydrogel with 1:1 complexes. A redox-responsive hydrogel actuator cross-linked with 1:2 inclusion complexes is designed, where γ-cyclodextrin (γCD) and viologens modified with an alkyl chain derivative (VC11) were employed as the host and guest units, respectively. γCD includes two VC11 molecules in its cavity. The obtained γCD–VC11 hydrogel cross-linked with the 1:2 complex showed faster and larger deformation behaviour than the αCD–VC11 and the βCD–VC11 hydrogels cross-linked with a 1:1 complex. The deformation ratio and response speed of the γCD–VC11 hydrogel, which forms a supramolecular cross-linking structure by stimuli, are 3 and 11 times larger, respectively, than those of our previous hydrogel consisting of a βCD/ferrocene 1:1 inclusion complex.",
"conclusion": "3. Conclusion In conclusion, γCD–VC11( x , y ) hydrogels showed effective contraction and expansion properties. The γCD and VC11 unit in the polymer network form a double-threaded 1:2 inclusion complex, which binds three polymer chains through a host–guest cross-linking point. When the γCD–VC11( x , y ) hydrogel was reduced in solution, the radical cation dimer of the viologen moieties is formed as a new cross-linking point. The dimer is included by another γCD unit to form supramolecular cross-linking structures. These two modes, double-threaded 1:2 inclusion complexation and radical cation dimerization inside the γCD cavity, enable the γCD–VC11( x , y ) hydrogels to show the largest deformation among all the hydrogels investigated in this work (the αCD–VC11( x , y ), βCD–VC11( x , y ), and VC11(0.2, y ) hydrogels) and our previous work (βCD–Fc(3,3,1) hydrogel). The mechanism achieved by using two kinds of 2:1 complexation is a new design concept for creating stimuli-responsive materials. In the future, swelling hydrogel actuators triggered by external stimuli could be developed by using new concepts inspired by biomacromolecules (sponge or sarcomere filament) or artificial topological polymer networks.",
"introduction": "1. Introduction Stimuli-responsive polymeric materials have attracted much attention because of their flexibility and macroscopic motion when used as actuators in a similar manner to a muscle. 1 There are some principles and material designs for preparing stimuli-responsive soft materials. 2–5 Dielectric elastomers have typically been used to prepare dielectric actuators, which are driven by generated charges in polymer networks near electrodes. 6–8 The orientation of a crystal lattice or a liquid crystal has been utilized for electrically responsive and photo-responsive materials, where the controlled orientation of the responsive molecules in materials leads to macroscopic deformations in the materials. 9–13 Another method to design responsive materials, control of the cross-linking density or distance between cross-linking points in polymer networks, caused the deformation of materials. Fig. 1 shows those network design concepts of stimuli-responsive supramolecular hydrogels. To achieve stimuli-responsive deformations, supramolecular chemists have chosen certain kinds of external stimuli, such as temperature, chemicals, pH, ionic strength, electric field/voltage/current, and light intensity. 14–24 Herein, we focus on redox-responsive materials based on the mechanism of controlling the cross-linking density by proposing another network design concept that uses an inclusion complex on the polymer side chain ( Fig. 1b ). Fig. 1 Network design concepts of stimuli-responsive supramolecular hydrogels driven by a change in the cross-linking distance (a) and cross-linking density (b). Pink ring: macrocyclic host molecule. Pale green elliptical sphere: stimuli-responsive barrier for the host. Green line: polymer chain. Grey line: linker connecting the host/guest moieties to the polymer chain. The grey linker acts as a station where the host molecule stays. We can control the cross-linking density by using a 1:1 inclusion complex (i) or a 1:2 inclusion complex (ii). Previously, we reported supramolecular polymeric hydrogels showing deformation based on the control of cross-linking density, where the host–guest interactions serving as cross-linking points are controlled by photo- 25–29 and redox-stimuli. 30,31 To realize actuators driven by host–guest interaction, we chose the combination between α-cyclodextrin (αCD) and azobenzene or between β-cyclodextrin (βCD) and ferrocene (Fc) as the 1:1 inclusion complex. 26,30 The 1:1 complex system involves two polymer chains ( Fig. 1b(i) ). The external stimuli control the association and dissociation of the 1:1 inclusion complex to generate the macroscopic expansion and contraction behaviours of the polymeric materials. 5,14 The change ratio of the cross-linking density resulted in a larger amount of displacement in the supramolecular polymeric hydrogel. Considering these results, the ratio of the host and guest units was increased to achieve larger changes in the cross-linking density. However, the βCD–Fc hydrogels with over 5 mol% of the host and guest cross-linking units showed too high Young's moduli to bear the increasing displacement, effectively. 30 Although polymer networks having a 1:1 inclusion complex are one of the established designs for achieving macroscopic motion, additional new network designs for supramolecular polymeric hydrogels should be proposed. To realize larger deformation, we introduced a 1:2 double-threaded inclusion complex into the polymer network because three polymer chains are involved in the 1:2 inclusion complex systems ( Fig. 1b(ii) ). Compared to a 1:1 inclusion complex, a 1:2 inclusion complex can bind three polymer chains together through the association and dissociation of the complexes to bring about a larger change in the cross-linking density. Of course, some excellent supramolecular gels using a 1:2 inclusion complex with two kinds of guest molecules and cucurbit[8]uril as a host molecule were reported. 32–38 These polymeric host–guest materials having two kinds of guest molecules successfully achieved hydrogelation and modulation in the presence of cucurbit[8]uril. The 1:1 inclusion complex in these systems can be applied as a cross-linking point between two polymer chains. If we use a 1:2 inclusion complex with three polymer chains, we will observe a larger change in cross-linking density and volume change. Based on this hypothesis, herein, we focus on redox-responsive materials, the cross-linking density of which can be controlled. We chose the combination of cyclodextrins (CDs) and viologens tethered to an undecyl unit (VC11; 4-undecyl-4′-methyl-bipyridinium dichloride) as host and guest units, respectively, as the 1:2 inclusion complex with three polymer chains. Here, we used α-, β- and γ-cyclodextrin (αCD, βCD and γCD) that consist of 6, 7 and 8 glucose units, respectively, with different cavity sizes (α-CD < β-CD < γ-CD).",
"discussion": "2. Results and discussion 2.1. Preparation of host–guest hydrogels We use three kinds of redox-responsive host–guest hydrogels, αCD–VC11( x , y ), βCD–VC11( x , y ) and γCD–VC11( x , y ) hydrogels ( Fig. 2a–c ). Both the undecyl unit and the one-electron reduced viologen (monocation radical) unit in VC11 can act as guest units for the CD host. 39–41 While shorter alkyl chains such as hexyl groups also act as guest units for CDs, the undecyl group was found to form a more stable complex with CDs. 42 In contrast, the oxidized viologen unit (dication) in VC11 does not form an inclusion complex with CDs because of the electrostatic repulsion between the inner cavity of the CDs and the oxidized viologen unit. 43–47 The electrostatic repulsion at the ends of the alkyl chain can function as an electric barrier to prevent the dissociation of the inclusion complex between the alkyl chain-tethered viologen guests and the CD hosts. 42 Therefore, the viologen unit can be used to kinetically control the association and dissociation of the complex. In this work, we found that the responsiveness (displacement and speed of the macroscopic deformation) of the γCD–VC11( x , y ) hydrogel is greater than that of the αCD–VC11( x , y ), βCD–VC11( x , y ) and chemically cross-linked control hydrogels (the VC11(0.2, y ), γCD( x ) and polyacrylamide (pAAm) hydrogels in Fig. 2d–f ). The covalent cross-linking by MBAAm often gave hard hydrogels, compared to host–guest cross-linking hydrogels. Hardness has some potential to affect the other physical properties. Therefore, the molar fraction of MBAAm was optimized to be 0.2 mol% to adjust the Young's modulus of the VC11 hydrogel to those of the CD–VC11 hydrogels. Fig. 2 Chemical structures of the αCD–VC11( x , y ) hydrogels (a), βCD–VC11( x , y ) hydrogels (b), and γCD–VC11( x , y ) hydrogels (c) as supramolecular host–guest hydrogels. The VC11(0.2, y ) hydrogels (d), γCD( x ) hydrogels (e), and pAAm hydrogels (f) are covalently cross-linked control hydrogels. Prior to polymerization, the complex formation behaviours and stoichiometric proportions of the CDs and VC11 units were investigated. Fig. S3, S5 and S7 † show the inclusion complexes of the CDs with VC11 observed by acquiring 2-dimensional rotating frame Overhauser effect spectroscopy (2D ROESY) nuclear magnetic resonance (NMR) spectra in D 2 O. These spectra demonstrated that the inner protons of the CDs were correlated with the protons of the undecyl unit of the VC11 monomer, indicating that the CD and VC11 monomers form inclusion complexes. The stoichiometry of the CD/VC11 complexes was determined by 1D 1 H NMR and isothermal titration calorimetry (ITC) measurements. α and βCDAAmMe each form a 1:1 inclusion complex with the VC11 monomer (Fig. S4 and S6 † ). On the other hand, 1:2 complexation was observed between γCDAAmMe and the two VC11 monomers in the Job plot and ITC (Fig. S8 † ). αCD–VC11( x , y ), βCD–VC11( x , y ), γCD–VC11( x , y ), VC11(0.2, y ), γCD( x ), and pAAm hydrogels ( Fig. 2 ) were prepared by using conventional radical copolymerization in water (total monomer concentration C m = 2 mol kg −1 ), in which potassium dithionite (K 2 S 2 O 4 ) and N , N , N ′, N ′-tetramethyl ethylenediamine (TEMED) were used as redox initiators (Schemes S2–S7 and Tables S1–S6 † ). Three types of CD vinyl monomers with different sizes of CD cavities (α, β and γCDAAmMe, Scheme S1, Fig. S1 and S2 † ) were employed. 4-(11-Acryloyloxyundecyl)-4′-(methyl)-bipyridinium dichloride (the VC11 monomer) was prepared as the guest monomer (see the ESI † ). The radical copolymerization of acrylamide (AAm), γCDAAmMe and the VC11 monomer in an aqueous solution yielded γCD–VC11( x , y ) hydrogels. Fourier transform infrared (FT-IR) spectra of the γCD–VC11( x , y ) hydrogels exhibited the characteristic peaks of both the γCD and VC11 moieties (Fig. S9 † ). The number of γCD and VC11 units in the obtained hydrogels was determined by solid-state 1 H field gradient magic angle spinning (FGMAS) NMR measurements of the hydrogels (Fig. S12 † ). The other host–guest hydrogels in Fig. 1 were also characterized by spectroscopy (Fig. S9–S11 † ). In these gel-state FGMAS NMR spectra (Fig. S10–S12 † ), the integral values of each signal indicate that the obtained host–guest hydrogels contain 2 mol% of the CD and VC11 residues as prepared. The αCD–VC11(2,2) and βCD–VC11(2,2) hydrogels showed signals derived from the methylene protons in the VC11 unit at δ = 1.29 and 1.30 ppm, respectively. On the other hand, the corresponding signals in the γCD–VC11(2,2) hydrogel appeared at δ = 1.24 ppm (shifted to a higher magnetic field), suggesting that the methylene chains of the VC11 units in γCD–VC11(2,2) with the 1:2 host–guest complex are closely packed in the γCD cavity to show a higher shielding effect, compared to αCD–VC11(2,2) and βCD–VC11(2,2). In former reports, 48,49 the polymerization of a host–guest inclusion complex effectively introduces the complex into polymeric materials. The complex structure is maintained even in the polymeric materials. According to the previous studies, the CD–VC11 complexes should maintain the 1:1 or 1:2 host–guest complex structures even in the hydrogel states. 2.2. Deformation behaviours of the host–guest hydrogels \n Fig. 3 shows the deformation behaviours of the αCD–VC11(2,2), βCD–VC11(2,2), γCD–VC11(2,2) and VC11(0.2,2) hydrogels. After immersion in 0.5 M phosphate buffer (pH 7.0) with 0.1 M sodium dithionite (Na 2 S 2 O 4 ) as a reductant, the colour of the hydrogels changed from light yellow to deep purple ( Fig. 3a and S13 † ). This colour change indicates the formation of the radical cation species of the viologen moiety due to one-electron reduction. Fig. 3b shows the time-course of the volume change in the hydrogel in the reductant solution. The normalized lengths of the hydrogels ( r ) were determined by the ratio r = L t / L 0 ( L t , length of the hydrogel during the volume change; L 0 , length of the hydrogel in phosphate buffer before the reduction, which is the equilibrium state). The size of the CD–VC11(2,2) hydrogels was decreased by the reduction. The displacement and speed of the contraction were different depending on the cavity size of the CDs. The γCD–VC11(2,2) hydrogel showed a markedly larger volume change than the αCD–VC11(2,2), βCD–VC11(2,2), and VC11(0.2,2) hydrogels ( Fig. 3c ). The αCD–VC11(2,2) and βCD–VC11(2,2) hydrogels showed an increase of the r values at longer time ( t > 30 min). A change in osmotic equilibrium in the reducing reagents is supposed to contribute to an increase in the volume of the αCD–VC11(2,2) and βCD–VC11(2,2) hydrogels at t > 30 min. The other control samples, the γCD(2) and pAAm hydrogels, did not change their colour or volume at all. If only the change in the charge of viologens affected the equilibrium of the polymer network's form, the degree of the volume change should be the same irrespective of the cavity size of CDs. Therefore, the difference in the volume change ( Fig. 3d ) indicates that complex formation between the γCD and VC11 units plays some role in the deformation. Fig. 3 (a) Photographs of the γCD–VC11(2,2) hydrogel before and after immersion in 0.5 M phosphate buffer (pH 7.0) with Na 2 S 2 O 4 (0.1 M) as a reductant. (b) Time-course of the normalized length ( r ) of the αCD–VC11(2,2), βCD–VC11(2,2), γCD–VC11(2,2) and VC11(0.2,2) hydrogels during immersion in the reductant solution. The error bars were obtained through three experiments. (c) The change in the r values of the hydrogels immersed in the reductant solution for 90 min. (d) The proposed structure of the γCD–VC11( x , y ) hydrogel in a reduced state. Green line: the pAAm main chain in the polymer network. Green ring: γCD unit. Purple unit: the reduced viologen moiety in VC11. Grey line: the undecyl linker in VC11. The grey linker acts as a station where the host molecule stays. The reduced viologen units (purple) form a cationic dimer via cation–π interactions. The viologen dimer can be included by another γCD unit. UV-Vis absorption measurements on the hydrogels revealed the details about the state of the viologen unit during the reduction (Fig. S14 † ). In the oxidized state (initial state), the absorption band derived from the dicationic species of the viologen unit was observed at approximately 400–450 nm. After the reduction, other new bands at approximately 480–650 nm appeared, indicating a radical cation species. The radical cation's band can be divided into two absorption modes, which are derived from the radical cation monomer and its dimer (Fig. S15 † ). The molar ratio of the dimer in the hydrogels ([dimer]/([dimer] + [monomer])) was evaluated by waveform separation of the UV/Vis spectra. The order of the dimmer's molar fraction is γCD–VC11(2,2) hydrogel (85%) > αCD–VC11(2,2) hydrogel (75%) ≥ βCD–VC11(2,2) hydrogel (74%) > VC11(0.2,2) hydrogel (67%) (Table S7 † ). Moreover, the radical cation dimer of the γCD–VC11(2,2) hydrogel showed bimodal peaks (Fig. S15c † ), whereas the unimodal peak of the dimer was observed in the other hydrogels. The bimodal peaks in the γCD–VC11(2,2) hydrogel are derived from the dimers isolated in the solution and included in the γCD cavity, respectively. The wave separation analysis also indicates that 52% of viologens are included in the γCD cavity (Table S7 † ). These results indicate that the VC11 units in the γCD–VC11(2,2) hydrogel effectively form radical cation dimers in the reduction reaction. This finding coincides with the results of the stoichiometric study mentioned above. The γCD unit includes the two undecyl residues in the VC11 unit and should also form a stable double-threaded 1:2 inclusion complex with the oxidized viologen dimer in the VC11 units, leading to the formation of radical cation dimers of the viologen residues ( Fig. 3d ). These results suggest that this double-threaded structure contributes to a larger deformation of the γCD–VC11(2,2) hydrogel than the other hydrogels following the reduction. 2.3. Change in the mechanical properties of the host–guest hydrogels through redox reactions We investigated the reductive/oxidative state of the VC11 unit and the internal molecular state in the CD–VC11( x , y ) hydrogels. The reduced γCD–VC11(2,2) hydrogel was immersed in 0.5 M phosphate buffer (pH 7.0) with potassium nitrite (KNO 2 , 0.1 M) as an oxidant. The reduced γCD–VC11(2,2) hydrogel was restored to its initial transparent state (see Movie S1 † ), suggesting that the viologen unit returned to its original dicationic state ( Fig. 4a ). UV-Vis spectroscopy also supports the oxidation of the reduced viologen units (Fig. S16 † ). The UV/Vis absorption bands corresponding to the radical cation monomer and dimer in the reduced γCD–VC11(2,2) hydrogel disappeared after oxidation. In addition, the band of the dicationic species appeared again. Fig. 4 (a) Photographs of the γCD–VC11(2,2) gel [initial (upper left); after reduction (upper right); after oxidation (lower right)]. (b) Plot of the normalized length ( r ) of the γCD–VC11(2,2) and the βCD–Fc(3,3,1) hydrogels during redox cycling. The data of βCD–Fc(3,3,1) were newly obtained in this work to examine under the same redox conditions. (c) The results of the repeated redox cycling test of the αCD–VC11(2,2), βCD–VC11(2,2), and γCD–VC11(2,2) hydrogels. The r values are plotted based on the redox cycles. (d) Stress–strain curve of the γCD–VC11(2,2) hydrogel in compression tests (green line: the initial oxidized state; purple line: after treatment in reducing agent solution; yellow line: the oxidized hydrogel after the first reduction. The reduced γCD–VC11(2,2) hydrogel was treated with an oxidative reagent. At larger strain λ > 40%, the standard deviation of the stress value is >18%). (e) Repeated testing of the Young's modulus of the γCD–VC11(2,2) hydrogel over multiple reduction/oxidation cycles. The error bars were obtained through three experiments under the same conditions. The volume of the reduced γCD–VC11(2,2) hydrogel was also recovered to the volume of the hydrogel in its initial state by oxidation. Note that this contraction and expansion behaviour of the γCD–VC11(2,2) hydrogel is exactly the opposite of that of the βCD–Fc(3,3,1) hydrogel under the same redox conditions (the βCD–Fc(3,3,1) hydrogel was prepared by the same method in our previous work 30 ) ( Fig. 4b ). The volume of gels generally increases upon decreasing their cross-linking density. While the neutral Fc molecule is included by the βCD host with a high association constant K a = 17 000 M −1 , the oxidized monocationic Fc + shows a low affinity for βCD ( K a = 15 M −1 ) owing to the electric instability of the inclusion complex. 50–52 Thus, the addition of an oxidant to the inclusion complex of βCD with Fc results in the dissociation of the complex. A reductant leads to the reassociation of the complex. In the βCD–Fc(3,3,1) hydrogel, reduction/oxidation triggered association/dissociation between the βCD and Fc units, resulting in an increase/decrease in the cross-linking density. Therefore, after the oxidation of the Fc unit, the cross-linking density of the βCD–Fc(3,3,1) hydrogel decreased, leading to an increase in the volume. 30 On the other hand, the initial state of the γCD–VC11(2,2) hydrogel was the oxidative state. Through the reduction of the viologen unit, the cross-linking density of the γCD–VC11(2,2) hydrogel should increase, leading to a decrease in volume. The displacement of deformation in the γCD–VC11(2,2) hydrogel is two times higher than that in the βCD–Fc(3,3,1) hydrogel. Additionally, the γCD–VC11(2,2) hydrogel still showed a larger volume change than the βCD–Fc(3,3,1) hydrogel in third cycles ( Fig. 4b ). Although Fc is generally a stable molecule against oxidation, some acylated Fc was gradually decomposed with oxidation. 53 The smaller deformation through the repeated oxidation/reduction reaction was derived from the decomposition of the Fc unit in the βCD–Fc(3,3,1) hydrogel. The deformation process of the γCD–VC11(2,2) hydrogel is reversible over more than ten oxidation/reduction cycles without hysteresis ( Fig. 4c ), indicating that the use of a viologen induces superior reversibility to the βCD–Fc(3,3,1) hydrogel. The γCD–VC11(2,2) hydrogel maintained its purple colour in the reductant solution at least for a month. The reduced γCD–VC11(2,2) hydrogel was able to recover the original colourless transparent state by the oxidation. These results show the reversibility and stability of the γCD–VC11(2,2) hydrogel. Fig. 4c also shows the results of the αCD–VC11(2,2) and βCD–VC11(2,2) hydrogels, which showed much lower volume change compared with the γCD–VC11(2,2) hydrogel. These results indicate that the molecular design with 1:2 complex cross-linking is more effective to achieve large deformation than that with the 1:1 complex. We can clearly examine the change in the cross-linking density of the γCD–VC11(2,2) hydrogel in response to redox stimuli based on its Young's modulus. Fig. 4d shows the stress–strain curves, which were obtained by compression tests, of the γCD–VC11(2,2) hydrogel before and after reduction/oxidative reactions. After the reduction reaction, the stress of the γCD–VC11(2,2) hydrogel increased, and with the oxidation reaction, the stress of the reduced γCD–VC11(2,2) hydrogel under the same strain decreased. The stress decreased by another oxidation reaction. We calculated the Young's modulus as the initial gradients of these curves in the range between 1% and 10% strain. In a typical polymer network material, its cross-linking density (the number of entropic springs between the cross-linking points) is proportional to its Young's moduli. Fig. 4e shows the change in the Young's modulus of the γCD–VC11(2,2) hydrogel in response to redox stimuli. The reduction reaction increased the Young's modulus of the γCD–VC11(2,2) hydrogel, indicating an increase in the cross-linking density due to formation of a complex between the double-threaded structure and the radical cation dimer. The Young's modulus of the γCD–VC 11(2,2) hydrogel was restored with the dissociation of these complexes in response to oxidative stimuli. The change in the Young's modulus was observed over more than 5 reduction/oxidation cycles. These results supported our proposed scheme: the deformation behaviour is derived from changing the cross-linking density based on supramolecular complex formation between the CD and VC11 units. On the other hand, the Young's moduli of the αCD–VC11(2,2) and βCD–VC11(2,2) hydrogels before and after immersion in the reductant solution were comparable (Fig. S19 † ), although the Young's modulus of the VC11(0.2,2) hydrogel, which has no CD moiety, slightly increased after the reduction due to the formation of the radical cation dimer. These results support the large deformation of the γCD–VC11(2,2) hydrogel driven by the 2:1 inclusion complexation between the two VC11 moieties and the γCD unit with a large cavity size. 2.4. Mechanism of deformation of the host–guest hydrogels \n Fig. 5 shows a proposed mechanism for the deformation of the γCD–VC11( x , y ) hydrogels. In the oxidized state, the γCD moiety and two VC11 residues form a 1:2 inclusion complex to make the double-threaded structure, where γCD includes the two alkyl chains in the VC11 unit. The reduction of the viologen unit triggers the dimerization of the monocation radical of the viologen units through cation–π electrostatic interactions, which increases the cross-linking density of the polymer network. Furthermore, UV/Vis and NMR spectroscopies of the VC11 monomer support the formation of the monocationic viologen radical dimer included in the γCD cavity (Fig. S17 and S18 † ). This inclusion behaviour between the cation dimer and γCD contributes to the formation of additional cross-linking points ( Fig. 5 ). The 1:2 inclusion complexes of γCD and viologen monocation dimer connect the original cross-linking points to make a supramolecular cascade structure. The molar ratios of the viologens in the γCD–VC11(2,2) hydrogel are x monomer = 15%, x dimer = 33%, and x CD-dimer = 52% (Fig. S15 and Table S7 † ), indicating that average number of viologen dimers is 5.7, and that of CD units in the single cascade structure is 10.3 ( Fig. 5 ). Thus, the γCD–VC11( x , y ) hydrogel should show a larger displacement of deformation than the other hydrogels. As these processes occurring via the reduction/oxidation of the viologen residues are reversible, the hydrogel can show repeated deformation more than ten times. The large Young's moduli change of the γCD–VC11( x , y ) hydrogels (Fig. S19 † ) also supports that the large deformation of the hydrogel is driven by the 2:1 inclusion complexation between the two VC11 moieties and the γCD unit. The αCD–VC11(2,2) and βCD–VC11(2,2) hydrogels did not show such change in the Young's moduli. Fig. 5 The proposed mechanism of the association/dissociation behaviours in the γCD–VC11( x , y ) hydrogels leading to large volume changes. Green line: the pAAm main chain in the polymer network. Green ring: γCD unit. Yellow unit: the oxidized viologen moiety in VC11. Purple unit: the reduced viologen moiety in VC11. Grey line: the undecyl linker in VC11. The reduced monocation radical viologen unit (purple) can form a stacked dimer structure via cation–π electrostatic interactions. The viologen dimer is able to be included by another γCD unit to make a new cross-linking point. These two types of host–guest interactions result in the formation of supramolecular cross-linking, which contributes to the large deformation of the γCD–VC11(2,2) hydrogel. The x monomer , x dimer , x CD-dimer values in Table S7 † indicate the number of inclusion complexes in the supramolecular cross-linking, where 5.7 viologen dimers are formed in the single supramolecular cross-linking. 10.3 inclusion complexes of γCD with the undecyl units or with the viologen dimers are connected to form a supramolecular cascade structure. In the case of αCD–VC11(2,2) and βCD–VC11(2,2) hydrogels, the αCD or βCD unit and the undecyl moiety in VC11 form a 1:1 inclusion complex that functions as a cross-linking point between the polymer chains. However, this 1:1 inclusion complex does not contribute to the formation of radical cation dimers, even in the presence of a reducing agent, because the αCD and βCD units do not largely promote the formation of the radical cationic dimer due to steric hindrance (αCD and βCD with small cavities are not able to include to stabilize the radical cationic dimer). Therefore, the αCD–VC11(2,2) and βCD–VC11(2,2) hydrogels did not show the cross-linking formation with radical cationic dimers of the viologen units. This is one of the reasons that unlike the γCD–VC11(2,2) hydrogel, the αCD–VC11(2,2) and βCD–VC11(2,2) hydrogels did not exhibit large deformations. Different swelling mechanisms of the αCD–VC11(2,2), βCD–VC11(2,2), and γCD–VC11(2,2) hydrogels were expected based on the Young's modulus. We defined the degree of change in the Young's modulus f = E reduction / E initial , and degree of change in the volume φ = φ reduction / φ initial , respectively (Fig. S20 † ). The f values of the αCD–VC11(2,2) and βCD–VC11(2,2) hydrogels almost did not change at all during the oxidation. On the other hand, the f value of the 1:2 inclusion complex hydrogel significantly increased as the φ value increased during the oxidation, indicating that the swelling mechanism of the γCD–VC11( x , y ) hydrogel was different from that of the αCD–VC11( x , y ) and βCD–VC11( x , y ) hydrogels. The two kinds of association and dissociation behaviours of the double-threaded 2:1 complex (γCD with the alkyl chain of VC11 and γCD with the reduced viologen dimer) form cross-linked structures consisting of the supramolecular polymers ( Fig. 5 ), resulting in a large change in the f value. Dynamic mechanical measurements (DMA) support the association–dissociation behaviours of the double-threaded dimer and the radical cation dimer, which were observed by using a dynamic shear rheometer (Fig. S21 and Table S8 † ). Some relaxation modes with relaxation time ( τ ) were observed in the hydrogels. In the reduced initial state, the VC11(0.2,2) hydrogel showed a very short shear relaxation time ( τ < 10 −3 ), indicating that there is no cross-linking mode within the frequency range in the DMA measurement. The τ values of the αCD–VC11(2,2), βCD–VC11(2,2), and γCD–VC11(2,2) hydrogels are 4000, 0.16, and 0.10 s, respectively. The relaxation modes are derived from threading movement of the CD ring onto the VC11 unit in the hydrogels. In particular, the very long relaxation time of the αCD–VC11(2,2) hydrogels is contributed by the electric trap effect of the viologen because of the narrow αCD cavity. 46 The higher G ′ value of the αCD–VC11(2,2) hydrogels than those of βCD–VC11(2,2), and γCD–VC11(2,2) hydrogels also agrees with these analyses. The reductant decreased the relaxation times of the αCD–VC11(2,2) and βCD–VC11(2,2) hydrogels, indicating that αCD and βCD move faster through the reduced monocationic viologen barrier than through the oxidized dicationic viologen barrier. In contrast, the τ value of the γCD–VC11(2,2) hydrogel increased with the reduction, suggesting that a new cross-linking mode appears in the reduced γCD–VC11(2,2) hydrogel. The inclusion complex of γCD with a radical cation dimer is supposed to prevent the threading and dethreading motion of the inclusion complexes. Thus, only the γCD–VC11(2,2) hydrogel network should form a kinetically stable supramolecular cross-linking structure in response to reducing stimuli ( Fig. 5 ). This structural change should enable the γCD–VC11(2,2) hydrogel to show a larger deformation than the αCD–VC11(2,2) and βCD–VC11(2,2) hydrogels. 2.5. Energy conversion by the host–guest hydrogels We evaluated the mechanical work done by the chemical reactions of the γCD–VC11(2,2) hydrogel and the control hydrogels. We compared the γCD–VC11(2,2) hydrogel (supramolecular host–guest hydrogel) and the VC11(0.2,2) hydrogel (chemically cross-linked hydrogel) ( Fig. 6c ) and investigated the redox responsiveness of the γCD–VC11(2,2) hydrogel ( Fig. 6d ), the relationship between the thickness of the hydrogel and the deformation rate ( Fig. 6e ), and the relationship between the mechanical work and the ratio of γCD–VC11 units introduced into the hydrogels ( Fig. 6f ). Fig. 6 (a) Schematic illustration of hydrogel actuation with a weight (422 mg) through the reduction reaction. “ x ” is the displacement of the lifted weight. (b) Photographs of the γCD–VC11(2,2) hydrogel responding to redox stimuli for 15 min. Scale bar indicates 10 mm. (c) Plot of the normalized position of the weight versus the immersion time in the case of γCD–VC11(2,2) and VC11(0.2,2) hydrogels (0.05 mm (thickness) × 5 mm (width) × 10 mm (length)) with the same weight (422 mg). (d) Plot of the normalized position of the weight versus the immersion time in the case of the γCD–VC11(5,5) hydrogel (0.05 mm (thickness) × 5 mm (width) × 10 mm (length)) responding to redox stimuli. (e) The relationship between the deformation rate and the thickness of the γCD–VC11(2,2) hydrogel. The red circles indicate the results for the γCD–VC11(2,2) hydrogel with a thickness of 0.5 mm, and the blue circles indicates the results for the γCD–VC11(2,2) hydrogel with a thickness of 0.05 mm and the same width and length (5 mm (width) × 10 mm (length)). (f) The relationship between the work performed in the deformation of the hydrogels per volume ( W ) and the mol% contents of the host/guest units in the γCD–VC11( x , y ) hydrogel and the control hydrogels. \n Fig. 6a shows the experimental setup used to analyse the energy conversion from chemical energy to mechanical work. A weight (422 mg) is hung at the bottom end of rectangular hydrogels (0.5 mm (thickness) × 5 mm (width) × 10 mm (length)). The hydrogel was immersed in 0.5 M phosphate buffer (pH 7.0) containing Na 2 S 2 O 4 (0.10 M) as a reductant. To observe the reverse deformation, the hydrogel was subsequently immersed in 0.50 M phosphate buffer (pH 7.0) with KNO 2 (0.10 M) as an oxidant. In the case of the γCD–VC11(2,2) hydrogel, the hydrogel was contracted by the reductant, vertically lifting the weight up. The reduced γCD–VC11(2,2) hydrogel was expanded by the oxidant, which restored the original position of the weight ( Fig. 6b, d and Movie S1 † ). In comparison with the γCD–VC11(2,2) hydrogel, the VC11(0.2,2) hydrogel showed a smaller change in the normalized position of the weight per unit time ( Fig. 6c ). The initial slope of the displacement, which was calculated by fitting a nonlinear curve to the data, indicates that the γCD–VC11(2,2) hydrogel shows 10 times faster deformation (3.3% min −1 ) than the VC11(0.2,2) hydrogel (0.27% min −1 ). These behaviours were in agreement with the degree of volume change in each hydrogel, as described above. Fig. 6d shows the time-course of the normalized position of the weight hung on the γCD–VC11(5,5) hydrogel in response to redox stimuli. The displacement of the weight increased with the reduction reaction within 4 minutes. Subsequently, the oxidation reaction completely returned the weight to its initial position in 7 minutes. The deformation rate of the γCD–VC11( x , y ) hydrogel was closely related to the thickness of the hydrogel. Fig. 6e shows the thickness dependence of the deformation of the γCD–VC11(2,2) hydrogels (thickness: 0.5 mm or 0.05 mm). The width and length of each hydrogel are the same (5 mm (width) × 10 mm (length)). Nonlinear least-squares curve fitting revealed that the initial deformation rate of the γCD–VC11(2,2) hydrogel sample with 0.05 mm thickness was 57% min −1 , which is eleven times faster than that of the γCD–VC11(2,2) hydrogel sample with 0.5 mm thickness (4.9% min −1 ). The mechanical work was determined by using the equation W = ( m − ρV ) gx ( m : mass of the weight 422 mg, ρ : density of the buffer 1007 kg m −3 , V : volume of the weight 48 μL, g : acceleration of gravity 9.80665 m s −2 , and x : length of the weight that was lifted). The energy conversion of the γCD–VC11( x , y ) hydrogel was calculated to be 0.92% based on the W value and sum of the redox potential of the viologen units (Δ G = −0.4 V) in the γCD–VC11( x , y ) hydrogel. Fig. 6f shows the W values of the γCD–VC11( x , y ) hydrogels and the control hydrogels per volume. The W of the γCD–VC11( x , y ) hydrogel increased with the mol% content of the γCD and VC11 moieties. Moreover, among the hydrogels tested, the γCD–VC11(5,5) hydrogel showed the largest W value, indicating that the energy conversion of the γCD–VC11( x , y ) hydrogel depends on the molar content of the VC11 unit. In addition, the W of the γCD–VC11(2,2) hydrogel was 1.8 times higher than that of the VC11(0.2,2) hydrogel. Notably, the W value of the γCD–VC11(3,3) hydrogel is also 7.4 times higher than that of the βCD–Fc(3,3,1) hydrogel in our previous work. 30 These results show that the formation of the complex between the double-threaded structure and the radical cation dimer contributes to the large deformation and work done by the γCD–VC11( x , y ) hydrogel. Work rates are also estimated from the initial slope values of Fig. 6c . The γCD–VC11(2,2) hydrogel shows a power P = 470 mW m −3 , which is 10 times higher than that of the control VC11(0.2,2) hydrogel ( P = 48 mW m −3 ). These results indicate that the design of 1:2 complexation is useful not only for the displacement but also the rate of deformation. The polymeric design of the γCD–VC11 hydrogel supports the superiority of its deformation ability in response to redox stimuli."
} | 9,341 |
36467305 | null | s2 | 8,011 | {
"abstract": "Native tissues orchestrate their functions by complex interdependent cascades of biochemical and biophysical cues that vary spatially and temporally during cellular processes. Scaffolds with well-tuned structural, mechanical, and biochemical properties have been developed to guide cell behavior and provide insight on cell-matrix interaction. However, static scaffolds very often fail to mimic the dynamicity of native extracellular matrices. Stimuli-responsive scaffolds have emerged as powerful platforms that capture vital features of native tissues owing to their ability to change chemical and physical properties in response to cytocompatible stimuli, thus enabling on-demand manipulation of cell microenvironment. The vast expansion in biorthogonal chemistries and stimuli-responsive functionalities has fuelled further the development of new smart scaffolds that can permit multiple irreversible or reversible spatiotemporal modulation of cell-directing cues, thereby prompting in-depth studies to interpret the decisive elements that regulate cell behavior. Integration of stimuli-responsive hydrogels with current biofabrication technologies has allowed the development of dynamic scaffolds with organizational features and hierarchical architectures similar to native tissues. This review highlights the progress achieved using stimuli-responsive hydrogels in fundamental cell biology studies, with particular emphasis on the interplay between chemistry, biomaterials design, and biofabrication technologies for manipulation of cell microenvironment."
} | 390 |
27540078 | PMC4991723 | pmc | 8,012 | {
"abstract": "Desulfotomaculum copahuensis strain CINDEFI1 is a novel spore-forming sulfate-reducing bacterium isolated from the Copahue volcano area, Argentina. Here, we present its draft genome in which we found genes related with the anaerobic respiration of sulfur compounds similar to those present in the Copahue environment."
} | 79 |
26861307 | PMC4783879 | pmc | 8,013 | {
"abstract": "Marine macroalgae (green, red and brown macroalgae) have attracted attention as an alternative source of renewable biomass for producing both fuels and chemicals due to their high content of suitable carbohydrates and to their advantages over terrestrial biomass. However, except for green macroalgae, which contain relatively easily-fermentable glucans as their major carbohydrates, practical utilization of red and brown macroalgae has been regarded as difficult due to the major carbohydrates (alginate and mannitol of brown macroalgae and 3,6-anhydro- l -galactose of red macroalgae) not being easily fermentable. Recently, several key biotechnologies using microbes have been developed enabling utilization of these brown and red macroalgal carbohydrates as carbon sources for the production of fuels (ethanol). In this review, we focus on these recent developments with emphasis on microbiological biotechnologies.",
"conclusion": "4. Conclusions and Perspectives Just a decade ago, it was difficult to convert brown and red algal carbohydrates into ethanol. However, this is now possible due to the development of several key biotechnologies as reviewed here ( Table 5 ). Utilization of agaropectin and carrageenan are not yet possible, and additional research is needed to utilize not only these substrates, but also alginate (or DEH), mannitol and agarose (or AHG). Improvement in the utilization of DEH, mannitol and AHG undoubtedly should be possible as demonstrated by the improvement of the utilization of galactose in S. cerevisiae . Expression and secretion of exo-type alginate lyase in bioengineered S. cerevisiae is awaited to utilize alginate directly. The method for utilizing glucan, which has been intensively studied for the utilization of terrestrial cellulosic biomass (e.g., [ 86 ]), should be integrated into the system described here to comprehensively convert macroalgal carbohydrates into ethanol. Moreover, additional challenges exist for the establishment of a practical system of ethanol production from macroalgae and include overcoming the problems as to where to cultivate macroalgae, how to collect them, how to get carbohydrates from them, how to saccharify some of the carbohydrates (alginate, agar and carrageenan), how to optimize the reaction to produce ethanol, how to scale-up, etc. Economical relevance is also a critical matter. Thus, there are many problems to overcome in order to achieve practical utilization of macroalgae. However, taking the advantages of macroalgae over terrestrial biomass into consideration, macroalgae are still a very promising alternative biomass, and further development of the key biotechnologies to utilize macroalgae is expected. ijms-17-00145-t005_Table 5 Table 5 Summary of the ethanol production in this review. Strains Concentration of Sugars in the Medium Concentration of Ethanol Produced Reference Z. palmae 38 g·L −1 of mannitol 12 g·L −1 [ 15 ] P. angophorae 40 g·L −1 of mannitol 14.4 g·L −1 [ 22 ] E. coli KO11 75 g·L −1 of mannitol 25.8 g·L −1 [ 24 ] S. paradoxus NBRC 0259-3 100 g·L −1 of mannitol 45 g·L −1 [ 25 ] S. cerevisiae MK4416 100 g·L −1 of mannitol 40 g·L −1 [ 21 ] Bioengineered Sphingomonas sp. A1 (50 g + 10 g)·L −1 of sodium alginate 13 g·L −1 [ 37 ] Bioengineered E. coli BAL1611 50 g·L −1 of a sugar mixture (alginate, mannitol, and glucose at a ratio of 5:8:1) 20 g·L −1 [ 18 , 48 ] Bioengineered E. coli BAL1611 130 g·L −1 of dry milled brown macroalgae ( L. japonica , kombu) 35–41 g·L −1 [ 18 , 48 ] Bioengineered S. cerevisiae BAL3215 98 g·L −1 of sugar (1:2 molar ratio of DEH:mannitol) 36.2 g·L −1 [ 20 ] Bioengineered E. coli KO11 3.2 g·L −1 of AHG and 4.1 g·L −1 of galactose 1.4 g·L −1 [ 64 ]",
"introduction": "1. Introduction Based on the medium variant projection, the world population of 7.2 billion in mid-2013 is projected to reach 8.1 billion in 2025 and 9.6 billion in 2050 [ 1 ]. Thus, the need for research in alternative renewable energy sources is growing each year. Among renewable energy sources, biomass is the only energy source capable of producing liquid fuels [ 2 ]. Macroalgae have attracted attention as an alternative source of biomass for the production of both fuels and chemicals. The advantages of macroalgae compared to that of terrestrial biomass includes no requirements for arable land, freshwater, agricultural fertilizer and pesticides. In addition, algae biomass is also relatively easy to extract carbohydrate from, due to the presence of little or no lignin, and has high productivity, and there is little concern for competition with agricultural food and feed crops [ 2 , 3 , 4 ]. Macroalgae consist of green, red and brown macroalgae. Green macroalgae contain glucans (a polymer of glucose, i.e. , cellulose and starch) and sulfated polysaccharides (e.g., ulvan). Red macroalgae contain agar (agarose and agaropectin), carrageenan and glucans. Brown macroalgae contain mannitol, alginate and glucans (cellulose and laminarin) [ 3 ]. The contents of glucan based on a dry weight basis in green, red and brown macroalgae are 22% ( Ulva pertusa ), 21.8% ( Gelidium elegans ) and 24.5% ( Alaria crassifolia ), respectively [ 5 ]. The macroalgae content of glucan is lower than that in wood (aspen), 45.6% [ 6 ], wheat straw, 31.5% [ 7 ], and corn stover, 39.5% [ 8 ]. However, the content of the other carbohydrates in red and brown macroalgae is higher as described below. The world production (33 countries) of captured and farmed algae in 2012 is 1.1 million and 23.8 million wet tonnes (tonne = a metric ton, 1000 kilograms), respectively. A few Asian countries dominate the farmed algae production accounting for 96.27% of the total ( Table 1 ) [ 9 ]. ijms-17-00145-t001_Table 1 Table 1 Percentage of global farmed algae production. Country % China 53.97 Indonesia 27.40 Philippines 7.36 Korea 4.30 Japan 1.85 Malaysia 1.39 Total 96.27 Farmed algae can be categorized into seven groups ( Table 2 ) [ 9 ]. These data show that there has been a rapid increase in the dominance of Eucheuma red algae farmed in both tropical and subtropical seawater that is used for carrageenan extraction [ 9 ]. Collectively, the major portion of farmed macroalgae is brown and red macroalgae. Since these macroalgae are farmed in Asian countries, a possibility remains that much more macroalgae can be farmed in other countries, including non-Asian countries. Improvement in the farming technology may increase the productivity of macroalgae. Thus, macroalgae, in particular red and brown macroalgae, are undoubtedly a promising renewable energy source capable of producing both liquid fuels and chemicals. ijms-17-00145-t002_Table 2 Table 2 Categorization of the farmed algae. The Farmed Algae Million Wet Tonnes Eucheuma red algae 8.30 Japanese kelp (brown algae, Laminaria japonica ) 5.65 Seaweed species not identified 2.75 Gracilaria spp. (red algae) 2.75 Wakame (brown algae, Undaria pinnatifida ) 2.10 Porphyra spp. (red algae) 1.75 Other seaweeds and microalgae 1.75 Total 25.50 Attempts to produce a high concentration of ethanol (one of the biofuels) from macroalgae have been reviewed [ 3 ]. In that review, it was concluded that a conversion of macroalgal glucan into ethanol is apparently not enough, and a conversion of the other carbohydrates (mannitol, alginate, agarose, agaropectin, carrageenan, etc. ) derived from both brown and red macroalgae into ethanol is needed to achieve a high concentration of ethanol [ 3 ]. Although it had been regarded as difficult to convert these brown and red algal carbohydrates into ethanol, recent advances in biotechnology have made it not difficult, as also reviewed recently [ 10 ]. However, several developments have been achieved after those reviews were published, and thus, in this review, we further overview this field including the latest developments with emphasis on microbiological biotechnologies."
} | 1,975 |
24028946 | null | s2 | 8,014 | {
"abstract": "Social transmission of information is vital for many group-living animals, allowing coordination of motion and effective response to complex environments. Revealing the interaction networks underlying information flow within these groups is a central challenge. Previous work has modeled interactions between individuals based directly on their relative spatial positions: each individual is considered to interact with all neighbors within a fixed distance (metric range), a fixed number of nearest neighbors (topological range), a 'shell' of near neighbors (Voronoi range), or some combination (Figure 1A). However, conclusive evidence to support these assumptions is lacking. Here, we employ a novel approach that considers individual movement decisions to be based explicitly on the sensory information available to the organism. In other words, we consider that while spatial relations do inform interactions between individuals, they do so indirectly, through individuals' detection of sensory cues. We reconstruct computationally the visual field of each individual throughout experiments designed to investigate information propagation within fish schools (golden shiners, Notemigonus crysoleucas). Explicitly considering visual sensing allows us to more accurately predict the propagation of behavioral change in these groups during leadership events. Furthermore, we find that structural properties of visual interaction networks differ markedly from those of metric and topological counterparts, suggesting that previous assumptions may not appropriately reflect information flow in animal groups."
} | 402 |
23624511 | PMC3638166 | pmc | 8,015 | {
"abstract": "In the Red Sea, two neighboring deep-sea brine pools, Atlantis II and Discovery, have been studied extensively, and the results have shown that the temperature and concentrations of metal and methane in Atlantis II have increased over the past decades. Therefore, we investigated changes in the microbial community and metabolic pathways. Here, we compared the metagenomes of the two pools to each other and to those of deep-sea water samples. Archaea were generally absent in the Atlantis II metagenome; Bacteria in the metagenome were typically heterotrophic and depended on aromatic compounds and other extracellular organic carbon compounds as indicated by enrichment of the related metabolic pathways. In contrast, autotrophic Archaea capable of CO 2 fixation and methane oxidation were identified in Discovery but not in Atlantis II. Our results suggest that hydrothermal conditions and metal precipitation in the Atlantis II pool have resulted in elimination of the autotrophic community and methanogens.",
"discussion": "Discussion In the present study, brine pool metagenomes in the Red Sea were analyzed and compared with deep-sea water metagenomes. The results revealed drastic differences in the composition of the communities and metabolic spectra between the brine pool metagenomes. Although the two metagenomes have been compared in our previous work, only aromatic-degrading bacteria and metabolic pathways were examined to document the presence of aromatic compounds in the Atlantis II brine pool 15 . The current study elaborates on how the two brine pool ecosystems can be further differentiated via a comprehensive comparison of the microbial communities and their potential functions. In particular, we revealed archaeal taxa and metabolic pathways that have not been previously observed 15 . The samples from adjacent brine pools revealed that our two brine metagenomes differed even more remarkably than the deep-sea reference metagenomes sampled at widely separate sites and could not be grouped due to their high level of dissimilarity. Considering the historical connection of the two brine pools 8 , the ecosystem in the Discovery brine pool might have been similar to that in the Atlantis II in the past. The present physical separation likely resulted in decrease in volume of the two brine pools, which has been reported in previous studies 9 . After the separation of the two brine pools, the exposure of Atlantis II to increasingly strong geothermal activities on the sea floor probably changed the original environment of Atlantis II. For example, in ABP, we did not find methanogens, AOM Archaea or other autotrophic microbes, which were present in DBP. The apparent absence of chemoautotrophic microbes in ABP might have completely converted the mode of life in this pool to heterotrophy. The present study provides evidence that microbes in ABP depended heavily on extracellular organic carbon, including aromatic compounds, non-aromatic heterocyclic compounds, amino acids, storage sugars and structural sugars in the surrounding water. Overall, conditions in the present lower convective layer of Atlantis II brine pool have selected against archaeal autotrophic and methanogenic inhabitants, while imposed minor effects on the bacterial residents. However, the elimination of these autotrophic inhabitants was probably not as extreme as demonstrated in this study. Considering the low cell density in the ABP sample, sampling drift and the experimental approach could have influenced our results. Crenarchaeotic marine group I (1.7%), Methanomicrobia (0.07%), Halobacteria (0.08%) and Archaeoglobi (0.15%) were detected in the lower convective layer of Atlantis II in an independent study (unpublished data). However, diversified archaeal groups were detected in the subsuperficial sediments of ABP by Siam et al. (2012) 30 ; however, their proportion in the whole community was not determined. In the same report, Archaea were also identified in DBP sediment samples, whereas Crenarchaeota dominated the archaeal communities rather than Euryarchaeota, which consisted of the overwhelming majority of Archaea in the overlying brine in the present study. The differences between the two studies may be a consequence of environmental changes in the sediments. Although more Archaea can probably be identified in Atlantis II, it is clear that the archaeal community in that pool has drastically diminished relative to that in the Discovery brine pool, potentially to the edge of extinction. A considerable fraction of the archaeal community in DBP was believed to be capable of fixing CO 2 , but these representatives were almost absent from ABP. This difference might be explained by CO 2 limitations in ABP. Although in situ CO 2 concentration in the Atlantis II brine pool was not measured, a body of evidence from the following geochemical analyses of brine water and sediments has suggested a very low CO 2 concentration in Atlantis II. In several sediment cores, manganosiderite minerals were much more abundant in Atlantis II than in all of the other brine pool sediments in the Red Sea 1 . These minerals were formed by the interaction of Fe 2+ and Mn 2+ ions with CO 2 . The sources of CO 2 could be the hydrothermal fluids and biogenic CaCO 3 that dissolved in the brines at low pH values 1 . However, in such a scenario, almost all the CO 2 would be accepted rapidly by Mn and Fe ions that are injected into the brine pool via geochemical activities. Concentrations of Mn and Fe ions in the lower convective layer of the Atlantis II brine pool were much higher (Fe, 120×; Mn, 28×) than those in Discovery (Ref. 1 and our unpublished data). CO 2 in the lower layer of the Atlantis II could be easily fixed by the large amount of Mn and Fe ions and precipitated as manganosiderite in the sediments. Therefore, deprivation of CO 2 by metal ions limited CO 2 -dependent autotrophy, particularly for the archaeal groups as indicated in the present study. In contrast, CO 2 fixation might also be conducted by bacteria such as Cupriavidus , Salinibacter and Meiothermus ; however, the latter two genera were not found in ABP, perhaps because the extreme environment of the Atlantis II pool inhibited their colonization. This finding might also partially explained by the compositional differences in the bacterial communities between brine metagenomes at the phylum level because Meiothermus and Salinibacter represent Deinococcus-Thermus and Bacteroidetes/Chlorobigroup, respectively. Hence, the CO 2 limitation in Atlantis II likely also accounted for the elimination of CO 2 autotrophic Archaea and some bacterial inhabitants. Regarding Cupriavidus spp. in ABP, the question is whether the involved genes were present to fix CO 2 or to function in the reverse direction. These genes play a role in several different metabolic pathways. It is also a possibility that the genes were not expressed under low CO 2 concentrations. Furthermore, Cupriavidus can degrade aromatic compounds 31 , and thus, their life mode might be heterotrophic in Atlantis II where organic maturation continues to occur 15 . The major role of Cupriavidus in Atlantis II was probably metal precipitation, as it is well known that Cupriavidus spp. are capable of precipitating different metal ions 32 33 . CO 2 fixation was also reported in a recent metagenomic study examining a Mediterranean deep-sea brine lake (DHAL) 34 . DBP and DHAL brine samples shared some taxonomic microbial assemblages such as Firmicutes and Gammaproteobacteria. Moreover, almost all types (CBB, cTCA and cACA) of CO 2 fixation uncovered in this study were performed by Euryarchaeota and Gammaproteobacteria present in the DHAL brine sample (a phosphoenolpyruvate-related type of CO 2 fixation was not described) 34 . However, the presence of CO 2 autotrophic Crenarchaeota in DBP is an important difference between these two deep-sea brine pools. High concentrations of methane derived from hydrothermal fluids have been reported for the Atlantis II pool 13 35 . In such an environment, methane is normally consumed by AOM from the ANME3 group, which uses manganese oxide as an oxygen donor 36 . Because Discovery pool may be less disturbed by hydrothermal fluids, manganese oxides could be maintained at the sub-floor and likely be supplied by those manganese oxides generated in Atlantis II that spread into Discovery via deep-sea water circulation around the Chain brine pool (refer to the deep-sea water channel in Fig. 1 ). As a result, the lower convective layer of Discovery could support the rapid assimilation of methane by ANME3, thus explaining the presence of ANME3 methanotrophic Archaea in DBP. The case differs in Atlantis II, where manganese ions are still oxidized at the interface between the deep-sea water and the brine pool 1 . Manganese oxides then transfer the oxygen to ferrous ions in the upper convective layer, especially at the boundary between the lower and upper brine layers of the brine pool 1 , resulting in the large-scale precipitation of ferrous oxides rather than manganese oxides to the sub-floor. There is evidence that Mn-hydroxides do not accumulate at the bottom of this pool as they do in Discovery, but rather, they have fallen to the slopes around the interface along the periphery of the Atlantis II brine pool and even in Discovery 1 . Hence, methane oxidation by ANME3 might occur at the interface of the Atlantis II pool and the seawater. As expected, mcrA sequences identical to those of ANME3 in DBP had been successfully cloned using the water sample collected from the interface of Atlantis II (unpublished data). Although Fe hydroxide also can be potentially used for methane oxidation by ANME3, Mn hydroxide is preferred due to its five-fold higher potential for free energy gain 36 . Therefore, the interface between the Atlantis II brine pool and the deep-sea water was found to be a better niche for ANME3. In addition, a novel branch was identified in our phylogenetic tree. Because no mcrA cloning sequences clustered with the known methanogens, they were likely derived from methanogenic Archaea. Without additional evidence, however, their role in ABP remains unclear. However, methane can be consumed by methanotrophic microbes that possess monooxygenase (encoded by the pmo and mmo genes) 37 . We used monooxygenase proteins to search for possible homologs in the four metagenomes. Positive results (BLAST cutoff score of 100) were obtained only for the CAM metagenome, in which uncultured crenarchaeota and methanotrophic bacteria (Methylococcaceae) were candidates for the consumption of methane under aerobic conditions. A high expression level of pmo genes was confirmed in a recent metatranscriptomic study of a seawater sample from the Carmen Basin, Gulf of California 20 . The presence of aromatic compounds in the lower convective layer of Atlantis II has been reported in our previous work 15 . In theory, the increasing temperature in the Atlantis II brine pool has converted organic carbons into aromatic compounds 15 . The change in carbon sources under high temperatures can affect microbial communities and metabolic activities dramatically. Aromatic compounds have seldom been reported as carbon sources for Archaea. For methanogens, alkanes, acetate and volatile fatty acids are typically used to produce methane 38 39 40 . If the methanogens were the original inhabitants of Atlantis II, sufficient labile carbon was not easy to access in the lower convective layer. Therefore, the exclusion of archaeal methanogens is likely ascribed to the conversion of organic carbon into aromatic compounds. This would also have limited the diversity of the bacterial communities because only those capable of degrading aromatic compounds could proliferate in the lower convective layer of Atlantis II. We have argued that carbon sources contributed to the compositional shift in ABP. Environmental stresses imposed by chemocline, thermocline, halocline and heavy metal content could have greatly impacted the microbes. To cope with chemocline and thermocline, microbes may employ chemotactic mechanisms to sense surrounding environmental changes; Bacteria and Archaea can react to changes in chemical factors by switching their motility, speed and the direction of their flagella 41 . ABP possessed a greater number of chemotactic genes; for example, it had four times more mcp (methyl-accepting chemotaxis protein) genes compared with DBP. More detailed comparisons between ABP and DBP with respect to chemotactic genes and pathways have been reported in our previous work 15 . Surprisingly, in the current study, related pathways for flagellar assembly and bacterial chemotaxis demonstrated greater enrichment in MED than in all of the other metagenomes evaluated. The significant enrichment for the chemotaxis in MED was considered to be an adaptation to the extreme lack of nutrients in Mediterranean deep-sea water (Ref. 19 and references therein). One may argue that the pursuit of nutrients is even more important than the stresses imposed by chemocline and thermocline in the lower convective layer of the Atlantis II pool. Perhaps, the enrichment of chemotactic genes in ABP relative to DBP was also due to a shortage in the nutrient supply. Two approaches, via the NADH:ubiquinone Na + antiporter and the multi-subunit Na + /H + antiporter, were discovered in the four metagenomes. First, multi-subunit Na + /H + antiporter genes were significantly enriched in both of the brine metagenomes. Because the salinity of the sampling sites in the brine pools was much higher than that in the deep-sea waters (34.6‰ for CAM and 38.7‰ for MED), the multi-subunit Na + /H + antiporter approach likely played a more important role in microbial adaptation to extreme salinity. Second, the comparison between the two brine metagenomes revealed that both antiporters were more strongly represented by the reads in DBP. Despite the same salinity at the two sites, this result suggested that microbes in DBP, surprisingly, possessed more Na + transporter genes than did those in ABP. The NADH:ubiquinone Na + antiporter is the dedicated Na + pump in many aerobic bacteria 42 . As expected, this pump was significantly enriched in the deep-sea water metagenomes in the present study, as compared with ABP and DBP. The pumping process is supposed to be coupled to the strong oxidative phosphorylation that occurs in deep-sea water metagenomes and, therefore, to serve as an adaptive strategy in oxic seawater environments. Furthermore, a large number of ATPs generated by the oxidative phosphorylation process could drive various biosynthetic activities, thus explaining the enrichment of biosynthesis genes in deep-sea water metagenomes. Considering the ongoing strong metal precipitation activities 1 , the Atlantis II brine pool imposes a stronger impact on microbial inhabitants that are exposed to a large amount of metal ions and a higher temperature, compared with those present in the Discovery. However, in DBP, we identified more metal ion pumps for cobalt, nickel, manganese and iron, which suggests that these metal transport processes are important for the microbes in DBP. In addition, there was a lack of a correspondingly high abundance of metal transporter genes in ABP, although manganese and iron were the major types of metal ions present in the lower convective layer of Atlantis II 1 . The microbes in ABP elected energy-saving mechanisms, likely because these pumps are energy-dependent ABC transporters. This phenomenon was exemplified by a two-component copper transport system encoded by the cus operon that had significantly more genes in ABP than in DBP. Most of the adaptive mechanisms discussed above may explain the adaption observed for the microbes in DBP. However, the mechanism by which microbes adapted to the complex and extreme conditions in the Atlantis II brine pool remains unclear. To address this issue, the enriched pathways in ABP were further examined, and their possible adaptive roles were explored. Transcriptional regulators were clearly important for a rapid response to the fluctuation of variant factors in the Atlantis II brine pool. The enrichment of genes for secretion systems IV and VI in ABP also suggested a potentially important mechanism. Six types of secretion systems have been identified thus far 43 . The secretion system IV has been recently reported in thermophilic bacteria and is thought to govern the transfer of DNA and protein between cells 44 . Because our conclusions are based on analyses of metagenomes from a small volume of brine water, further transcriptomic studies are required to support our findings regarding autotrophic metabolism. A comprehensive survey of microbial communities should be undertaken at more sampling sites with replicates to determine whether the microbial communities changed dramatically in the different layers and at different sites in the same layers of the brine pools."
} | 4,271 |
23607440 | PMC3655853 | pmc | 8,016 | {
"abstract": "Background A single cultured marine organism, Nanoarchaeum equitans , represents the Nanoarchaeota branch of symbiotic Archaea, with a highly reduced genome and unusual features such as multiple split genes. Results The first terrestrial hyperthermophilic member of the Nanoarchaeota was collected from Obsidian Pool, a thermal feature in Yellowstone National Park, separated by single cell isolation, and sequenced together with its putative host, a Sulfolobales archaeon. Both the new Nanoarchaeota (Nst1) and N. equitans lack most biosynthetic capabilities, and phylogenetic analysis of ribosomal RNA and protein sequences indicates that the two form a deep-branching archaeal lineage. However, the Nst1 genome is more than 20% larger, and encodes a complete gluconeogenesis pathway as well as the full complement of archaeal flagellum proteins. With a larger genome, a smaller repertoire of split protein encoding genes and no split non-contiguous tRNAs, Nst1 appears to have experienced less severe genome reduction than N. equitans. These findings imply that, rather than representing ancestral characters, the extremely compact genomes and multiple split genes of Nanoarchaeota are derived characters associated with their symbiotic or parasitic lifestyle. The inferred host of Nst1 is potentially autotrophic, with a streamlined genome and simplified central and energetic metabolism as compared to other Sulfolobales . Conclusions Comparison of the N. equitans and Nst1 genomes suggests that the marine and terrestrial lineages of Nanoarchaeota share a common ancestor that was already a symbiont of another archaeon. The two distinct Nanoarchaeota -host genomic data sets offer novel insights into the evolution of archaeal symbiosis and parasitism, enabling further studies of the cellular and molecular mechanisms of these relationships. Reviewers This article was reviewed by Patrick Forterre, Bettina Siebers (nominated by Michael Galperin) and Purification Lopez-Garcia",
"conclusion": "Conclusion For a decade, the only specific association between two Archaea involved the ectoparasite Nanoarchaeum equitans and its marine hyperthermophile host, Ignicoccus hospitalis . N. equitans is a deep archaeal lineage, with a tiny genome, enriched in split genes, and lacking primary metabolism. We sequenced the genome of the first hyperthermophilic Nanoarchaeota from a terrestrial environment (Yellowstone National Park) and its likely archaeal host. A larger genome, fewer split genes, and existing carbohydrate metabolism indicate that nanoarchaeal symbiosis predates the divergence of terrestrial and marine lineages, and resulted in distinct gene loss and fragmentation. This second symbiotic system enhances understanding of interspecies interaction and evolution of archaea and will guide future research on characterizing the molecular and cellular mechanism involved in these archaeal symbiotic associations.",
"discussion": "Discussion Despite multiple ultrastructural, biochemical and functional genomic studies, the nature of the relationship and the mechanisms of interaction between I. hospitalis and N. equitans remain poorly understood. So far, there is no evidence for a beneficial role of N. equitans for its host, suggestive of a parasitic as opposed to a mutualistic relationship\n[ 12 ]. Experimental and genomic inferences point to the two archaea having co-evolved, with N. equitans using I. hospitalis as its sole host\n[ 12 , 29 ]. The difficulty in the characterization of their interaction and phylogenetic placing of N. equitans comes in large part from the unusual features of the N. equitans genome that make it problematic to differentiate between two distinct scenarios for the origin of the Nanoarchaeota. Under the first scenario, Nanoarchaeota represent an ancient lineage with many ancestral features whereas the alternative involves relatively recent, rapid evolution and genomic collapse driven by the parasitic lifestyle. The analysis of the Nst1 genome described here addresses some of these questions and provides an evolutionary perspective on archaeal parasitism/symbiosis. The Nst1 genome lacks split tRNA genes but encompasses split protein genes, so that the existence of both unique and shared gene splits between the two Nanoarchaeota provides insight into the evolution of this feature. It now appears most likely that genome reduction, probably by intrachromosomal recombination and deletion events, led to stochastic fragmentation of multiple genes, with those split in locations compatible with functional enzymatic reconstitution in trans being retained. The presence of several genes with the same split site between the two Nanoarchaeota implies that this process predated the separation of the two lineages. Together with multiple common gene losses, these shared gene splits suggest that the most recent common ancestor of the terrestrial and marine Nanoarchaeota, represented by the two current representatives, already was a symbiont or parasite that was undergoing genome shrinkage. Given the large evolutionary distance between N. equitans and Nst1 and the fact that they inhabit different environments and appear to employ highly diverged Crenarchaeota as hosts, the radiation of the two lineages probably was an ancient event. Genome contraction apparently has continued after ecological separation and by either host specialization or switching. The larger genome of Nst1 and the presence of some primary metabolic functions indicate that the terrestrial nanoarchaeon has not reached the advanced genomic collapse stage that is characteristic of its marine sister group. The complete absence of split tRNA genes in Nst1 and the presence of the RNase P machinery is compatible with this scenario, indicating that these unique alterations of the N. equitans translation system evolved more recently as a result of the extreme genomic degradation in this lineage. Genome sequencing of other members of the Nanorchaeota should aid in further elaborating this scenario. Phylogenetic analysis of the two Nanoarchaeota revealed a strongly supported, deep branching clade that was originally proposed to represent a distinct phylum\n[ 1 ]. Clear affinities to the Euryarcheaota , in terms of shared gene content, are maintained, as previously pointed out\n[ 6 ], but such deep affinities might predate phyla divergence, such as those between Korarchaeota and Crenarchaeota [ 35 ] and between Thaumarchaeota and Crenarchaeota [ 36 ]. Conceivably, the evolutionary driving force that led to the separation of Nanoarchaeota from the Euryarchaeota was an ancient symbiotic event, with the corollary that all members of the Nanoarcheaota could be symbionts or parasites. Similar to N. equitans, Nst1 apparently relies on an external source of almost all building blocks, with the probable exception of some amount of ATP and NADH that could be produced by glycolysis. The absence of an ATP synthase, while extraordinary, remains to be confirmed by genome closure. It is notable, however, that even in N. equitans , the assembly of a functional ATP synthase complex has not been yet demonstrated and remains uncertain given the absence of the genes for several subunits\n[ 37 ], even though the present ones are expressed\n[ 38 ]. Although a specific host-symbiont/parasite association between Acd1 and Nst1 requires formal proof by isolation and cultivation of the two organisms in the laboratory, the results presented here strongly suggest a relationship between these two organisms. The lack of readily detectable genomic and physiological complementarity between N. equitans and its host implied that N. equitans is a parasite rather than a mutualistic symbiont\n[ 5 , 12 , 29 ]. Despite the initial hypothesis that large membrane vesicles may transfer proteins and lipids from the host to N. equitans [ 5 ], whole cell proteomic measurements have not found evidence of significant amounts of biosynthetic enzymes being transported from Ignicoccus to N. equitans [ 38 ]. The transfer of small molecules from I. hospitalis (confirmed for lipids and aminoacids\n[ 12 , 39 ]) must occur therefore through membrane transporters or a specialized structure that may be present at the point of contact between the cells\n[ 40 ]. The second archaeal parasite(symbiont)-host pair described here adds further complexity to the question how these relationships are established and maintained. The membrane organization and gene content of I. hospitalis and Acd1 differ substantially. Genome analysis indicates that Acd1 is closely similar to other Sulfolobales and likely has the characteristic S-layer membrane\n[ 34 ], distinct from the unique double membrane that is a hallmark feature of Ignicoccus [ 41 ], genus so far exclusively marine . Thus, the two Nanoarchaeota might have evolved independent mechanisms to interact with their hosts and/or share common genes and structures for acquiring metabolic precursors that remain to be characterized. Although Nst1 generally resembles N. equitans in lacking readily detectable inferred functionalities that could complement functions missing in the host, a major exception is the archaellum that is encoded in the Nst1 genome but apparently not in the genome of Acd1. Cellular appendages have been observed occasionally in N. equitans [ 42 ] but their nature and roles are unknown, and the genome lacks recognizable archaeallum genes\n[ 18 ]. The predicted Nst1 archaeallum might provide motility or attachment capabilities for the nanoarchaeon cell and perhaps even its associated host, a possibility that remains to be explored once the cultivation of these organisms is achieved. Despite the substantial differences in the gene repertoires and the lack of specific common trends, the two hosts of Nanoarchaea do share a prominent common trait, genome streamlining. Indeed, I. hospitalis has the smallest genome amongst Crenarchaeota , whereas the Acd1 genome, even though larger, is by far the smallest among the Sulfolobales . Reconstruction of genome evolution indicates that the reduced gene repertoire is not an ancestral feature but a derived one caused by extensive gene loss. The shrinking of functional capabilities, in particular in defense systems, might have made these organisms vulnerable to parasite infestation or conversely, the host genome shrinkage was a result of the relationship with their nanoarchaeal companions; these two possibilities are not necessarily mutually exclusive. Characterization of additional archaeal parasite/symbiont-host systems from such geochemically diverse ecosystems as marine and terrestrial thermal habitats will show how general these trends are and what evolutionary forces and mechanisms drive them."
} | 2,704 |
38322579 | PMC10845243 | pmc | 8,019 | {
"abstract": "A polymicrobial biofilm model of Komagataeibacter hansenii and Pseudomonas aeruginosa was developed to understand whether a pre-existing matrix affects the ability of another species to build a biofilm. P. aeruginosa was inoculated onto the preformed K. hansenii biofilm consisting of a cellulose matrix. P. aeruginosa PAO1 colonized and infiltrated the K. hansenii bacterial cellulose biofilm (BC), as indicated by the presence of cells at 19 μm depth in the translucent hydrogel matrix. Bacterial cell density increased along the imaged depth of the biofilm (17-19 μm). On day 5, the average bacterial count across sections was 67 ± 4 % P . aeruginosa PAO1 and 33 ± 6 % K. hansenii . Biophysical characterization of the biofilm indicated that colonization by P. aeruginosa modified the biophysical properties of the BC matrix, which inlcuded increased density, heterogeneity, degradation temperature and thermal stability, and reduced crystallinity, swelling ability and moisture content. This further indicates colonization of the biofilm by P. aeruginosa. While eDNA fibres - a key viscoelastic component of P. aeruginosa biofilm - were present on the surface of the co-cultured biofilm on day 1, their abundance decreased over time, and by day 5, no eDNA was observed, either on the surface or within the matrix. P. aeruginosa -colonized biofilm devoid of eDNA retained its mechanical properties. The observations demonstrate that a pre-existing biofilm scaffold of K. hansenii inhibits P. aeruginosa PAO1 eDNA production and suggest that eDNA production is a response by P. aeruginosa to the viscoelastic properties of its environment.",
"conclusion": "5 Conclusion Co-culturing a preformed BC matrix of K. hansenii with P. aeruginosa PAO1 resulted in integration of the two populations. This is demonstrated by complete distribution of cells over BC matrix, significantly denser more heterogeneous surface, and a less porous structure with thick bundled fibres coated with EPS. Extended degradation temperature, improved thermal stability and reduction in crystallinity, swelling ratio and moisture content of the co-cultured biofilm in comparison to BC control, further indicate colonization of K. hansenii BC matrix by P. aeruginosa . The co-culturing method using a preformed matrix is an innovative approach to design and test interactions between the species. FTIR and confocal images indicates the absence of eDNA in the co-cultured biofilms after day 3, and that when a preformed matrix exists, P. aeruginosa does not produce eDNA. Further research is required to understand the critical limits for inhibiting eDNA production by P. aeruginosa in various preformed matrix environment (with regards to e.g., viscoelasticity and mesh size).",
"introduction": "1 Introduction Biofilms are an adaptation enabling microbial survival under a broad range of environmental conditions [ 1 , 2 ], an important mode of microbial life that play vital structural and functional roles [ 3 , 4 ]. Microbes achieve the formation of biofilm by secreting exopolymers that promote phase separation and the establishment of a physically distinct habitat for cells, that is the extracellular matrix [ 5 ]. This provides the microbes with a defense mechanism, where cells are encased within extracellular polymeric substance (EPS) thereby enabling adhesion to surfaces, nutrient sequestration, increased persistence, passaging of signaling molecules and other virulence factors, genetic exchange, creation of microenvironments, increased mechanical stability, and antimicrobial tolerance [ 6 , 7 ]. Numerous aspects of biofilms, including quorum sensing, growth mechanisms, virulence, extracellular polymers and matrix building, have been studied extensively in single species systems (e.g., Pseudomonas aeruginosa ) [ 8 ]. However, in clinical and environmental systems, bacteria rarely exist in pure cultures. Instead, polymicrobial communities predominate, where a range of relationships can exist between constituent populations [ 9 , 10 ]. The effects of community interactions within biofilms vary widely, from enhancing growth and survival of some, to inhibiting growth or killing another. Pseudomonads are present in many ecological settings . While P. aeruginosa has been shown to have an antagonistic relationship with some species, such as filamentous Candida albicans, which it attacks and kills, it neither attaches to nor kills others like yeast-form cells [ 11 ]. Competitive interactions can occur in community biofilms, due to overlapping metabolic preferences. Co-operative interactions are also possible which can contribute to enhanced biomass and biopolymer production [ 12 , 13 ]. Biofilms provide a matrix for localized interactions between species. Our understanding of polymicrobial EPS composition, its functional role, structural organization, ultimately how different microbes collectively regulate production and interact with EPS components within biofilm, is limited. Understanding the ecological roles and relationships between microbial populations in community biofilms is important to develop novel strategies to control biofilm formation. In this study, two well-known biofilm formers K. hansenii and P. aeruginosa PAO1 were used. Studies on co-culturing of BC-producing strains with other microorganisms are scarce. P . aeruginosa is a well-characterized model microorganism for studying biofilm formation and is commonly used to address questions about biofilm biology and ecology in general. It is actively motile in a wide-range of growth temperatures (25-42 °C), pH (5.6–9) and has simple nutritional requirements [ 14 ]. It is also well understood in terms of matrix composition having several polysaccharides in matrix formation (i.e., alginate, Pel and Psl) as well as proteins (CdrA, type iV fimbriae, functional amyloids), eDNA [ 15 ] and eRNA [ 16 ] as foundation structural polymers in its biofilms. eDNA was first observed in biofilms around twenty years ago [ 17 ]. Recently, attention has been diverted to the mechanism of eDNA assembly in the matrix and its formation. Some researchers indicate that it results from programmed lytic explosion of cells, others that it is the unplanned consequence of cell lysis [ 18 ]. A third explanation is that it is coordinated by quorum sensing [ 15 ]. Following release, it assembles into a 3-D cross-linked network that contributes to the foundation structure of Pseudomonas biofilm matrices. Turnbull et al ., 2016 , illustrated that coordinated explosive cell lysis occurred with a specific subpopulation of P. aeruginosa resulting in eDNA release and matrix assembly [ 18 ]. Furthermore, DNase has been shown to be effective at inhibiting biofilm formation at early stages of growth, but has no significant effects on established biofilms. This is likely due to the effect of protective interactions within the biofilm matrix [ 17 , 19 ], for example, resulting from crosslinking of eDNA by the cationic exopolysaccharide Pel [ 20 ], the formation of G-quadreplex eDNA structures [ 21 ], shielding of the eDNA from enzymatic actions [ 19 ] through the transition from B- to Z-form DNA [ 22 ], or hybrid formation with eRNA in the matrix [ 16 ]. However, what triggers the transition of supercoiled chromosomal DNA to viscoelastic and networked eDNA is not understood, including whether it is an active or deliberate strategy by the bacteria to assemble a biofilm matrix. We therefore sought to address this question, and specifically whether eDNA production by P. aeruginosa still occurs under conditions when a foundational matrix sub-structure is not required, such as when it colonizes another biofilm. Bacterial cellulose (BC) produced by Komagataeibacter spp. (formerly Gluconacetobacter ) was used as primary scaffold due to its unique characteristics such as nanofibrous, porous, crystalline matrix making it stand out over cellulose from other sources [ 23 ]. To the authors best knowledge, there are no studies reporting the presence of eDNA as key structural material in K. hansenii biofilms and thus an ideal model to investigate the research hypothesis. Using BC as a model preformed matrix allows an assessment of whether eDNA is a passive mechanism or an active response to the need for a biofilm matrix structure. Furthermore, this study demonstrates the value of the Komagataeibacter spp. and P. aeruginosa community biofilms as a tool to study interactions between microbial colonies, with regards to spatial distribution, biofilm integration and formation of biofilm components.",
"discussion": "4 Discussions To date, eDNA is understood to be released as a consequence of autolysis in biofilm systems [ 18 ]. The released eDNA has been shown to provide structural scaffold and mechanical resistance to biofilms by forming extracellular matrix [ 20 ]. However, in this study, we suggest that eDNA release is an active cell regulated mechanism. This is due to the attenuation of eDNA production after day 3 in the presence of preformed BC matrix of our co-cultured in vitro model of PAO1 and Komagataeibacter sp. One reason for this observation might be due to the highly nanofibrous structures of cellulose ( Fig. 2 ) which provide optimal surface for efficient cell adsorption. Additionally, higher moisture content along with nanoporous structures of cellulose provide favourable nutrient rich conditions for PAO1 growth without the need for eDNA production during the later stages of biofilm formation. Our study reports the development of a reproducible polymicrobial biofilms model that is intended to be used for understanding the co-existence, interaction, structural integration, biofilm components modification and relationships between mixed microbial population that exist in nature. The model is developed by using preformed BC from K. hansenii 53582 instead of co-culturing the two as we experienced that P. aeruginosa outgrows K. hansenii 53582, likely due to shorter doubling time (30–50 min compared to 8–10 h) or the production by P. aeruginosa of metabolites that inhibit competitors (e.g., pyocyanin). There was no sign of BC matrix production even with increased inoculum ratios of K. hansenii . The microscopy results of co-cultured biofilm, BC(PAO1), clearly indicate biofilm integration as suggested by the significantly denser, heterogeneous surface, less porous with larger ribbons coated with EPS and infiltration of P. aeruginosa PAO1 into the BC matrix. These results are in agreement with earlier reports, as EPS plays a significant role in regulating the bundling process of BC microfibrils, resulting in larger bundles. The bundling of nanofibers was promoted by coating co-crystallized microfibrils. Aggregation of co-crystallized microfibrils is due to van de Waals interactions and hydrogen bond [ 30 , 34 ]. Bacterial motility facilitates interaction by penetration into the existing biofilm promotes colonization by invasion into the fibres. P. aeruginosa preferential growth on BC matrix might be due to depletion of oxygen and limited nutrients. Growing within the biofilm is advantageous for growth and survival of any organism, but favourable rich environment suppressing the release of eDNA foundation matrix cannot be considered. It is reported that biofilms with eDNA presence in bacterial infected wounds are difficult to treat and heal [ 35 ]. It is evident that P. aeruginosa outcompetes K. hansenii. The nonappearance of eDNA at the end of co-culturing strongly indicates that P. aeruginosa PAO1 can modify its strategy for biofilm assembly when a structural scaffold is already available, as illustrated here with a preformed BC matrix along with viable K. hansenii cells. The changes in the physicochemical properties of co-cultured BC(PAO1) in comparison to BC control indicate that PAO1 EPS is interacting with BC nanofibers. The XRD results show a reduction in crystallinity of co-cultured biofilm which could be due to the amorphous nature of EPS [ 36 ]. Insertion of polymeric material into the existing crystalline biopolymer has been reported to cause crystallinity reduction [ 37 , 38 ]. The incorporation and penetration of EPS molecules with the cellulose microfibrils disrupts the original hydrogen–bonding interactions between the cellulose microcrystalline chains [ 37 ]. Tensile testing of co-cultured BC(PAO1) revealed no significant changes in the Young's modulus, stress at break, and strain at break compared with BC control. While improved mechanical strength was expected, the high concentrations of EPS, coating the surface of co-crystallised microfibrils might have disrupted their additional aggregation and networking with bacterial cellulose microfibrils. Hence, impeding enhancement of its mechanical strength [ [30] , [39] ]. However, in the absence of eDNA, which is known to dominate the elasticity of P. aeruginosa biofilms, the mechanical properties and strcutural integrity of BC remain unaffected by EPS from P. aeruginosa . Prior studies have shown similar results. There was no significant change in the mechanical properties by co-culturing K. hansenii ATCC 23769 with E. coli ATCC 35860, which produces a high concentration of EPS (41.4 mg/ml), but had a significant increased mechanical strength by co-culturing with E. coli ATCC 700728, which produces relatively low concentration (3.4 mg/ml) of EPS [ 30 ]. The TGA results revealed that the initial weight loss below 200 °C was due to dehydration and at higher temperature the cleavage of glycosidic bonds occurs with rapid weight loss. The maximum weight loss is related to pyrolysis of the β-1,4-glycosidic bond [ 24 ]. The less intense and wider endothermic peaks corresponding to reduced crystallinity and increased thermal stability of BC(PAO1) co-cultured biofilm. The addition of EPS is likely to cause disruption of the regular arrangement among the glucose molecules. The TGA results on BC(PAO1) are consistent with the XRD results and further confirm the integration of EPS (increased amorphous content) into BC matrix as reflected by the extended degradation temperature, thermal stability and reduced crystallinity of the co-cultured biofilm. The substantial reduction in swelling ratio and moisture content of BC(PAO1) can be attributed to reduced porosity of BC matrix compared to BC control, caused by EPS coating over BC nanofibers."
} | 3,608 |
30154827 | PMC6102323 | pmc | 8,020 | {
"abstract": "Experimental microbial ecology and evolution have yielded foundational insights into ecological and evolutionary processes using simple microcosm setups and phenotypic assays with one- or two-species model systems. The fields are now increasingly incorporating more complex systems and exploration of the molecular basis of observations. For this purpose, simplified, manageable and well-defined multispecies model systems are required that can be easily investigated using culturing and high-throughput sequencing approaches, bridging the gap between simpler and more complex synthetic or natural systems. Here we address this need by constructing a completely synthetic 33 bacterial strain community that can be cultured in simple laboratory conditions. We provide whole-genome data for all the strains as well as metadata about genomic features and phenotypic traits that allow resolving individual strains by amplicon sequencing and facilitate a variety of envisioned mechanistic studies. We further show that a large proportion of the strains exhibit coexistence in co-culture over serial transfer for 48 days in the absence of any experimental manipulation to maintain diversity. The constructed bacterial community can be a valuable resource in future experimental work.",
"introduction": "Introduction Testing ecological and evolutionary theory in a highly controlled manner using simple laboratory setups with one or two microbial species ( Fraser and Keddy, 1997 ; Buckling et al., 2009 ) has produced important insights into ecological interactions–e.g., competition, cooperation, and cross-feeding interactions ( Helling et al., 1987 ; Treves et al., 1998 ; Rozen and Lenski, 2000 ; Shou et al., 2007 ; Harcombe, 2010 ); the role of cheaters ( MacLean and Gudelj, 2006 ); predator–prey interactions ( Shertzer et al., 2002 ); and host–parasite interactions ( Morgan et al., 2005 )–and evolutionary processes–e.g., the evolution of coexistence ( Good et al., 2017 ), coevolution between species ( Hall et al., 2011 ; Brockhurst and Koskella, 2013 ), and eco-evolutionary feedback dynamics ( Yoshida et al., 2003 ; Hiltunen and Becks, 2014 ). However, there is an increasing awareness that ecological and evolutionary processes can be fundamentally altered in more complex multispecies communities owing to several features such as altered competitive interactions and multiple selection pressures ( Dunham, 2007 ). Recent empirical findings show, for example, that pairwise interactions can be strongly altered in the presence of other species ( Kastman et al., 2016 ) and the rate of adaptation of species can differ between monocultures and communities ( Lawrence et al., 2012 ). Even a basic understanding of certain characteristics of microbial life such as horizontal gene transfer ( Smillie et al., 2011 ), metabolic interactions and spatial heterogeneity ( Elias and Banin, 2012 ; van Gestel et al., 2014 ) requires investigation of multispecies settings integral to them. Furthermore, several key ecological features are specific to multispecies communities, such as diversity, stability, succession and high-order (e.g., four-way) species interactions ( Bairey et al., 2016 ). There is therefore a profound need to expand the biotic complexity of study systems used in the fields of experimental microbial ecology and evolution. The design of multispecies model communities in experimental ecology and evolution is part of the emerging field of synthetic ecology where synthetic communities are used for a plethora of basic and applied purposes. Several research attempts have sought mechanistic understanding of specific natural systems, such as methane consuming communities ( Yu et al., 2017 ), plant root colonizing bacteria ( Lebeis et al., 2015 ), the human gut microbiota ( Goodman et al., 2011 ), and cheese rind communities ( Wolfe et al., 2014 ), by complementing observational findings with findings from controlled in vitro or in vivo studies using synthetic communities. These studies focus on designing synthetic communities that capture the essential features of the natural system being investigated. A typical approach is to determine the prevalent taxa in the natural system or in the core microbiome ( Shade and Handelsman, 2012 ) common to similar systems, to construct a synthetic community of taxonomically representative strains isolated from the natural system, and to culture the community in conditions mimicking the natural system. The limitations of this approach include the potentially important role in ecological functions or evolutionary processes of low-abundance taxa ( Liu et al., 2017 ), microdiversity ( Chase et al., 2017 ), or interactions between bacteria and members of other taxonomic groups such as viruses, unicellular eukaryotic predators or fungi, as well as technical difficulties in mimicking natural conditions in the laboratory ( Wolfe, 2018 ). Likely owing to such limitations, among these studies, cases have been observed both where simple synthetic communities representing predominant taxa in natural systems recapitulate the dynamics in natural systems ( Goodman et al., 2011 ; Wolfe et al., 2014 ; Lebeis et al., 2015 ) and where major differences are observed between synthetic and natural systems ( Yu et al., 2016 ). Compared with studies employing synthetic communities to understand specific natural systems, more applied studies focusing, among others, on medical therapeutics ( Petrof et al., 2013 ; Sheth et al., 2016 ), bioremediation ( Dejonghe et al., 2003 ; Zomorrodi and Segre, 2016 ), or biofuel production ( Wang et al., 2015 ), rely even more heavily on a detailed understanding of the characteristics and functions of specific bacterial taxa in natural systems to engineer communities that can successfully perform desired functions. In contrast, studies attempting to investigate highly general ecological or evolutionary processes, similar to traditional experimental microbial ecology and evolution using one- or two-species model systems, do not necessarily seek to, or prefer simple culture conditions over the ability to, accurately represent a particular natural community. For instance, a synthetic community of 72 bacterial strains isolated from tree-hole bacterial communities–but limited to aerobic heterotrophs cultivable in simple laboratory conditions–has been used to investigate several key ecological questions, including the relationship between diversity and ecosystem productivity ( Bell et al., 2005 ) and the success of multispecies invasions during different stages of ecological succession ( Rivett et al., 2018 ). Celiker and Gore (2014) , in turn, used a completely synthetic model community comprising six apparently random soil bacterial strains from culture collections to examine the repeatability of change in community composition over time. In simplified synthetic communities, verisimilitude is sacrificed to obtain relative ease of analysis and modeling, and control of species interactions, non-linear effects from added traits and strains, and evolutionary change ( Widder et al., 2016 ). There is ongoing debate about the utility of simple microcosm setups to understand ecological and evolutionary phenomena ( Carpenter, 1996 , 1999 ; Fraser and Keddy, 1997 ; Drenner and Mazumder, 1999 ; Benton et al., 2007 ; Buckling et al., 2009 ), yet the approach continues to produce major scientific discoveries ( van Houte et al., 2016 ; Good et al., 2017 ; Betts et al., 2018 ; Frickel et al., 2018 ). Similarly, the definition of, need for, and necessary level of representativeness of synthetic communities remain matters of debate ( Dolinsek et al., 2016 ; Widder et al., 2016 ; Zomorrodi and Segre, 2016 ; Wolfe, 2018 ), and are likely strongly dependent on the research questions. Although debated, completely synthetic communities composed of strains isolated from different habitats can also be used to study general questions as well as having special use in studying questions such as community assembly and the evolution of coexistence in newly formed communities. In this context, the detailed, mechanistic understanding of simpler, less representative synthetic communities can be thought to inform, or even be a prerequisite to, understanding more complex synthetic systems, and ultimately, natural systems. It has been argued that such efforts should focus on understanding a limited set of well-defined model synthetic communities, which would make results comparable between studies and allow collaborative efforts toward mechanistic understanding ( Widder et al., 2016 ). However, not many such systems exist to our knowledge despite the general boom in synthetic ecology. Furthermore, the highly general level studies that exist primarily focus on simple phenotypic analyses ( Bell et al., 2005 ; Foster and Bell, 2012 ; Celiker and Gore, 2014 ; Rivett et al., 2016 , 2018 ; Rivett and Bell, 2018 ), although high-throughput molecular methods, such as amplicon sequencing, (meta)genomics, (meta) transcriptomics, proteomics and metabolomics, which have been promisingly utilized in studies focusing on synthetic systems mimicking natural systems ( Goodman et al., 2011 ; Wolfe et al., 2014 ; Lebeis et al., 2015 ; Stopnisek et al., 2016 ; Yu et al., 2017 ), could provide valuable insights into the mechanisms behind observed phenotypic and community level features. To address these needs, we here constructed a simplified experimental system comprising a completely synthetic community of 33 bacterial strains representing two phyla and six classes that can be cultured individually and in co-culture in highly simple laboratory conditions, and that can be individually resolved based on amplicon sequencing. Furthermore, we present draft-level whole genome sequence data as well as information regarding genomic features and phenotypic traits for all strains in the community, facilitating further mechanistic studies. We also present proof of concept for coexistence of a large proportion (14/33) of the strains in co-culture after serial passage of cultures for 48 days. Such a community can be a highly useful resource for experimental microbial ecology and evolution. For instance, we recently used a closely related model system to track the mobility of antibiotic resistance genes in a complex bacterial community ( Cairns et al., 2018 ). For future studies, we envision, for example, exploration of the trajectories of ecosystem composition and genetic structure in response to environmental perturbations or variability in functional trait space. We are also considering using the community as an internal control for improving high-throughput microbial single cell genome sequencing techniques such as epicPCR ( Spencer et al., 2016 ) or metagenome assemblies.",
"discussion": "Discussion and Conclusion We developed a multispecies synthetic bacterial community, which was characterized at the genomic and phenotypic levels, revealing high diversity in the resistome, mobilome and functionome of the community. Furthermore, we demonstrated the utility of the community by showing coexistence of a large proportion (14/33) of the strains in co-culture over serial transfer for 48 days. These observations indicate that the community is suitable for use as a cultivated model community to ask a wide range of biological questions. Along with characterizing the community, we produced comprehensive genomic and phenotypic metadata for the community members. This facilitates future mechanistic work with the community. For instance, our pipeline allows the use of amplicon sequencing to track community composition over time at strain-level resolution. Moreover, the genome assemblies provide a reference database for (meta)genomic and (meta)transcriptomic studies. Isolation of individual colonies combined with colony PCR, in turn, allows the rapid identification of substrains possessing mutations or horizontal gene transfer events of interest. Our model community is composed of diverse bacterial strains isolated from different environments and hence does not mimic any specific natural community. Therefore, the community is more suited to study general questions about ecology and evolution such as community assembly and response to environmental perturbations rather than to explain patterns in any particular natural microbial community ( Wolfe, 2018 ). The ability of the community to answer general questions may be limited by the potential absence of focal taxonomic groups or high-order interactions that occur in more complex communities. The community is composed of bacteria alone, while interactions between bacteria and fungi, protozoa or bacteriophages often play a key role in natural microbial communities. In a separate study, however, we have introduced a method for incorporating protozoa in the community ( Cairns et al., 2018 ). The utility of the 33-strain model community and its predecessor is demonstrated in the current and previous work by us ( Cairns et al., 2018 ). Here we present the community and a collection of methods and metadata to the scientific community. A previous version of the community has already been successfully used for tracking the mobility of antibiotic resistance genes ( Cairns et al., 2018 ), and as prominent cases of future use we envision, for instance, replicated ecosystem microcosms to explore the trajectories of ecosystem composition and genetic structure in response to various environmental perturbations. We also envision the community as an efficient spike-in control to increase the statistical rigor of high-throughput microbial single cell assays such as epicPCR ( Spencer et al., 2016 ) or as a test system for validating metagenome assemblers."
} | 3,443 |
25350160 | PMC4409162 | pmc | 8,021 | {
"abstract": "Low-input agricultural systems aim at reducing the use of synthetic fertilizers and pesticides in order to improve sustainable production and ecosystem health. Despite the integral role of the soil microbiome in agricultural production, we still have a limited understanding of the complex response of microbial diversity to organic and conventional farming. Here we report on the structural response of the soil microbiome to more than two decades of different agricultural management in a long-term field experiment using a high-throughput pyrosequencing approach of bacterial and fungal ribosomal markers. Organic farming increased richness, decreased evenness, reduced dispersion and shifted the structure of the soil microbiota when compared with conventionally managed soils under exclusively mineral fertilization. This effect was largely attributed to the use and quality of organic fertilizers, as differences became smaller when conventionally managed soils under an integrated fertilization scheme were examined. The impact of the plant protection regime, characterized by moderate and targeted application of pesticides, was of subordinate importance. Systems not receiving manure harboured a dispersed and functionally versatile community characterized by presumably oligotrophic organisms adapted to nutrient-limited environments. Systems receiving organic fertilizer were characterized by specific microbial guilds known to be involved in degradation of complex organic compounds such as manure and compost. The throughput and resolution of the sequencing approach permitted to detect specific structural shifts at the level of individual microbial taxa that harbours a novel potential for managing the soil environment by means of promoting beneficial and suppressing detrimental organisms.",
"conclusion": "Conclusion Agricultural soils under long-term organic and conventional farming harbour distinct microbiomes. The response of microbial diversity to agricultural management is, however, highly complex and simplistic statements like ‘higher biodiversity under low-input farming' fall short of this complexity. Under the exclusion of other fundamental factors often common to agricultural management such as differential soil tillage or monocropping systems, our study demonstrated that the fertilization scheme, in particular the application and quality of organic fertilizers, is the major determinant of microbial diversity. The impact of an integrated pest management regime, characterized by moderate and targeted application of pesticides, appears to be of subordinate importance, although some effects may be attributed to this factor. It can be assumed that differences in microbial diversity between organic and conventional farming would have been even more substantial at more intense pesticide applications and soil tillage operations as well as with cropping systems lacking soil-replenishing crops such as legumes, all traits that are common to many conventional farming systems. Long-term agricultural management in the DOK experiment appeared to select for system-specific community patterns that are consistent with the existing knowledge of individual taxonomic groups, but the limited functional information provided by phylogenetic surveys also precludes more definite conclusions. However, the ability to observe specific structural shifts at the level of individual microbial taxa now offers novel insights into the potential of managing the soil microbiome for sustainable agricultural productivity and plant protection.",
"introduction": "Introduction With the advent of the green revolution, agricultural productivity has been raised by increased fertilization and pesticide application, improved irrigation, soil management regimes and crops as well as massive land conversions ( Tilman et al. , 2002 ). There is increasing concern, however, that agricultural intensification leads to large-scale ecosystem degradation and loss of productivity in the long term. Negative environmental implications include soil degradation, increased greenhouse gas emissions, accumulation of pesticides and diminished availability and quality of water ( Tilman et al. , 2001 ; Foley et al. , 2005 ). In fact, agricultural intensification is perceived as one of the greatest threats to global biodiversity ( Convention on Biological Diversity, 2010 ). Low-input systems such as organic farming, which substantially reduce the use of synthetic fertilizers, pesticides, energy and mechanic stress, aim at mitigating these negative impacts in order to improve sustainable production ( Gomiero et al. , 2011 ). However, we still have an incomplete understanding of the challenges, benefits and limitations of low-input farming ( Tscharntke et al. , 2012 ) and the sustainability of organic farming ( Wu and Sardo, 2010 ). One of the cornerstones of agricultural management is proper stewardship of soil. Soil provides fundamental ecosystem services including nutrient cycling, water regulation, transformation of organic materials and toxic compounds as well as control of pests and diseases ( Doran and Zeiss, 2000 ). At the system level, the microbiome plays an integral role in virtually all soil processes ( Barrios, 2007 ), such that microbial abundance, activity and composition will largely determine sustainable productivity of agricultural land ( van der Heijden et al. , 2008 ). In this light, the ability to manage the soil microbiome for the presence of beneficial and absence of detrimental organisms could offer a promising approach to improve sustainable agricultural production. Effects of agricultural management on the soil microbiome are, however, complex and diverse ( Bünemann et al. , 2006 ; Nelson and Spaner, 2010 ), and retrieving universally valid conclusions on organic and conventional farming systems is difficult. In general, it has been reported that low-input farming systems promote higher abundance and diversity of most organisms, and although the positive effects on the macrobiota are largely consistent across studies, the impact on the microbiota seems less clear ( Hole et al. , 2005 ; Postma-Blaauw et al. , 2010 ). The enormous complexity of microbial life and the technical constraints to properly measure its components have so far limited our understanding of the relationships between low-input farming and microbial diversity. Novel high-throughput DNA sequencing technologies offer ways to explore the soil microbiota at higher resolution, coverage and throughput, and have the potential to shed more light on the community- as well as taxon-level responses to agricultural management ( Taberlet et al. , 2012 ). The broad spectrum of agricultural practices further limits comparability among different studies ( Hole et al. , 2005 ; Gomiero et al. , 2011 ). Whereas organic systems are commonly defined by management practices lacking the application of synthetic fertilizers and pesticides, the definition of conventional management is more variable. Fertilization and plant protection schemes as well as crop rotation and soil tillage strategies often vary across conventional farming systems. Commonly, conventional management practices rely on the use of synthetic fertilizers and pesticides and often avoid the use of organic fertilizers. However, as organic amendments have been shown to exert positive effects on various soil properties ( Rosen and Allan, 2007 ), more integrated conventional fertilization strategies seek to use a combination of synthetic and organic fertilizers. However, only a few agroecosystem experiments exist that compare organic and conventional management strategies with different fertilization and plant protection regimes over an extended period of time ( Raupp et al. , 2006 ) that is ultimately required for evaluating sustainability of land-use regimes ( Rasmussen et al. , 1998 ). The Swiss DOK (German abbreviation for d ynamic, o rganic and c onventional agricultural management) experiment represents a unique system to compare the long-term effects of organic and conventional management on ecosystem properties ( Raupp et al. , 2006 ). Since 1978, 96 plots have been managed according to five different farming systems along with a 7-year crop rotation in three temporally shifted parallels ( Mäder et al. , 2002 ). These farming systems differ in plant protection and fertilization regimes, whereas factors such as tillage and crop rotation are kept constant. The DOK experiment includes two conventional approaches, an exclusively minerally fertilized system and an integrated system with a fertilization scheme combining mineral and organic fertilization, and contrasts these to three organic systems with different fertilization schemes but all lacking the use of chemicals. Over the years, organic systems revealed an increase in microbial biomass and activity, largely driven by quantity and quality of farmyard manure ( Fliessbach et al. , 2007 ; Birkhofer et al. , 2008 ). Whereas management effects on microbial bulk parameters have been well documented, the impact on soil microbial community composition was more difficult to assess. The first-generation molecular tools used to examine shifts in community structures such as genetic profiling and phospholipid fatty acid analyses demonstrated structural differences among the various organic and conventional systems ( Hartmann and Widmer, 2006 ; Hartmann et al. , 2006 ; Widmer et al. , 2006 ; Esperschuetz et al. , 2007 ). However, diversity coverage and phylogenetic resolution strongly limited the assessment of both α- and β-diversity as well as a thorough identification of microbial groups indicative of specific management regimes. In this context, we employed a 454-pyrosequencing approach ( Margulies et al. , 2005 ) of bacterial and fungal ribosomal markers to examine the response of soil microbial diversity to >20 years of continuous organic and conventional farming in the DOK experiment. At the farming system level, we aim to identify the major agricultural factors driving differences in α- and β-diversity across management and crop regimes. Based on the initial community-level assessment, we then aim at harnessing the power of the sequencing approach to identify soil microbial taxa that have adapted to conditions characteristic of long-term agricultural intensification or low-input farming. In the long term, the capability to monitor individual microbial taxa may improve our potential to manage agricultural soils for sustainable productivity by promoting beneficial and suppressing pathogenic microorganisms.",
"discussion": "Discussion The DOK field experiment represents a unique system to evaluate the influence of management strategies under near-practical conditions including different crop types. More than two decades of continuous organic and conventional farming altered soil microbial diversity ( Figure 1 and Tables 2 and 3 ). The long-term effect of agricultural management revealed a greater impact than the short-term effects of the cultivated crop, in particular on bacteria. The spatiotemporal variability was substantial, demonstrating the importance of thoroughly replicated, temporally monitored long-term field studies to measure robust effects. Application and quality of the fertilizer appeared to be the major factor shaping the soil microbiota, whereas the plant protection measures, applied at moderate and targeted levels, were of subordinate importance ( Figures 1 and 4 ). In general, management-sensitive taxa were heterogeneously distributed across the taxonomic tree ( Figure 3 and Supplementary Figure 2 ); however, some consistent patterns, for example among members of the Acidobacteria and Firmicutes ( Figure 5 ), were observed. Long-term agricultural management drives soil microbial community structure All five farming systems harboured structurally distinct microbial communities, and both bacteria and fungi showed a very similar response ( Figure 1 ). Despite the significant spatiotemporal variability common to field studies, our approach revealed consistent underlying management effects, indicating that the spatiotemporal variation, although high, did not confound these effects. While these observations are largely in agreement with earlier assessments in the DOK experiment using first-generation molecular techniques, the pyrotag approach offered improved resolution of the management effects in terms of explained variance and discrimination power (see Supplementary Results for detailed evaluation). Overall, FYM application appeared to be the major driver of microbial diversity by altering composition, reducing dispersion, increasing richness and decreasing evenness of the soil microbiota ( Figure 1 , Tables 2 and 3 and Supplementary Tables 1 and 2 ). The observation that conventional (CONFYM and CONMIN) or organic (BIODYN and NOFERT) systems under the same plant protection regime share less similarity in community structure than systems with similar nutritional status but different plant protection regimes (for example, NOFERT and CONMIN) suggest that the plant protection component is likely of subordinate significance in the DOK experiment ( Figures 1 and 4 ). It is, however, important to understand that the DOK experiment compares management regimes at the system level rather than evaluating the impact of individual management factors; therefore, the impact of the plant protection strategies cannot be completely isolated from fertilization effects. Although it can be expected that plant protection strategies affect microbial diversity, either directly by means of fungicides or indirectly by changing above- and below-ground communities through herbicide and insecticide application ( Bünemann et al. , 2006 ), the rather small plant protection effect in the DOK experiment is not necessarily surprising as herbicides, fungicides and insecticides have been applied according to the Swiss standards of integrated farming that largely corresponds to a moderate and targeted application of these chemicals ( Fliessbach et al. , 2007 ; Mäder et al. , 2007 ). While research has long focussed on the effect of agricultural management on biodiversity of higher organisms, assessing microbial diversity has only recently become more accurate in the light of high-resolution sequencing. Based on the response of richness, evenness and dispersion, it could be hypothesized that the high availability of a rich substrate like FYM increased richness by promoting copiotrophic organisms, whose predominance in turn reduced evenness. Furthermore, the consistent availability of the same substrate in all these plots streamlined the community and therefore reduced across-sample dispersion. In contrast, the absence of FYM led to a less eutrophic environment and a likely more variable distribution of nutrients, leading to reduced richness while increasing evenness and dispersion potentially by favouring various slow-growing oligotrophic organisms. We can conclude that organic farming significantly altered the soil microbiota when compared with conventionally managed soils under exclusively mineral fertilization; however, these effects were largely attributed to the use and quality of organic fertilizer, as differences became smaller when conventionally managed soils under an integrated fertilization scheme were compared. Reports on the effects of organic farming on microbial diversity are often ambiguous, in particular because the experimental systems and management definitions vary widely. Although Ge et al. (2008) observed the same countertrend between richness and evenness, other studies reported an increase in richness being accompanied by either positive ( Parham et al. , 2003 ; Jangid et al. , 2008 ) or no effect ( Sun et al. , 2004 ) on evenness after manure amendment. More recent high-throughput sequencing studies reported an increase in microbial evenness in organic systems ( Sugiyama et al. , 2010 ; Chaudhry et al. , 2012 ), but have not detected significant effects on richness ( Sugiyama et al. , 2010 ; Li et al. , 2012 ). Hence, it seems difficult to draw a robust conclusion on the effect of conventional and organic farming on bulk diversity parameters, in part because these metrics have often little power in resolving differences in community structure ( Hartmann and Widmer, 2006 ), but most importantly because the conclusion drawn strongly depend on the methods used, on the metric itself and, largely, on the experimental design. As an example for the latter, it has been reported that bacterial evenness under organic farming only increased in the first few years and then decreased in the long term ( van Diepeningen et al. , 2006 ), highlighting the importance of the temporal component for evaluating management effects. Soil chemistry appeared to be a statistically significant determinant of the soil microbial community structure, but it explained only ∼20% of the variance ( Table 4 ), and this could largely be attributed to the consistent differences between the unfertilized and all other systems ( Figure 2 ). The consistently lowest values in the unfertilized system could indicate poor sustainability of this farming system. At the other end of the spectrum, the biodynamic system showed significantly higher C org , N tot and pH, all of which are factors known to influence the soil microbiota ( Lauber et al. , 2008 , 2009 ). The higher degree of organic matter stability in composted FYM could be one explanation for the higher C org content ( Fliessbach et al. , 2007 ). The strongest differences were observed for soil P and Mg ( Table 4 ). It could be hypothesized that arbuscular mycorrhizal fungi changed in abundance and/or composition in soils with lower P concentrations ( Antunes et al. , 2012 ); however, we observed only few Glomeromycota, probably in part because of limited coverage by the primers used ( Kohout et al. , 2014 ; Stockinger et al. , 2010 ), and their response to the management regimes was minor. Overall, given the rather small differences in soil chemistry among the other farming systems, for example, 0.4 units of pH, 0.3% C or 0.03% N, it must be acknowledged that these differences, although statistically robust, are likely of minor biological significance. These small differences in soil chemistry, despite the large differences in carbon and nutrient inputs among the farming systems, suggest that substrate amendments had likely a more direct effect on the community structure than indirectly by altering the soil chemical status. Management-sensitive microbial taxa One of the most important attributes of the high-throughput sequencing approach is the potential to identify microbial taxa responsible for shifts in community structure. A considerably large fraction of the community, representing 10% of the OTUs that accounted for 50% of the pyrotags, responded significantly to the management regimes ( Figure 4 ). In general, OTUs associated with the same farming system or system combination were scattered across the taxonomic tree and only very few taxonomic groups responded uniformly ( Supplementary Figure 2 ). This is not necessarily surprising. Whereas a severe environmental impact such as soil compaction can affect entire clades of the soil microbiota by changing fundamental factors such as oxygen and water availability ( Hartmann et al. , 2014 ), more moderate changes introduced by agricultural management such as differences in the nutritional status likely cause more subtle shifts in community composition. The construction of co-correlation networks demonstrated that many of the abundant phyla revealed a strongly bimodal response to FYM application instead of favouring one condition ( Figure 5 ). Acidobacteria showed the strongest bimodal response, but different acidobacterial groups were found to occupy different clusters. OTUs assigned to the genus Candidatus Solibacter (and one Candidatus Koribacter ) revealed the most tightly correlated cluster in the complete network and were associated with systems not receiving FYM ( Supplementary Figure 4 ). Members of this genus have been suggested to be slow-growing oligotrophs adapted to nutrient-limited environments ( Ward et al. , 2009 ). Therefore, an increased abundance of these taxa in farming systems not receiving manure, where nutrients inputs are either low (NOFERT) or directly accessible to plants (CONMIN), is in agreement with this putative lifestyle. In contrast, the cluster tightly associated with FYM-based systems was mainly characterized by OTUs assigned to the classes Chloracidobacteria and RB25, who's lifestyles are largely unknown. Our observations therefore partially confirm the hypothesis that Acidobacteria generally prefer soil environments of low resource availability ( Fierer et al. , 2007 ) and higher acidity ( Jones et al. , 2009 ), but are also in agreement with the contrasting behaviour of individual acidobacterial subgroups reported previously ( Rousk et al. , 2010 ). The Firmicutes clade appeared to be the only abundant phyla responding in the same direction ( Figure 5 ). All OTUs assigned to this phylum, with one exception ( Paenibacillus chondroitinus ), were associated with systems receiving FYM; however, the rather dispersed co-correlation network indicates very different preferences for the different FYM systems. Among these 35 Firmicutes OTUs, 12 were assigned at genus level and included the genera Bacillus , Clostridium , Epulopiscium , Paenibacillus , Solibacillus , Symbiobacterium , Tepidimicrobium , Thermobacillus and Ureibacillus ( Supplementary Figure 4 ). Many of these genera have been found during meso- and thermophilic degradation processes of organic materials such as manure or compost ( Ryckeboer et al. , 2003 ) and are known to be capable of degrading various complex organic materials ( Watanabe et al. , 2007 ; Charbonneau et al. , 2012 ). Similar observations were made for fungi. OTUs assigned to coprophilous taxa such as Coprinellus , Coprinopsis , Preussia , Psathyrella and Mortierella , including members of the family Lasiosphaeriaceae such as Cercophora , Cladorrhinum , Podospora , Schizothecium and Zopfiella ( Krug et al. , 2004 ; Bills et al. , 2013 ), were tightly associated with FYM-based systems ( Supplementary Figure 4 ). Indeed, co-correlation analysis identified the family Lasiosphaeriaceae as a largely uniform cluster associated with FYM ( Figure 5 ). It is important to understand that we can only speculate on the ecological role of the detected taxa based on what has been previously described in other systems. Furthermore, we discovered several management-sensitive bacterial and fungal taxa for which we have little or no information about their lifestyle or for which we were not able to get taxonomic information at lower levels. It therefore remains challenging to infer the ecological role for many community members simply from phylogenetically based surveys, and additional information on the distribution of functional genes can now shed more light on our overarching observations. Therefore, our data should not be overgeneralized and the statistically significant observations need to be confirmed in other agricultural systems. It seems, however, that many of the OTUs associated with FYM-based farming systems are related to bacterial and fungal taxa that have been frequently described in manure and similar substrates. It remains to be determined whether manure served as inoculum for introducing novel taxa to the soil, or whether manure mainly served as substrate for indigenous taxa. As a next step, it would therefore be interesting to analyse the microbiota of the different manure types and evaluate how soil communities that have been unfertilized for a long time would respond to manure amendments over an extended period of time. With the novel sequencing technologies, we have tools at hand to monitor soil microbial taxa at higher throughput and resolution than previously possible. This offers the potential to evaluate success of agricultural soil management at the level of individual taxa and, potentially, their attributed function. For example, we can look specifically for known beneficial or pathogenic taxa that are promoted or suppressed by different management strategies. Members of the fungal order Hypocreales, for instance, are of vast economic importance in agricultural systems as they include many plant pathogens as well as potential biocontrol agents ( Rossman, 1996 ). In this study, several members of this group responded to the different management strategies ( Supplementary Figure 4 ). One of the most abundant OTUs (1.8%) assigned to the hypocrealean genus Bionectria was strongly ( R =0.6) associated with all organic systems, suggesting a negative influence of fungicide application or other plant protection measures. The necro- and biotrophic Bionectria are known plant, insect and mycoparasites that have found use as biocontrol agents in agriculture ( Schroers, 2001 ). Another common agricultural biocontrol agent, the entomopathogenic fungus Beauveria bassiana ( Feng et al. , 1994 ), was also positively associated with one of the organic systems. Conversely, several members of the common plant pathogen Fusarium were associated with conventional systems or systems not receiving manure ( Supplementary Figure 4 ). As another example, members of the potential plant pathogens Phoma and Ascochyta ( Davidson et al. , 2009 ) were particularly associated with the unfertilized system. These observations demonstrate that specific management strategies can select for beneficial or detrimental organisms. In the light of these examples, the novel technologies offer new ways to monitor the presence and absence of different beneficial and pathogenic taxa and thereby managing the soil microbiome for improving sustainable agricultural production ( Chaparro et al. , 2012 )."
} | 6,516 |
33939701 | PMC8092802 | pmc | 8,022 | {
"abstract": "Within the field of bioproduction, non-model organisms offer promise as bio-platform candidates. Non-model organisms can possess natural abilities to consume complex feedstocks, produce industrially useful chemicals, and withstand extreme environments that can be ideal for product extraction. However, non-model organisms also come with unique challenges due to lack of characterization. As a consequence, developing synthetic biology tools, predicting growth behavior, and building computational models can be difficult. There have been many advancements that have improved work with non-model organisms to address broad limitations, however each organism can come with unique surprises. Here we share our work in the non-model bacterium Actinobacillus succinognes 130Z, which includes both advancements in synthetic biology toolkit development and pitfalls in unpredictable fermentation behaviors. To develop a synthetic biology “tool kit” for A . succinogenes , information gleaned from a growth study and antibiotic screening was used to characterize 22 promoters which demonstrated a 260-fold range of fluorescence protein expression. The strongest of the promoters was incorporated into an inducible system for tunable gene control in A . succinogenes using the promoter for the lac operon as a template. This system flaunted a 481-fold range of expression and no significant basal expression. These findings were accompanied by unexpected changes in fermentation products characterized by a loss of succinic acid and increase in lactic acid after approximately 10 months in the lab. During evaluation of the fermentation shifts, new tests of the synthetic biology tools in a succinic acid producing strain revealed a significant loss in their functionality. Contamination and mutation were ruled out as causes and further testing is needed to elucidate the driving factors. The significance of this work is to share a successful tool development strategy that could be employed in other non-model species, report on an unfortunate phenomenon that needs addressed for further development of A . succinogenes , and provide a cautionary tale for those undertaking non-model research. In sharing our findings, we seek to provide tools and necessary information for further development of A . succinogenes as a platform for bioproduction of succinic acid and to illustrate the importance of diligent and long-term observation when working with non-model bacteria.",
"conclusion": "Conclusion The findings reported in this work include vital information for researchers seeking to develop A . succinogenes as a biological platform. A . succinogenes , while a highly interesting bacterium for bioproduction purposes, is not well characterized. A shift in production capabilities following a standard practice for storage is a crucial piece of information for anyone working with this non-model species. In sharing this phenomenon, which has not previously been reported, we have brought to light an area of opportunity for further development of A . succinogenes as a stable and useful strain for SA bioproduction. This work also disseminates information more broadly applicable to non-model bacteria research in general. The development of the inducible promoter system p100i for A . succinogenes demonstrates a strategy that could be highly useful in synthetic biology tool development for other non-model bacteria. The described approach for increasing the dynamic range of the inducible lac system could be specifically tailored for other organisms of interest. The loss of SA production can also apply to non-model research in general by serving as a cautionary tale. In research involving non-model organisms, the lack of characterization and long-term studies can lead to unexpected challenges. Such organisms with unique traits can be full of surprises and we propose that careful observation over time should be included in studies seeking to add to their characterization. Specifically, groups working in non-model organisms should focus on their preservation processes and how they could affect phenotype. Taking this into account at the initiation of a project could advance the pace of work within potentially powerful organisms by avoiding “rabbit holes,” like the one we have shared here. The hurdles to developing non-model bacteria are worth overcoming. As has been seen in other non-model systems, time, effort, and innovative solutions have been able to advance work within organisms of interest [ 5 , 6 ]. By sharing both exciting developments as well as pitfalls, the challenges of non-model systems can be overcome to unlock unique and promising capabilities for use as bio-platforms.",
"introduction": "Introduction Recent research endeavors have turned to generating useful chemicals from biological platforms as an environmentally responsible alternative to non-sustainable sources [ 1 , 2 ]. Bioproduction of industrially important chemicals can utilize organic and renewable feedstocks as nutrient-sources for microbial fermentation using metabolically engineered strains for optimized production. Examples of bioproduction success stories include the production of artemisinin [an anti-malaria drug) from engineered yeast [ 3 ] and hydrogen from engineered E . coli [ 4 ]. Non-model organisms are becoming increasingly interesting bioproduction platforms as they would expand the range of metabolic capabilities potentially harnessed for bioproduction purposes. Specific characteristics that would make an organism a good biological platform include native abilities to degrade sugar polymers, utilize renewable feedstocks to produce biochemicals of interest, and grow in challenging environments [ 5 ]. These unique characteristics that can be found in non-model microbes go hand-in-hand with unique challenges. The limited characterization of non-model organisms can raise issues when utilizing synthetic biology tools in predictable ways, elucidating effective metabolic engineering strategies, and understanding complex regulatory behaviors. Advances in computational tools to harness omics data and synthetic biology have made it possible to begin development of non-model organisms as bioproduction platforms. In fact, a recent review highlights many success stories of how challenges of working with non-model organisms have been overcome to unlock their unique potential [ 6 ]. Examples include the identification and incorporation in centromeric regions to solve the problem of low plasmid maintenance in the lipogenic and unconventional yeast Yarrowia lipolytica [ 7 ] and the modification of CRISPR/Cas9 plasmid system to reduce problematic recombination events in non-model actinobacteria producers of diverse natural products [ 8 ] among many others. These innovative solutions can serve as inspiration for work in other non-model organisms, such as Actinobacillus succinogenes 130Z. A . succinogenes 130Z is a Gram-negative, biofilm-forming, capnophilic, anaerobic and non-model bacterium identified as a potential bioproduction platform for succinic acid (hereafter SA) [ 9 ] and could also be developed for other products such as itaconic acid or fumarate. Here we target production of SA; an organic acid that can serve as a precursor for many chemicals used in the production of various commodities, including biodegradable plastics, active pharmaceutical agents, and textiles [ 10 – 12 ]. It has been predicted that bioproduction of SA from complex sugar sources could become the primary mode of production, eventually replacing current unsustainable methods that rely on declining petroleum sources [ 13 – 15 ]. SA bioproduction is supported by A . succinogenes’ ability to utilize both C5 and C6 sugars derived from cellulosic biomass [ 9 , 16 ] and its unique metabolic pathway which includes a truncated TCA cycle resulting in naturally high production of SA [ 17 ] without demonstrating product inhibition [ 16 ]. This bacterium is a biosafety level 1 organism meaning it could be readily incorporated into any industrial facility. To this date, A . succinogenes -driven SA production has reached a yield of 94% (w/w) from glucose [ 16 , 18 ] yet has a theoretical yield of 121% (w/w) from glucose [ 19 ]. It has also been demonstrated to grow robustly on corn stover hydrolysate which contains chemicals that can inhibit microbial growth [ 20 ]. This indicates that this bacterium could be an efficient SA producer through its ability to utilize the carbon in hydrolysate without requiring extensive preprocessing. It has been noted that growth condition optimization is not sufficient to obtain maximum SA levels [ 17 ], therefore, increasing SA production further will require other strategies such as metabolic engineering using synthetic biology tools, few of which exist for this non-model organism. Previous studies have shown strategies employing endogenous promoters [ 21 ] and gene-knock out methods [ 21 – 23 ], but as of yet, exogenous promoters have not been tested or characterized in A . succinogenes and no specific inducible promoter has been designed for this bacterium. It is well-known that development of promoters, specifically inducible promoters that can be turned on and off, is one of the easiest and most effective ways to control gene expression [ 24 ]. Hence, a wider range of available tools would allow for further fine-tuning of A . succinogenes ’ metabolism for maximizing SA production. To this end, here we share a case study of both advancements and challenges of working with A . succinogenes for SA production. Several steps were taken prior to engineering A . succinogenes to increase SA production, including performing small-scale growth studies, identifying effective selection antibiotics, and characterizing and developing synthetic biology tools. We show characterization of 22 constitutive promoters using green fluorescent protein and a flavin-binding fluorescent protein demonstrating a 260-fold range of expression from the weakest to strongest promoter. Additionally, we present characterization of the commonly used inducible lac system from E . coli and our development of a novel inducible system demonstrating a 481-fold dynamic range following a design strategy that could be applied and tailored to other non-model bacteria of interest. While the progress toward a synthetic biology toolkit for A . succinogenes is an important development, we also find SA production being lost over time in the working stock of A . succinogenes . This unexpected fermentation shift is yet to be overcome; however, we believe that both the progress and the challenges shared here could aid in future development of A . succinogenes as a more stable and efficient producer of SA. These results could simultaneously inspire researchers working in other industrially interesting non-model organisms to adopt practices of more long-term observation. This would benefit not only the stakeholders (i.e., bioprocessing industry and related agricultural markets) but also clear smoother paths for bioproduction efforts using other non-model microbes.",
"discussion": "Results and discussion Growth curve Identifying A . succinogenes’ growth phases (lag, exponential, and stationary) is important as some molecular biology methods (e.g. electroporation [ 25 ]) require their application within certain growth phases. In literature, growth conditions have been described in 500 mL flasks [ 26 ], 500 mL Duran bottles [ 27 ], bioreactors [ 18 , 21 , 26 , 28 ], and test tubes [ 29 ]; however, there has yet to be a reported growth curve showing the growth phases that are important for small scale engineering studies. A growth curve for A . succinogenes was generated by fitting a logistic model to OD 600 measurements taken at 30-minute intervals over the course of a 10-hour growth period. Results demonstrated a 2-hour lag phase, followed by a 6-hour exponential growth phase after which the cells entered stationary phase (S1 Fig in S1 File ). Early exponential phase, a key point for transformation of the bacterium via electroporation [ 25 ], was determined to be between hour 2 and 4 and at 0.4–0.6 OD 600 . Antibiotic screening Another crucial aspect for developing synthetic biology tools is effective selection antibiotics. Screening of standard antibiotics is needed to provide options that enforce plasmid maintenance for tool testing. Cultures of A . succinogenes were grown in the presence of kanamycin (50 μg/mL), tetracycline (10 μg/mL), ampicillin (100 μg/mL), gentamicin (15 μg/mL), spectinomycin (50 μg/mL), or chloramphenicol (34 μg/mL). Antibiotic concentrations were selected within the ATCC recommended concentration range for plasmid maintenance in bacteria containing mid-range plasmid copy number. Previous work with A . succinogenes shuttle vectors demonstrated low to medium copy number [ 30 ], therefore concentrations within the guidelines for mid-range copy numbers should be sufficient. OD 600 was measured at 2, 4, 6, and 24 hours. Fig 1 shows the efficacy of each antibiotic displayed as percent growth repression (Materials and Methods). Although spectinomycin and ampicillin both eventually inhibit growth of this fast-growing bacterium equivalently to the other tested antibiotics, neither took effect until after two hours. The delayed response to spectinomycin may be due to slow uptake, which is possible when using aminoglycoside class antibiotics in anaerobic conditions [ 31 ]. Similarly, the slow response to ampicillin may be due to difficulty passing through the cell wall, which can be seen in Gram-negative bacteria [ 32 ]. Although wild-type A . succinogenes cells were eventually killed, using ampicillin for selection posed a problem when selecting successfully transformed colonies of this biofilm-forming bacterium. Resistance to ampicillin is achieved by excretion of β-lactamase which breaks open the antibiotic’s β-lactam ring [ 33 ]. It is possible that cells containing the plasmid could create an environment for the non-transformed cells to keep growing by excreting the enzyme into the growth medium, therefore making selection difficult. Based on these findings, kanamycin, tetracycline, chloramphenicol, and gentamicin are recommended as selection markers in A . succinogenes . 10.1371/journal.pone.0245407.g001 Fig 1 Antibiotic screening. Antibiotic in liquid medium with wild type A . succinogenes shown as percent repression of normal growth. Error bars represent one standard deviation. Constitutive promoter library To enable control of transcription in A . succinogenes , 22 constitutive (always expressing) promoters were characterized. The set of promoters included P lac , a promoter native to E . coli [ 34 ]; P pcka , a promoter native to A . succinogenes [ 21 ]; and the family of Anderson promoters, synthetic promoters that were developed in E . coli [ 35 ]. The Anderson promoter library and the Lac operon’s promoter were chosen since they have been shown to function well in multiple bacteria [ 36 – 40 ]. A major goal of this project was to investigate the use of synthetic biology tools that would be less likely to demonstrate cross talk with native genetic components in A . succinogenes [ 38 ]. Characterization of these orthogonal tools within A . succinogenes was necessary as promoters often do not behave the same across different species, which can be seen in the cyanobacterium Synechocystis sp. 6803 [ 38 ]. For example, in Synechocystis , promoter BBa_J23112 was stronger than BBa_J23100 whereas in E . coli , BBa_J23100 produced the strongest expression. Furthermore, P lac was not inducible with IPTG in the cyanobacterium. As shown in Fig 2A , each promoter was inserted into the plasmid SSBIO-AS001 upstream of the modified jellyfish A . victoria green fluorescence protein gene ( gFPuv ) [ 41 ]. Transformation of the plasmids into A . succinogenes created strains sAS100 –sAS122 (S5 Table in S1 File ) and normalized expression (Materials and Methods) is shown in Fig 2B . To compare the relative expression of the Anderson promoter library in A . succinogenes with activity in E . coli , average expression values in A . succinogenes were divided by the highest expressing promoter (BBa-J23100) thus setting the maximum expression to 1. These values were compared to reported relative expression values in E . coli [ 35 ], which were calculated in the same way, as can be seen in Fig 2C . Findings demonstrated that maximal and minimal expressing promoters were the same in both bacteria however, relative expression was not equivalent across the entire promoter set. For instance, BBa_J23119 and BBa_J23100 were expressed similarly in E . coli while there was a drastic difference in expression of the two promoters in A . succinogenes , revealing unique sensitivities between the two bacteria to sequence variations at different locations within the promoters. A look at how the expression varies within the promoter set reveals a pattern that is evident in both E . coli and A . succinogenes . A guanine instead of a thymine at the position -12 appeared to hinder expression. This location falls within the -10 hexamer region and the decreased expression may be due to a lower affinity of polymerase binding. Aside from that one consistency, there is not a clear pattern of how the promoter sequence is tied to expression changes, thus reiterating the importance host-specific characterization. A second reporter gene, flavin-binding fluorescent protein [ 42 ], hereafter fbfp , was inserted in place of gFPuv and was tested under the control of a mid-range Anderson promoter (BBa_J23111) and the native promoter (P pcka ). FbFP was used because the protein can fold in anaerobic conditions [ 42 ] unlike GFPuv which requires oxygen [ 43 ]. This allowed for fluorescent measurements to be taken immediately after culturing and removed any variation that may have been introduced by the aeration process used when measuring GFPuv expression. Results showed that BBa_J23111 expressed both GFPuv and FbFP approximately 4 times stronger than the native promoter P pcka (4.49 and 4.29 respectively), demonstrating consistently stronger expression with the synthetic promoter. Finally, to determine the range of expression across all tested promoters in A . succinogenes , promoters showing no expression were discarded and the remaining 15 were compared to the lowest expressing promoter (BBa_J23105) showing a relative range of 260-fold. The Anderson promoters demonstrate a significantly greater range of expression (up to 2,547-fold) in E . coli [ 35 ] (verification shown in S2 Fig in S1 File ). A possible explanation is that the Anderson promoters were designed from E . coli ’s consensus sequence (labeled as BBa_J23119 in the Anderson promoter set). This means that minor changes were made to the -10 and -35 hexamer regions of the optimum promoter sequence for transcription within E . coli . In contrast, A . succinogenes ’ consensus sequence has not been determined. While E . coli and A . succinogenes share many characteristics, there may be variation within the replication machinery, such as differences in sigma factors [ 44 ], which could account for the lower range of expression observed in A . succinogenes . 10.1371/journal.pone.0245407.g002 Fig 2 Characterization of 22 constitutive promoters in Actinobacillus succinogenes 130Z. (A) Schematic of SSBIO-SA001 expression system. (B) GFPuv expression normalized by absorbance and background control (Materials and Methods). Error bars represent one standard deviation. (C) A comparison of relative expression of the Anderson promoters in A . succinogenes and E . coli . For both bacteria, relative expression was calculated by dividing all values by normalized expression from the strongest promoter (BBa_J23100). Characterization of the inducible P lac promoter While constitutive promoters are useful tools for setting constant gene expression rates, metabolic engineering often requires promoters that can respond to external signals [ 45 ]. The lac operon from E . coli [ 34 ] is an inducible system that includes the promoter P lac flanked by operator regions that bind to the repressor protein, LacI. When LacI is bound, transcription is turned off via steric hinderance; however, an inducer molecule, isopropyl β-D-1-thiogalactopyranoside (hereafter IPTG), can bind to LacI and prevent repression of transcription. Therefore, varying levels of IPTG can tune expression of genes under control of P lac . To characterize this inducible system within A . succinogenes , the repressor protein’s gene, lacI , and its native promoter were included with all the same components as SSBIO-AS001, creating SSBIO-AS003 ( Fig 3A ). Transforming A . succinogenes with the plasmid created strain sAS124. Performance of sAS124 induced at 0 and 5 mM IPTG was compared to both wild type A . succinogenes and strain sAS120 containing the constitutive system with P lac . Growth was compared across IPTG concentrations and was shown to be consistent (S3 Fig in S1 File ). As can be seen in Fig 3B , expression in sSA124 at 0 mM IPTG was not statistically different than wild type background fluorescence and expression in sSA124 at 5 mM IPTG was not statistically different than sAS120. Cultures were grown at various concentrations of IPTG within the range of 0 to 5 mM and expression was measured. Visualization on a logarithmic scale showed a graded response ( Fig 3C ). While the change in expression from the deactivated to activated state of the inducible system was only 90-fold, the on-state matched the expression level of constitutive P lac , demonstrating complete induction. Additionally, the system did not show leakiness, as no GFPuv expression was observed in the absence of IPTG. While the range of control is limited by the relatively low maximum level of expression of P lac within A . succinogenes when compared to other constitutive promoters (see Fig 2B ), the binary on and off states make this system promising for development within A . succinogenes . 10.1371/journal.pone.0245407.g003 Fig 3 Characterization of strain sAS124 containing SSBIO-AS003 using GFPuv as the reporter protein. (A) Schematic of the expression system used in SSBIO-AS003. (B) Comparison of on and off states of sAS124 at 0 and 5 mM IPTG with wild type A . succinogenes and strain sAS120. Values are normalized by absorbance (Materials and Methods). (C) Induction of sAS124 at IPTG levels ranging from 0 to 5 mM. Values are normalized by absorbance and wild-type (Materials and Methods). All error bars represent one standard deviation. Development of a stronger inducible promoter: P100i To create an inducible system for A . succinogenes with a larger range of expression, the strongest constitutive promoter (BBa_J23100) was added to SSBIO-AS003 in place of the core P lac , sequence creating SSBIO-AS004. In the constitutive system, BBa_J23100 expressed GFPuv ~10 times stronger than P lac and was predicted to set a higher maximum level of expression for the inducible system. The design strategy followed work in cyanobacterium [ 45 , 46 ] and can be seen in Fig 4A . Due to the differences in length of the core promoter between P lac (36 bp) and BBa_J23100 (35 bp), each possible nucleotide was inserted on the 5’ end of the -35 region of BBa_J23100 (hereafter called position -36). Position -36 was chosen to keep the spacing between the operator sites O1 and O3 as well as between the -10 region and the transcription start site equivalent for the new promoter and P lac . As can be seen in Fig 4B , there was significant variation among the four versions (strains sAS125-sAS128). A cytosine allowed for the greatest expression level whereas guanine and adenine showed decreased expression and thymine showed the least expression. Expression tests in E . coli revealed the same pattern, suggesting that the single nucleotide was crucial for some aspect of transcription. Sequences upstream of the -35 hexamer can have various regulatory effects due to interactions with transcription factors [ 47 ]. For example, the Cyclical-AMP receptor protein (CRP), which enhances polymerase binding, has a binding site in the lac system upstream of the -35 hexamer and improves transcription efficiency. It is possible that variations at the -36 site may be changing the binding affinity for CRP. Further exploration of A . succinogenes replication machinery will need to be conducted to elucidate the variation caused by the -36 site residues. 10.1371/journal.pone.0245407.g004 Fig 4 Characterization of strain sAS125 containing SSBIO-AS004 using GFPuv as the reporter protein. (A) Schematic of the expression system used in SSBIO-AS004 showing strategy of where to include the extra nucleotide to make size and spacing equivalent. (B) Comparison of expression variation due to the -36 nucleotide in both A . succinogenes and E . coli normalized by absorbance and respective wild type (Materials and Methods) at 0 and 1 mM IPTG. (C) Comparison of on and off states of sAS125 at 0 and 5 mM IPTG with wild type A . succinogenes and strain sAS100. Fluorescence values are normalized by absorbance (Materials and Methods). (D) Induction of sAS125 at IPTG levels ranging from 0.002 to 5 mM. Fluorescence values are normalized by absorbance and wild-type. All error bars represent one standard deviation. Performance of sAS125, containing the cytosine -36 residue, and which is hereafter labeled p100i, induced at 0 and 5 mM IPTG was compared to both wild type A . succinogenes and strain sAS100 containing the constitutive system with BBa_J23100. As can be seen in Fig 4C , expression in sSA125 at 0 mM IPTG was not different than wild type and expression in sSA125 at 5 mM IPTG was not different than sAS100. These findings confirmed that p100i was demonstrating a non-leaky off-state and complete induction. Cultures were grown at various concentrations of IPTG within the range of 0 to 5 mM. Visualization on a logarithmic scale showed a graded response ( Fig 4D ) and 481-fold dynamic range. The non-leaky nature of this inducible system is unique as even E . coli shows leakiness of basal expression [ 48 ], making this a very exciting development towards A . succinogenes metabolic engineering. Such a tool could be very useful for tuning metabolic gene expression within this organism. Loss of succinic acid production At this stage, we sought to test the effect of the presence of the plasmids on the production of SA and discovered a decrease in production not only present in the transformed strains, but also in the wild type used for comparison. Fig 5A shows the SA production loss in the working strains at this time point. This loss is presented in relation to fermentation measurements taken in wild type A . succinogenes at the beginning of the project (approximately 10 months before synthetic biology toolkit development) and also in relation to a brand-new strain purchased after the loss was realized. What can be seen is that the initial fermentation results and the results from the freshly purchased strain showed comparable levels of SA production after 24 hours. Here we cannot compare the additional organic acids (lactic acid, formic, acid, and acetic acid) because those were not included in the first set of measurements taken in the lab. The wild type strain that had been frozen and used as working stock in the lab for 10 months showed much lower SA production and also an increase in lactic acid. This unsettling finding prompted further investigation. The initial hypotheses were either contamination or mutation causing the decrease in SA production, both of which were tested by sequence comparisons between producing (hereafter SA(+)) and non-producing (SA(-)) strains. Using primers for 16S rRNA, sequencing of the SA(-) strain revealed a 99% match with A . succinogenes ’ reference genome (GCA_000017245.1), making contamination an unlikely cause. Whole genome comparisons between producing and non-producing strains revealed no major mutations, but one small, 5 nucleotide deletion in SA(-) at position 731146 in an intergenic region and a single nucleotide polymorphism (A in SA(+) and reference, G in SA(-)) at position 1004969 at the 5’ end of ASUC_RS04870 ( Fig 5B ). Investigation into these mutations revealed the SNP had been previously shown to have no effect on SA production [ 49 ]. While the deletion would have to be investigated to completely rule out mutation as the cause for the loss of SA production, such a minor difference between the two genomes in an intergenic region suggests there may be a better explanation. 10.1371/journal.pone.0245407.g005 Fig 5 Findings related to succinic acid production loss in A . succinogenes . (A) Comparison of organic acid fermentation profiles between A . succiongenes working stock at the beginning of use in the lab (labeled 1 on the x-axis), ten months later (labeled 2), and a newly purchased strain (labeled 3) after 24 hours growth. Data was not collected for lactic acid, formic acid, or acetic acid in the first fermentation in the lab (labeled 1). (B) A . succinogenes genome map indicating positions of the indel mutation (loss of 5 nts) and SNP mutation (A->G) shown to be different in the SA(-) strain. (C) Production profiles of wildtype, SA(+) A . succinogenes after 30-hour fermentation following storage in DMSO, sucrose, and glycerol and being subjected to 10 freeze/thaw cycles. (D) GFP expression data in transformed SA(+) and SA(-) strains under the control of BBa_J23100 and p100i. Glucose (Glu), succinic acid (SA), lactic acid (LA), formic acid (FA), acetic acid (AA). All error bars represent standard deviation. Since the loss of SA production occurred after several months, one factor may be storage stress. Freeze-dried A . succinogenes cells were purchased from ATCC (ATCC 55618), resuspended in liquid culture, and frozen at -80°C. Cryopreservation at -80°C has been shown to preserve organisms like E . coli for years [ 50 ] and can be conducted using a variety of cryo-protectants to avoid water crystallization and subsequent cell damage [ 51 ]. For this study, A . succinogenes cells had been stored in a final concentration of 20% glycerol as the cryo-protectant and no other cryo-protectants had been tested. To see if a different cryoprotectant would prevent fermentation shifts, aliquots of a newly purchased SA(+) strain was stored in various cryoprotectants including the intracellular protectants glycerol (20%) and DMSO (5%), and the extracellular protectant sucrose (0.15M). Aliquots were then subjected to 10 freeze-thaw cycles to mimic use in the lab and SA fermentation at 30 hours was measured. The findings are shown in Fig 5C and indicate there is some difference in optimality of cryoprotectant used, with both DMSO and sucrose showing better protection than glycerol evidenced by maintenance of SA production. Cells stored in glycerol show the pattern of decreased SA and increased lactic acid that we saw in the old strains used in the lab. However, there was not a complete loss of SA production and so this was not completely sufficient to explain the shift in fermentation profile seen after 10 months. In addition to investigating cryo-protectant effects, there are other storage strategies that could be tested. For bacterial cultures, ATCC utilizes both freeze drying and cryopreservation in the vapor phase of liquid nitrogen at -130°C [ 50 ]. These strategies are alternatives that could potentially better preserve A . succinogenes over time. At this point, a new SA(+) strain from ATCC was transformed with BBa_J23100 and p100i for further comparisons between SA(+) and SA(-) strains. These promoters were chosen due to the high expression levels of both and the tight inducibility of p100i. These notable characteristics were used to spot check if the developed tools would function the same when A . succinogenes produced SA. For the induced expression test, we chose to induce p100i at 0 and 1mM IPTG to see if the tool showed the expected “off” and “on” states respectively. Expression tests revealed that the differences between SA(+) and SA(-) strains extended to how the synthetic biology tools worked. As seen in Fig 5D , the tools were much less effective in the SA(+) strain with both BBa_J23100 and p100i showing much lower expression and p100i losing inducibility. Both promoters produced equivalent expression, with or without IPTG, suggesting that the inducible promoter was not turned off in this system and was operating at maximum, albeit low, expression. We did not try higher levels of IPTG since this showed the expression was already at the maximum possible. This finding adds to the picture of what is happening. Not only are there changes in overflow metabolism, but also changes in the expression of genes on a plasmid. This suggests that gene regulators play a role in the phenotypes of the different strains. Future work could be done to characterize the full set of promoters in an SA(+) strain, however, the underlying causes of the phenotypic changes should first be addressed. Future work would include long-term studies investigating effects of storage conditions to reveal environmental components contributing the loss of SA production in A . succinogenes . Additional studies should include transcriptomics to elucidate the underlying shifts in gene expression that cause A . succinogenes to change from SA(+) to SA(-). We hypothesize a transcriptomic comparison between SA(+) and SA(-) will reveal differential gene expression related to sigma factors. Previous studies have shown very drastic fermentation profile changes linked to sigma factor switching in bacteria [ 52 , 53 ]. Such patterns revealed in A . succinogenes could provide information on how SA production changes in this non-model bacterium long-term. It could also be helpful in pinpointing which regulators are key in how the developed synthetic biology tools are expressed. Identifying the factors contributing to both the loss of SA production and the change in the developed tool efficacy could reveal potential interventions that could prevent SA production loss, possibly recover lost SA production, or aid in making the tools more useful in the presence of SA production. This could create a more stable strain of A . succinogenes and boost its usefulness as a biological platform for bioproduction."
} | 8,682 |
29104570 | PMC5655573 | pmc | 8,024 | {
"abstract": "Flax dew-retting is a key step in the industrial extraction of fibers from flax stems and is dependent upon the production of a battery of hydrolytic enzymes produced by micro-organisms during this process. To explore the diversity and dynamics of bacterial and fungal communities involved in this process we applied a high-throughput sequencing (HTS) DNA metabarcoding approach (16S rRNA/ITS region, Illumina Miseq) on plant and soil samples obtained over a period of 7 weeks in July and August 2014. Twenty-three bacterial and six fungal phyla were identified in soil samples and 11 bacterial and four fungal phyla in plant samples. Dominant phyla were Proteobacteria, Bacteroidetes, Actinobacteria, and Firmicutes (bacteria) and Ascomycota, Basidiomycota, and Zygomycota (fungi) all of which have been previously associated with flax dew-retting except for Bacteroidetes and Basidiomycota that were identified for the first time. Rare phyla also identified for the first time in this process included Acidobacteria, CKC4, Chlorobi, Fibrobacteres, Gemmatimonadetes, Nitrospirae and TM6 (bacteria), and Chytridiomycota (fungi). No differences in microbial communities and colonization dynamics were observed between early and standard flax harvests. In contrast, the common agricultural practice of swath turning affects both bacterial and fungal community membership and structure in straw samples and may contribute to a more uniform retting. Prediction of community function using PICRUSt indicated the presence of a large collection of potential bacterial enzymes capable of hydrolyzing backbones and side-chains of cell wall polysaccharides. Assignment of functional guild (functional group) using FUNGuild software highlighted a change from parasitic to saprophytic trophic modes in fungi during retting. This work provides the first exhaustive description of the microbial communities involved in flax dew-retting and will provide a valuable benchmark in future studies aiming to evaluate the effects of other parameters (e.g., year-to year and site variability etc.) on this complex process.",
"discussion": "Discussion Microbial identification and retting parameters Previous studies using culture-based approaches and non-HTS metabarcoding have identified different bacteria and fungi phyla present during retting including Actinobacteria, Firmicutes, Proteobacteria (bacteria), and Ascomycota and Zygomycota (fungi) (Lanigan, 1950 ; Rosemberg, 1965 ; Brown, 1984 ; Sharma, 1986a , b ; Donaghy et al., 1990 ; Henriksson et al., 1997 ). Our results obtained using metabarcoding coupled with HTS not only identified these phyla, but also allowed the identification of new phyla not previously associated with dew-retting. Overall we identified 95 bacteria and 215 fungi species in dew-retted flax straw (plant) samples. HTS metabarcoding has been recently used to investigate bacterial (but not fungal) population dynamics in water-retted flax (Zhao et al., 2016 ). A comparison of relative abundances of the major bacterial phyla identified indicates that water retting is very different from dew-retting, despite the fact that the same lignocellulosic material is being degraded. Major phyla identified during water-retting were Firmicutes (genus Clostridium) and Proteobacteria (genera Azotobacter and Enterobacter). In contrast, Firmicutes were only present in low abundance during dew-retting and Azotobacter were absent. These differences can be most likely related to the anaerobic environment of water-retting compared to the more aerobic environment of dew-retting. Indeed, Clostridium is an obligate anaerobe and is known to be an agent of water-retting (Donaghy et al., 1990 ; Tamburini et al., 2003 ). Phyla, identified in our study and not previously associated with flax dew-retting, included, for the bacteria, Acidobacteria, Bacteroidetes, CKC4, Chlorobi, Fibrobacteres, Gemmatimonadetes, Nitrospirae and TM6; and for the fungi, Basidiomycota and Chytridiomycota. The Bacteroidetes phylum has been associated with cellulose degradation in agricultural soils (Schellenberger et al., 2010 ) and was previously detected in hemp dew-retting (Ribeiro et al., 2015 ) and flax water-retting (Zhao et al., 2016 ). Our observation of this phylum could indicate that it is also involved in flax dew-retting. Basidiomycota are linked to plant cell wall degradation in different ecosystems (Baldrian et al., 2008 ; Schneider et al., 2012 ; Kuramae et al., 2013 ; Voříšková and Baldrian, 2013 ; Rytioja et al., 2014 ) and were also detected in hemp dew-retting (Ribeiro et al., 2015 ). Although the observation that new bacterial phyla (except for the Bacteroidetes) and fungal phyla represent less than 2% of the whole microbiota might suggest that they are not involved in the retting process, some of these phyla are related to microorganisms characterized as biomass degraders in previous studies (Zhao et al., 2014 ). This observation, together with the fact that low abundance OTUs can still contribute to the decomposition of plant matter (Baldrian et al., 2012 ) indicates that these phyla should not be ignored during the study of dew-retting. A number of parameters potentially affecting microbial population structure during retting were examined. It is commonly admitted by farmers that the maturity of flax plants has a direct impact on the retting time and influences the choice for the pulling (up-rooting) date. Generally, straw from younger plants (flowering/green capsule stage) rets more quickly than that of more mature plants (yellow/brown capsule stage). This is thought to be related to differences in cell wall composition (e.g., pectin/lignin modifications and/or deposition) and water content (Meijer et al., 1995 ; Day et al., 2005 ; Akin, 2013 ). Our results showing that there was no significant difference in microbial communities and colonization dynamics between the early vs. standard cultures would suggest that differences in retting time may indeed be related to differences in cell wall structure and not to population differences. Compared to litter decay that normally proceeds undisturbed, dew-retting is a semi-controlled process during which the straw swaths are turned by farmers to obtain a more uniform fiber separation. Our analyses revealed that this practice had a significant effect on both bacterial and fungal community membership and structure of the flax straw microbiome confirming a real microbiological effect of swath turning that probably contributes to a more uniform retting. Although our results indicated no significant correlation between measured climatic conditions (temperature and rainfall) and community structures during the retting period it is important to remember that our study was conducted within a single year. It is possible that significant variations in community structures may occur between different seasons and further work is necessary to clarify this point. Microbial dynamics During dew-retting the relative abundance of the Bacteroidetes phylum increases while that of the Protobacteria decreases. A similar dynamic also occurs during biodegradation of field biomass from different angiosperm species (e.g., Arundo donax, Eucalyptus camaldulensis , and Populus nigra ) suggesting, as might be expected, that similarities exist between the temporary dew-retting ecosystem and degradation of lignocellulose in the field (Ventorino et al., 2015 ). Interestingly, the bacterial dynamics of flax dew-retting appear to be closer to that of field lignocellulose degradation than to that observed during flax water retting where Protobacteria increased during retting (Zhao et al., 2016 ). In this latter case, the phylum Proteobacteria was mainly represented by the genera Azotobacter that increased during retting and (to a much lesser extent) Enterobacter that remained constant. For fungal phyla we observed an increase in the relative abundance of Ascomycota at the expense of Basidiomycota in contrast to the situation generally observed during both field and forest litter decomposition (Schneider et al., 2012 ; Kuramae et al., 2013 ; Voříšková and Baldrian, 2013 ). The observed increase of Ascomycota was due to the saprophytic Altenaria species (Dang et al., 2015 ) that has previously been linked to later stages of dew-retting (Brown et al., 1986 ). In contrast, Altenaria species are more abundant during initial stages of litter decay (Snajdr et al., 2011 ). Our results also indicated that C. herbarum and Epicoccum nigrum contributed to the increase in Ascomycota relative abundance. During this stage less recalcitrant components of the biomass (pectins, and hemicelluloses) are progressively degraded (Dilly et al., 2001 ). Contrary to litter decay, dew-retting is a semi-controlled process and the challenge is to limit degradation of major quality related polymers such as crystalline cellulose. In this context, changes in the relative abundance of Ascomycota vs. Basidiomycota could represent an interesting bioindicator of retting progress. More detailed information on population dynamics at different time points during retting was provided by analyzing the relative abundance of OTUs at different taxonomic rank (e.g., phyla, classes, or genus/species level). The most abundant bacterial OTU corresponded to Sphingomonas sp. that was present throughout most of the retting period in both early and standard cultures. Although Sphingomonas species have been previously identified during bamboo and hemp retting, as well as in forest litter microbiome, this is the first time they have been found in flax retting (Fu et al., 2011 ; Ribeiro et al., 2015 ) (Urbanová et al., 2015 ). These species are able to hydrolyze terminal non-reducing alpha-L-rhamnose residues in alpha-L-rhamnosides giving them the ability to degrade pectin (rhamnogalacturonan I and rhamnogalacturonan II) in the middle lamella (Hashimoto and Murata, 1998 ). Another Sphingomonas species, S. paucimobilis is also able to degrade lignin (Masai et al., 1999 ; de Gonzalo et al., 2016 ). The second most abundant OTU corresponded to P. rhizosphaerae , present during the early and medium retting stages but decreasing in latter stages. A number of Pseudomonas species have previously been associated with retting of different fiber plants (e.g., flax, hemp, jute, ramie) (Rosemberg, 1965 ; Munshi and Chattoo, 2008 ; Duan et al., 2012 ; Ribeiro et al., 2015 ). Pseudomonas sp. is considered as one of the most efficient lignin degradation bacterium (Shui Yang et al., 2007 ) and the genomes of both Pseudomonas putida and Pseudomonas aeruginosa contain genes encoding endoglucanases (Talia et al., 2012 ). Other abundant OTUs corresponded to Rhizobium, Pedobacter, and Flavobacterium that are known to show pectinase, cellulose, and hemicellulose activities (Mateos et al., 1992 ; McBride et al., 2009 ; López-Mondéjar et al., 2016 ). In addition, Pedobacter has also been identified during bamboo and hemp retting (Fu et al., 2011 ; Ribeiro et al., 2015 ) or forest litter degradation (Urbanová et al., 2015 ). In contrast to Sphingomonas and Pseudomonas, these organisms become more abundant toward the end of the retting period and could be associated with “over-retting” when the structural integrity of the fiber starts to be degraded. In contrast to the more evenly distributed abundance of the bacterial OTUs, fungal OTUs were dominated by one major species— C. herbarum —that rapidly increased during early retting. This species, as well as the third most abundant OTU ( E. nigrum ) are known to be common dew-retting agents and are believed to degrade cellulose (Brown, 1984 ). Of the other fungal OTUs, all have previously been associated with dew-/water-retting except for Itersonilia perplexans . Interestingly, our results also indicated that Alternaria alternata is present at the start of retting. Traditionally, the appearance of this species is used as a signal that retting is starting to go too far and that the swaths should be collected (Brown et al., 1986 ). Hydrolytic enzyme potential Prediction of hydrolytic enzymes potentially present during retting was performed by using PICRUSt (Langille et al., 2013 ). This software successfully predicts bacterial enzymatic activities represented in different databases (e.g., KEGG Ortholog, COGs, or CAZy). Overall, a large collection of enzyme activities targeting both the main backbones and side chains of the major polysaccharide polymers were identified. Based on OTU counts, ~38, 43, and 19 percent of the total hydrolytic enzyme potential targeted pectins, hemicelluloses, and cellulose, respectively. Despite the clear dynamics and significant changes in the straw microbiome these values remained constant throughout the retting period. Similar software does not exist for predicting fungal enzyme potential. This represents an important hurdle for obtaining a complete overview of the dew-retting process as fungi are major producers of extracellular hydrolytic enzymes (Schneider et al., 2012 ). Nevertheless, FUNGuild analysis showed that pathogenic taxa, present at the beginning of retting are progressively replaced by saprophytic fungi, more able to degrade lignocellulose. This change is most likely related to the fact that flax plants are still living when up-rooted. In conclusion, we have shown that HTS metabarcoding is a powerful technique for analyzing complex bacterial and fungal community dynamics during flax dew-retting that can be used to identify different factors affecting the microbiota and—potentially—fiber isolation and quality. However, these results were obtained on samples retted in 1 year and it will be necessary to validate these data over several seasons. The use of PICRUSt data allows a predictive study of potential bacterial hydrolytic activity but should be coupled in future studies with alternative meta-omics methods such as metatranscriptomic or metaproteomic coupled with metagenomics to facilitate the assembling with appropriate reference genomes (Schneider et al., 2012 ; Dai et al., 2015 ; Hesse et al., 2015 ; Kuske et al., 2015 ; Wu et al., 2015 ). Such an approach would not only allow confirmation of bacterial enzyme dynamics but would also enable identification of fungal enzymes involved in this process."
} | 3,595 |
29938165 | PMC6010908 | pmc | 8,026 | {
"abstract": "Abstract Marine macrofoulers (e.g., barnacles, tubeworms, mussels) create underwater adhesives capable of attaching themselves to almost any material. The difficulty in removing these organisms frustrates maritime and oceanographic communities, and fascinates biomedical and industrial communities seeking synthetic adhesives that cure and hold steadfast in aqueous environments. Protein analysis can reveal the chemical composition of natural adhesives; however, developing synthetic analogs that mimic their performance remains a challenge due to an incomplete understanding of adhesion processes. Here, it is shown that acorn barnacles ( Amphibalanus (= Balanus ) amphitrite ) secrete a phase‐separating fluid ahead of growth and cement deposition. This mixture consists of a phenolic laden gelatinous phase that presents a phase rich in lipids and reactive oxygen species at the seawater interface. Nearby biofilms rapidly oxidize and lift off the surface as the secretion advances. While phenolic chemistries are ubiquitous to arthropod adhesives and cuticles, the findings demonstrate that A. amphitrite uses these chemistries in a complex surface‐cleaning fluid, at a substantially higher relative abundance than in its adhesive. The discovery of this critical step in underwater adhesion represents a missing link between natural and synthetic adhesives, and provides new directions for the development of environmentally friendly biofouling solutions."
} | 366 |
19803470 | null | s2 | 8,027 | {
"abstract": "Many synthetic and natural peptides are known to self-assemble to form various nanostructures. During the self-assembling process, environmental conditions such as salt concentration, pH, temperature, and surface characteristics play a critical role by influencing intermolecular interactions, and hence the process of self-assembly. Here we studied the self-assembly of a genetically engineered protein polymer composed of silk-like and elastin-like repeats on a mica surface. Silk-elastin-like protein polymers (SELPs) consist of tandem repeats of Gly-Ala-Gly-Ala-Gly-Ser from Bombyx mori (silkworm) and Gly-Val-Gly-Val-Pro from mammalian elastin. At a very low polymer concentration of 1 mug/mL, SELPs self-assembled into nanofibrous structures on a mica surface. Examination using atomic force microscopy (AFM) and dynamic light scattering techniques showed that SELPs self-assembled into nanofibers in the presence of the mica surface but not in the bulk state. Ionic strength had a significant influence on nanofiber growth, indicating the importance of electrostatic interactions between the polymer and the mica surface. At low ionic strength, the kinetics of nanofiber growth showed that the mica surface effectively removed a lag phase by providing nucleating sites, facilitating nanofiber self-assembly of SELPs. Furthermore, self-assembly on additional substrates such as silicon and a hydrophobic pyrolytic carbon surface revealed that the charged hydrophilic surface provides the optimal surface to facilitate self-assembly of SELPs."
} | 386 |
32015848 | PMC6988560 | pmc | 8,028 | {
"abstract": "Abstract Alternative stable states are nontransitory states within which communities can exist. However, even highly dynamic communities can be viewed within the framework of stable‐state theory if an appropriate “ecologically relevant” time scale is identified. The ecologically relevant time scale for dynamic systems needs to conform to the amount of time needed for a system's community to complete an entire cycle through its normal range of variation. For some systems, the ecologically relevant period can be relatively short (eg, tidal systems), for others it can be decadal (eg, prairie wetlands). We explore the concept of alternative stable states in unstable systems using the highly dynamic wetland ecosystems of North America's Prairie Pothole Region. The communities in these wetland ecosystems transition through multiple states in response to decadal‐long climate oscillations that cyclically influence ponded‐water depth, permanence, and chemistry. The perspective gained by considering dynamic systems in the context of stable‐state theory allows for an increased understanding of how these systems respond to changing drivers that can push them past tipping points into alternative states. Incorporation of concepts inherent to stable‐state theory has been suggested as a key scientific element upon which to base sustainable environmental management.",
"conclusion": "9 CONCLUSIONS While stable‐state theory has typically not been applied to systems that undergo dynamic changes to variable environmental conditions, we show how the ideas presented within stable‐state theory can be applied to these dynamic systems if the normal range of community variation during a coherent period is considered to be the “stable state.” By doing so, one can then explore how community and environmental drivers, and tipping points during incoherent periods can work to cause state shifts that result in community changes outside of the bounds of the previous stable‐state community. Prairie‐pothole wetland ecosystems provide an example of shifting stable states within a highly dynamic system. The perspective gained by considering these dynamic systems in the context of stable‐state theory and the concept of multiplicity of ecosystem alternative stable states allow for an increased understanding of how they respond to changing community and environmental drivers during both coherent and incoherent periods. A better understanding of the domains of attraction and the community and environmental drivers that can push dynamic systems to alternative stable states will become increasingly important as changing climate and land‐use conditions across the globe threaten both stable and dynamic ecosystems without prejudice."
} | 678 |
31362392 | PMC6721167 | pmc | 8,029 | {
"abstract": "Simple Summary Dietary interventions aimed at reducing methane production may be influenced by other factors such as animal breed and feed efficiency (indicated by residual feed intake (RFI) status). We examined the rumen and fecal microbiota of Holstein and Jersey dairy cows with diverging RFI status fed diets differing in concentrate-to-forage ratio. Community differences seen in the rumen were reduced or absent in feces, except in the case of animal-to-animal variation, where differences were more pronounced. Understanding factors that influence methane production will be key to determining effective methane reduction strategies in the future. Abstract Identifying factors that influence the composition of the microbial population in the digestive system of dairy cattle will be key in regulating these populations to reduce greenhouse gas emissions. In this study, we analyzed rumen and fecal samples from five high residual feed intake (RFI) Holstein cows, five low RFI Holstein cows, five high RFI Jersey cows and five low RFI Jersey cows, fed either a high-concentrate diet (expected to reduce methane emission) or a high-forage diet. Bacterial communities from both the rumen and feces were profiled using Illumina sequencing on the 16S rRNA gene. Rumen archaeal communities were profiled using Terminal-Restriction Fragment Length Polymorphism (T-RFLP) targeting the mcrA gene. The rumen methanogen community was influenced by breed but not by diet or RFI. The rumen bacterial community was influenced by breed and diet but not by RFI. The fecal bacterial community was influenced by individual animal variation and, to a lesser extent, by breed and diet but not by RFI. Only the bacterial community correlated with methane production. Community differences seen in the rumen were reduced or absent in feces, except in the case of animal-to-animal variation, where differences were more pronounced. The two cattle breeds had different levels of response to the dietary intervention; therefore, it may be appropriate to individually tailor methane reduction strategies to each cattle breed.",
"conclusion": "5. Conclusions Changes in methanogen communities did not relate to differences in methane production, but the structure of the bacterial community was correlated with methane production. Community differences seen in the rumen are reduced or absent in feces except in the case of animal-to-animal variation, where differences were more pronounced. Therefore, feces samples are not representative of the differences seen in rumen communities and should not be used as proxies for the latter. Changes in the bacterial communities were observed with diet intervention and between breeds but not with differing RFI status. The two cattle breeds had different levels of response to the dietary intervention; therefore, it may be appropriate to tailor methane reduction strategies to each cattle breed individually.",
"introduction": "1. Introduction The contribution of dairy cattle greenhouse gas emissions to climate change has prompted research into the function and structure of the rumen microbiome [ 1 , 2 , 3 , 4 ]. The rumen contains a complex community of microorganisms including archaea, bacteria, fungi and protozoa that ferment ingested feedstuffs, providing nutrients for the host and also the by-product methane. Compared to the rumen, the hindgut microbiota, represented by the fecal microbiome, is poorly characterized, particularly by next-generation sequencing. Next-generation sequencing allows for comprehensive surveys of microbiomes both quickly and inexpensively by targeting the 16S rRNA gene. The fecal microbiome has differences from the rumen microbiome [ 5 , 6 ] but, like the rumen community, the fecal community is altered by changes in diet [ 7 ] and therefore may potentially show differences in relation to other factors as well, such as feed efficiency and breed. Thus, there is a need to investigate whether the microbiomes in both the rumen and in the feces are equally affected by different factors. The hindgut microbiota is also important for animal health and represents important sources of environmental contamination from feces [ 8 ]. Methane is predominately produced by methanogenic archaea residing in the rumen, from the products of rumen fermentation. Bacteria are the most numerous microbes fermenting feedstuffs in the rumen, thus both methanogen and bacterial populations are of interest when examining the influence of factors that might alter methane production. Dietary effects on the rumen microbiome and on methane emission traits are well established, but reports of individual cow effects [ 9 ], breed effects, and particularly the effects of interactions between diet and individual animals have been scarcely reported [ 10 ]. Residual feed intake (RFI) is the difference between the actual feed intake and the calculated expected feed intake. This can be taken as a measure of efficiency, with more efficient animals eating less than their calculated needs. Animals with a low RFI (high efficiency) have been shown to produce the same amount of methane per day (g of CH4/d) as high-RFI animals on the same diet, but have a higher methane yield (g of CH4/kg of dry matter intake (DMI)) due to the low-RFI cows having lower DMI [ 11 ]. Increased efficiency is also linked to lower methane emissions per kg of milk [ 12 ]. This led us to speculate that if an animal, already very feed efficient, would gain any further methane reduction from diet modifications. To elucidate this, it is important to examine the interaction of dietary intervention aiming at reducing enteric methane, in combination with cattle breed and the RFI status of the cows as a measure of feed efficiency. We hypothesize that the microbiomes in the rumen fluid and the feces would respond differently to dietary manipulation aimed at reducing methane, and also that the responses would be affected by breed and RFI status. The aims of the present study were therefore to investigate the microbiome of rumen content and fecal samples from two breeds of dairy cows (Holstein and Jersey), differing in RFI status and fed diets differing in the concentrate-to-forage ratio, and to test the validity of using a fecal sample (easy to obtain) as a proxy for microbial populations/activities in the rumen (hard to obtain).",
"discussion": "4. Discussion Residual feed intake groups did not differ in methane yield (discussed in Olijhoek et al. [ 10 ]), so it is not surprising that RFI status had no effect overall on the methanogen community. This finding is supported by a study in cattle by Zhou et al. [ 28 ], who also found RFI status had no effect on the overall methanogen population; likewise, Carberry et al. [ 29 ] reported no difference in the abundance of methanogens between RFI phenotypes. Nevertheless, the structure of the methanogen community, detected by examining DNA, does not always indicate differences in methane emission as this may be determined at the gene expression level rather than the community structure level [ 30 ]. In our case, breed but not diet had a significant effect on the methanogen community structure, but both breed and diet had a significant influence on the methane yield expressed as L/kg of DMI. However, only diet had an effect on methane production when expressed per kg of energy-corrected milk (ECM). Our results are in contrast to Carberry et al. [ 29 ] and Jeyanathan et al. [ 31 ], where diet affected the methanogen populations and Cersossimo et al. [ 32 ], where breed had no effect on methanogen populations. However, our results are in agreement with Kumar at al. [ 33 ], where diet had no influence on methanogen populations. The bacterial community plays an important role in methane emissions by producing the substrates for methanogenesis via the conversion of feed to fermentation products. In this study, the overall bacterial communities are dominated by Lachnospiraceae, Bacteroidales and Succinivibrionaceae, where Prevotellaceae is ranked 6th with only 6.7% of the sequences. This seems low as Prevotellaceae is usually the most dominant genus in the rumen [ 34 ]. This may reflect real differences in our experimental animals or biases in the sample handling and sequencing methodologies, but similar results were reported from animals in this herd by Zhu et al. [ 15 ]. Our samples were taken orally with a stomach probe, a method that allows rumen sampling from an animal that has not been surgically altered, and although this allowed fine feed particles to be collected, large solid digesta was omitted. The inclusion of solid feed particles is important for good representation of the rumen community as the majority of bacteria adhere to the feed particles [ 35 ]; however, it has been demonstrated that community composition of the ruminal liquid phase observed from the stomach probe technique is indistinguishable from those collected via rumen cannula [ 36 , 37 ]. Diet is known to have a prominent effect on the bacterial population structure [ 34 , 38 , 39 ] as this provides the substrates for bacterial growth and therefore determines selective pressure on the community. Diet had a large impact on the bacterial communities, showing a significant effect in both the rumen and the feces with both weighted and unweighted UniFrac measures ( Table 1 ). Diet also strongly affected the alpha diversity measures of both rumen and fecal communities ( Table S2 ). Weighted UniFrac distances take into consideration the number of sequences in each OTU and are suitable for showing changes in taxon abundance. They usually show shifts in the dominant taxa, whereas unweighted UniFrac distances are suitable for showing differences in community membership. The latter usually show the presence or absence of the less dominant taxa as it is unlikely in the gut environment that a dominant group will disappear altogether. Diet-related community differences were more pronounced for Holstein cows than for Jersey cows ( Figure 3 ) demonstrating differences in breed response to the diets. The bacterial community differed between Holstein and Jersey cows for both weighted and unweighted UniFrac measures in the rumen, but were only significantly different in the unweighted UniFrac measure in feces. This demonstrates that breed-related differences in the bacterial community are evident in the rumen; however, they are less pronounced in the feces, where they may only differ in the less dominant taxa. A previous study by Paz et al. [ 37 ], comparing the rumen communities between Holstein and Jersey cows, also reported community differences between breeds. Contrary to this, Bainbridge et al. [ 40 ] found that breed contributed to very few differences in the rumen community when comparing Holstein, Jersey and Holstein–Jersey crossbreds on the same diet. Few studies have looked at both rumen and fecal communities concurrently; however, one study, examining high- vs low-production dairy cattle, observed differences in the ruminal bacteria but not in the feces [ 41 ]. In another case, Dill-McFarland et al. [ 42 ] found the effect of animal age strongly influenced both the rumen and fecal bacterial communities, but in adult cows only the rumen communities were affected by diet. We found that both animal breed and diet affect the rumen community, where breed was only significant with the unweighted UniFrac in the fecal community. We also found that rumen communities have a much stronger correlation with rumen fermentation parameters (NDF digestibility, A:P ratio and methane production) than fecal communities. Bacterial communities associated with each animal were statistically different for the unweighted UniFrac in both rumen and feces, but only feces showed animal differences in the weighted UniFrac. These results indicate that the animal-specific microbes mostly comprise minor groups in the rumen, but animal-to-animal variation is more pronounced in fecal communities. Animal-specific variation in rumen bacterial communities is dependent on the animals chosen as it is significant in some studies [ 1 ] but not in other studies [ 43 ]. Therefore, examining the fecal communities may have an advantage when looking at animal differences. No differences were detected between the two RFI groups in either rumen or fecal bacterial communities ( Table 1 ). In addition, there was no correlation between the actual RFI values and either the rumen or fecal communities ( Table 2 ). Therefore, we cannot confirm our hypothesis that RFI status would correlate with changes in the microbial community. Without any effect of RFI status, we cannot determine whether cows that are more efficient would respond differently to dietary interventions aimed at reducing methane than less efficient cows. This study used animals from an experimental herd, simulating a commercial herd. Therefore, the genetic differences and differences in RFI were small and are comparable to those of the whole Danish Holstein and Jersey populations. The microbiome results reported here are in concordance with the lack of significant differences seen in methane production, rumen fermentation, and milk characteristics in connection with RFI, as reported by Olijhoek et al. [ 10 ]. The rumen bacterial community plays a significant role in NDF digestibility, VFA production, and methane emission. Moderate and significant correlations between rumen communities to the total tract NDF digestibility, rumen A:P ratio and methane yield per kg of DMI are evident, with mantel correlation tests ( Table 2 ). This suggests a link between the bacterial community and methane production. In accordance, Kittelmann et al. [ 44 ] also found that differences in rumen bacterial communities were linked to methane emissions. In the present study, correlations were weaker in the fecal communities compared to the rumen community. The fecal communities have a significant but weak correlation with NDF digestibility, rumen A:P ratio and methane production with a stronger correlation for the unweighted UniFrac. Overall, these results indicate that differences between taxonomic groups in the feces are smaller compared to those in rumen samples."
} | 3,547 |
30777812 | PMC6421345 | pmc | 8,030 | {
"abstract": "Two common classes of nitrogen-fixing legume root nodules are those that have determinate or indeterminate meristems, as in Phaseolus bean and pea, respectively. In indeterminate nodules, rhizobia terminally differentiate into bacteroids with endoreduplicated genomes, whereas bacteroids from determinate nodules are less differentiated and can regrow. We used RNA sequencing to compare bacteroid gene expression in determinate and indeterminate nodules using two Rhizobium leguminosarum strains whose genomes differ due to replacement of the symbiosis (Sym) plasmid pRP2 (strain Rlp4292) with pRL1 (strain RlvA34), thereby switching symbiosis hosts from Phaseolus bean (determinate nodules) to pea (indeterminate nodules). Both bacteroid types have gene expression patterns typical of a stringent response, a stressful environment and catabolism of dicarboxylates, formate, amino acids and quaternary amines. Gene expression patterns were indicative that bean bacteroids were more limited for phosphate, sulphate and iron than pea bacteroids. Bean bacteroids had higher levels of expression of genes whose products are predicted to be associated with metabolite detoxification or export. Pea bacteroids had increased expression of genes associated with DNA replication, membrane synthesis and the TCA (tricarboxylic acid) cycle. Analysis of bacteroid-specific transporter genes was indicative of distinct differences in sugars and other compounds in the two nodule environments. Cell division genes were down-regulated in pea but not bean bacteroids, while DNA synthesis was increased in pea bacteroids. This is consistent with endoreduplication of pea bacteroids and their failure to regrow once nodules senesce.",
"conclusion": "Conclusions (1) Against a general pattern of down-regulation of gene expression in bacteroids compared with free-living rhizobia, both bean and pea bacteroids showed increased expression of genes associated with nitrogen fixation and utilization of dicarboxylates, formate, amino acids and quaternary amines. The decreased expression of many genes may be associated with the increased expression of stringent response genes. (2) Gene expression patterns suggest that bean bacteroids were more limited for P, S and Fe than pea bacteroids, and the expression of cytochrome oxidase genes suggests that bean bacteroids are exposed to higher levels of oxygen than pea bacteroids. (3) Bacteroids in bean nodules expressed many genes whose products are predicted to be related to metabolite detoxification and export. (4) Bean bacteroids express high levels of phasin genes that are associated with storage of the large amounts of PHB that accumulate in bean nodules. (5) Pea nodules have strongly up-regulated genes associated with central metabolism and this is indicative of some fundamental differences in the use of the TCA cycle. (6) Surprisingly, pea bacteroids showed evidence for expression of nitrate and nitrite reduction enzymes. (7) Expression patterns of uptake transporters are indicative that bacteroids in pea and bean nodules are exposed to different sets of substrates specific to each nodule type.",
"introduction": "Introduction Rhizobia are a group of α- and β-proteobacteria forming symbiotic nitrogen-fixing nodules on legumes [ 1 ]. Legume nodulation is typically initiated by exchange of signalling compounds, with rhizobia attaching to root hairs and growing down plant-made infection threads into the root cortex [ 2 ]. Rhizobia are then endocytosed and surrounded by a plant-derived membrane (symbiosome membrane). The resulting structure, which resembles an organelle, is called a symbiosome [ 3 ], within which bacteria differentiate into bacteroids. N 2 reduced to ammonia is supplied from bacteroids to the plant in exchange for a carbon supply, mostly in the form of dicarboxylic acids, such as malate [ 3 ]. Bacteroids exist in a microoxic environment, essential for activity of the oxygen-sensitive nitrogenase [ 4, 5 ]. Nodules on phaseoloid legumes (including Phaseolus vulgaris ) are determinate with a transient meristem; the rhizobia do not terminally differentiate and nitrogen-fixing bacteroids can be cultured from mature nodules. In contrast, nodules formed on indeterminate nodules such as pea ( Pisum sativum ) maintain an active meristem and infection zone. In indeterminate nodules, growing infection threads release rhizobia into nodule cells; these bacteria endoreduplicate their genomes and terminally differentiate into pleiomorphic nitrogen-fixing bacteroids that cannot be cultured [ 6 ]. The main body of indeterminate nodules contains nitrogen-fixing symbiosomes [ 2, 7 ]. In legumes such as Medicago truncatula and Pisum sativum, belonging to the inverted repeat-lacking clade (IRLC), there are up to 600 genes which encode nodule-specific cysteine-rich (NCR) peptides [ 8–10 ] that induce bacteroid differentiation [ 11, 12 ]. Studies on bacteroid gene expression using transcriptomic techniques such as microarrays or RNA sequencing (RNA-Seq) have compared free-living cells with bacteroids from Rhizobium leguminosarum bv. viciae 3841 [ 13 ], Bradyrhizobium japonicum [ 14–16 ], Azorhizobium caulinodans ORS571 [ 17 ], Sinorhizobium NGR234 [ 18 ] and Sinorhizobium meliloti 1021 [ 19–21 ] (for a comprehensive review see [ 22 ]). Advances in RNA-Seq have allowed analysis of the transcriptomes of both plant and bacteroids in different zones of S. meliloti -infected Medicago truncatula nodules [ 23 ]. Our aim was to compare gene expression in determinate bean and indeterminate pea bacteroids. We used two R. leguminosarum strains that efficiently nodulate and fix nitrogen in bean or pea nodules. They differ due to the replacement of the symbiosis (Sym) plasmid pRP2 (in strain Rlp4292) with pRL1 (in strain RlvA34) but share a core genome, facilitating direct comparison of transcriptomes in bacteroids from determinate and indeterminate nodules.",
"discussion": "Results and Discussion Structure of Rlp4292 and RlvA34 genomes The shared genomes of Rlp4292 and RlvA34 comprise four replicons: a 4.7 Mb chromosome ( RHL0001 – 4710 ), 1 Mb plasmid A ( RHLa4712–5668 ), 594 kb plasmid B ( RHLb6570–6235 ) and 562 kb plasmid C ( RHLc6237–6762 ) (Fig. S1). The Sym plasmids encode many genes involved in symbiosis and nitrogen fixation ( Fig. 1 ). In Rlp4292, pRP2 is 430 kb with 433 genes (RHLp6764–7197) , while in RlvA34 pRL1 is 214 kb with 223 genes ( RHLv8000 – 8223 ). Although RlvA34 is a ‘synthetic strain’ made by introducing Sym plasmid pRL1, it is comparable to native strains, e.g. R. leguminosarum bv. viciae 3841, on pea plants grown without added nitrogen as measured by plant dry weight, acetylene reduction and 15 N 2 reduction [ 21, 36, 37 ]. Fig. 1. Scale genetic maps of Sym plasmids pRP2 [Rlp4292, 433 genes ( RHLp6764 – 7197 )] and pRL1 [RlvA34, 223 genes ( RHLv8000–8223 )]. Genes are coloured according to differential expression in bean and pea bacteroids. Genes up-regulated >10-fold in bacteroids are red; >2-fold up-regulated, orange; between 2-fold up-regulated and 2-fold down-regulated, yellow; >2-fold down-regulated, light blue; >10-fold down-regulated, dark blue. Exploded regions show the names of genes discussed in the text. The prefix for each gene name is shown in brackets within each replicon and the numbers printed inside the outer ring indicate the gene (e.g. on pRP2: RHLp7097 , nifB ). Data for this figure is given in Tables S6 and S8. Initial annotation of Rlp4292 and RlvA34 [downloaded from the JGI (Joint Genome Institute) database: https://img.jgi.doe.gov/ ] lacked many conventional gene names (over 2000 gene products labelled as hypothetical). Rlp4292 and RlvA34 share most homology at the nucleotide level with R. etli CFN42 [ 38 ], whereas genes from pRL1 show highest homology to Sym plasmid pRL10 in the pea-nodulating strain R. leguminosarum bv. viciae 3841 (Rlv3841) [ 39 ]. Annotations from CFN42 and Rlv3841 were used to improve annotation of Rlp4292 and RlvA34. Both pRP2 and pRL1 Sym plasmids encode nitrogen-fixation enzymes in nif and fix gene clusters. Among pRP2 genes directly involved in symbiotic nitrogen fixation, there are three predicted homologues of nodD , and two each of nodA and nifH (Table S3). The pseudogenes (Ψ) Ψ fixN (RHLp7176), Ψ nifB1 and Ψ nifB2 (RHLp7023 and RHLp7057), Ψ nifD (RHLp7132), and Ψ nifH (RLP7071) have inappropriately short predicted gene products (Table S3, Fig. 1 ) and are not considered further. Differential gene expression during growth of free-living Rlp4292 and RlvA34 Gene expression differences in Rlp4292 and RlvA34 grown under identical in vitro conditions must be due to their Sym plasmids or to mutations within their genomes; about 97 % of the common genes showed little (<2-fold) or no differences in expression (Table S4). Some common genes (0.3 %) were differentially expressed (>5-fold). In RlvA34, this included the following genes normally induced under iron limitation: RHLa5120 ( rpoI ); the vicibactin synthesis and uptake cluster RHLa5121–6 ( vbsLDAGSO ); the RHL2532–40 genes, including the hmuPSTU haemin uptake genes ( RHL2537–40 ) [ 40, 41 ]; and RHLa5475-7 encoding a FeCT (iron chelate family uptake) ABC transporter (Table S5. The RNA-Seq data revealed in RlvA34 (but not Rpl4292) a nucleotide (T) deletion in rirA , which encodes a repressor of iron-regulated genes [ 42 ]. The frameshift would change amino acid lysine 75 to leucine and lead to truncation of 80 amino acids from RirA (161 amino acids). We conclude that mutation of rirA caused up-regulation of this regulon of genes in RlvA34. The only genes expressed more strongly (>5-fold) in Rlp4292 than in RlvA34 were RLH2777 encoding a putative oxidoreductase and RHL4467 of unknown function (Table S5). The consistency of expression of shared genes in free-living cultures of Rlp4292 and RlvA34 justifies the validity of comparison of gene expression under symbiotic conditions, with the proviso that the RlvA34 carries a rirA mutation causing up-regulation of some iron-related genes. Differential expression of Sym plasmid genes in bean and pea bacteroids RNA sequence reads from Rlp4292 and RlvA34 bacteroids were compared with data from their respective free-living cells to generate normalized values for differential gene expression in bacteroids (Table S6). Fig. S2 shows the proportion of genes, by replicon, that are >2-fold differentially regulated. These data were heavily skewed, with most genes down-regulated, representing the ‘real’ nature of the gene expression in bacteroids, but not allowing accurate comparison of differential gene expression. Therefore, we applied DeSeq normalization to these data to allow calculation of differential gene expression (Table S7). Genes shown as differentially expressed in Table S7 show >5-fold normalized increases or decreases in RlvA34 or Rlp4292 bacteroids relative to the expression in free-living cultures of the same strain; we used this differential in our analyses described below (summarized in Figs 2 and 3 ). In this section, we will deal with differentially expressed Sym plasmid genes ( Fig. 2 ), and in the next section we will consider the genes on the common genome ( Fig. 3 ). Fig. 2. Summary of Sym plasmid genes differentially regulated in bacteroids. Expression data of Sym plasmid genes of pRP2 (433 genes) in bean bacteroids are given in Table S6 and for those of pRL1 (223 genes) in pea bacteroids in Table S8. Data for genes that are common (>80 % id) to both pRP2 and pRL1 (45 genes) are given in Table S9. Fig. 3. Summary of genes on the shared genome differentially regulated in bacteroids. Genes up-regulated >5-fold in both bean and pea bacteroids (89 genes) are listed in Table S10. Genes up-regulated >5-fold in bean and <2-fold in pea bacteroids (150 genes) are listed in Table S13. Genes up-regulated >5-fold in pea and <2-fold in bean bacteroids (116 genes) are listed in Table S15. Genes down-regulated >5-fold in both bean and pea bacteroids (17 genes) are listed in Table S18. Genes down-regulated >5-fold in bean and >1-fold pea bacteroids (14 genes) are listed in Table S19. Genes down-regulated >5-fold in pea and >1-fold bean bacteroids (18 genes) are listed in Table S20. As the Sym plasmid plays a key role in symbiosis, differential gene expression on plasmids pRP2 (433 genes) and pRL1 (223 genes) is summarized as a heat-map ( Fig. 1 , showing >2- and >10-fold differential expression, Tables S6 and S8). pRP2 and pRL1 encode 45 gene products showing >80 % amino acid id, and so we considered them as orthologues (summarized in Fig. 2 ). Table S9 gives their relative expression in bean and pea bacteroids. (i) Expression of common Sym plasmid genes in bean and pea bacteroids Nitrogen-fixation genes The nif genes on pRP2 and pRL1 were up-regulated >10-fold in bacteroids ( Fig. 1 ). The nifHDKEN operons ( RHLp7062–58 and RHLv8088–4 ) were up 100- to 460-fold in bean, and 40- to 180-fold in pea bacteroids, respectively (Tables S6, S8 and S9). The fixABCXnifAB genes on pRP2 ( RHLp7092–7 ) and pRL1 ( RHLv1824–19 ) were about 7- to 280-fold and 12- to 40-fold up-regulated, respectively, in bacteroids (Table S9). The fixGHIS (fixG1H1I1S1 ; RHLp7178–81 and RHLv8139–42 ) and fixNOQP ( fixN1O1Q1P1 ; RHLp7186–3 and RHLv8134–7 ) genes were highly up-regulated ( Fig. 2 , Table S9). The shared genome of Rlp4292 and RlvA34 also contains fixNOQP ( fixN3O3Q3P3 ; RHL4126–3 ) and fixSI ( fixS1I2 ; RHL4119–20) genes, but these were not induced in bean or pea bacteroids (Table S4), presumably regulation of their expression (differing from that of analogous genes on the Sym plasmid) reflects their upstream control regions and local DNA topology. Also, on the common genome is fixK1 ( RHLb5914 ), encoding an FNR/CRP-family transcriptional regulator; it was about threefold up-regulated in bean but about fourfold down-regulated in pea bacteroids (Table S4). Nodulation ( nod ) genes The clustered ( Fig. 1 ) nod genes on pRL1 [ 43 ], nodABCIJ ( RHLv8111–15 ) , nodFEL ( RHLv8109–7 ), nodMNT ( RHLv8106–4 ) and nodO ( RHLv8100 ) are regulated by the sole copy of NodD (RHLv8110). On pRP2, the nodABCIJ genes are more scattered ( nodA1 : RHLp7065 , nodA2 ; RHLp7104 , nodBCSUIJ RHLp7151– 46) ( Fig. 1 ). There are no nodFEL, nodMNT and nodO genes, but the presence of nodS ( RHLp7149 ), nodU ( RHLp7148 ) and nodZ , ( RHLp7173 ) suggest the Nod factor(s) are similar to that of R. etli [ 44 ], with N- methyl, carbamoyl and fucosyl groups. In RlvA34 bacteroids, nod genes were not expressed (Table S8), whereas in bean bacteroids nodA1 ( RHLp7065 ), nodA2 ( RHLp7104 ), nodD2 ( RHLp7142 ), nodD3 ( RHLp7161 ) and nodU ( RHLp7148 ) were up-regulated about 3- to 9-fold, while other nod genes on pRP2 were not. Interestingly, it has been shown that the determinate nodule-forming Mesorhizobium loti requires expression of specific nodD genes at different stages through nodule formation on Lotus japonicus, and it is thought that these form additional checkpoints for the infection process [ 45 ]. For indeterminate nodules where there is only a single nodD , and where nod gene expression is strongly up-regulated in the pea rhizosphere and infection threads [ 46 ], but rapidly ceases following release from infection threads [ 47 ], the observed low level of nod gene expression in bacteroids means there must be very little contamination of these RlvA34 pea bacteroids with infection threads or extracellular rhizobia. Common Sym plasmid genes >5× down-regulated in pea include RHLp6783 / RHv8206 ( traI ) and RHLp6974 / RHLv8171 ( traD ) involved in plasmid conjugation, which are known to be induced in free-living cultures [ 48 ]. (ii) pRP2 genes differentially regulated in bean bacteroids In Rlp4292 bacteroids, 27 % of the Sym plasmid pRP2 genes were >5-fold up-regulated and 15 % were >5-fold down-regulated (Table S7). As pRP2 contains 210 more genes than pRL1 (Fig. S1), many pRP2-unique genes with no pRL1 orthologue are differentially regulated in bean bacteroids (summarized in Fig. 2 ). pRP2 genes up-regulated in bean bacteroids Many up-regulated genes are predicted to be involved with detoxification or export of unwanted chemicals/toxins, presumably reflecting the environment within bean nodules (Table S6). Genes RHLp7122–6 and RHLp7083 (up-regulated 60- to 150-fold) encode five cytochrome P450 monooxygenase proteins and an oxidoreductase (Table S6). RHLp7189–97 (up-regulated 10- to 100-fold) encode genes for a putative ferredoxin and two copper-containing oxidases ( Fig. 1 , Table S6). Several of these predicted monooxygenases, oxido-reductases and oxidases could target specific nodule compounds made in bean but not pea nodules. In view of the observation that peas make NCR defensin-like peptides but beans and other determinate nodules do not [ 6 ], secondary antimicrobial metabolites may be of importance in bean to reduce infection by other bacteria (cheaters) that do not contribute to symbiotic nitrogen fixation. Nitrogen-responsive sigma factor RpoN In rhizobia, the sigma factor σ 54 (RpoN) regulates the expression of nitrogen fixation ( nif/fix ), nitrite assimilation ( nir ) and C4-dicarboxylate transport ( dct ) genes. Some rhizobia have a single rpoN gene, but others, including B. japonicum [ 49 ] and R. etli CFN 42 [ 50 ], have two, one being induced at low oxygen levels during symbiosis or during free-living growth, and the other being negatively auto-regulated [ 49, 50 ]. In Rlp4292, rpoN2 on pRP2 ( RHLp7087 ) was up-regulated about 160-fold in bean bacteroids (Table S8), whereas the chromosomal rpoN (encoding RHL4002, 55 % id to RHLp7087) was about 2-fold down-regulated in bean bacteroids. RlvA34 has only the chromosomal rpoN ( RHL4002 ), which was up-regulated about eightfold in bacteroids. Phasin genes The most highly up-regulated pRP2 genes (increased more than 500–600-fold) were RHLp6775, RHLp6995 and RHLp7194, encoding phasins (95–98 % id) (Table S6). These non-catalytic proteins coat polyhydroxyalkanoate (PHA) granules, preventing formation of large masses of PHA [ 51 ]. Their role is probably to coat the extensive granules of polyhydroxybutyrate (PHB, a form of PHA) found in Rlv4292 bacteroids [ 37 ]. Although RlvA34 produces PHB in pea nodule infection threads, PHB granules are not seen in mature pea bacteroids [ 37 ] and pRL1 lacks the phasin genes found on pRP2. PHB synthase ( phaC , RHL1006 ) was about threefold up-regulated in bean (Rlp4292) but not in pea (RlvA34) bacteroids (Table S4). The formation of PHB and/or lipid storage polymers enables recycling of CoA from acetyl-CoA. Melanin Production of melanin in Rlp4292 requires pRP2-encoded MelA (RHLp6882) [ 52 ], which oxidises tyrosine immediately prior to its polymerization into melanin. In bean nodules, melA ( RHLp6882 ), which is co-regulated with fix genes [ 53 ], was up-regulated about 300-fold (Table S6). Melanin can trap free radicals that are produced during nitrogen fixation, possibly reflecting a different redox environment within bean and pea bacteroids. Fe-S proteins Genes encoding a Fe-S cluster assembly protein (RHLp7088) and a 4Fe-4S binding domain protein (RHLp6777) were up-regulated 40- and 100-fold, respectively, in bean nodules, and could be involved in electron transfer during nitrogen fixation or to other proteins, such as cytochrome P450s. pRP2 genes down–regulated in bean bacteroids Although about 45 % of pRP2 genes were not differentially expressed >2-fold in bacteroids (yellow in Fig. 1 , Table S6), many genes were down-regulated (>2-fold) in bean bacteroids (light blue in Fig. 1 , Table S6), including genes encoding plasmid conjugation ( RHLp6940–5 and RHLp6969–81 ), putative ABC transport systems for sugars ( RHLp6928–32 ) and nopaline ( RHLp6983–7 ), components of a type IV secretion system ( RHLp6948–59 ) and transposase proteins ( RHLp7043–5, RHLp7110–1 and RHLp7172–4 ) (Table S6). (iii) pRL1 genes differentially regulated in pea bacteroids In RlvA34 pea bacteroids, 15 % of pRL1 genes were up-regulated >5-fold, whereas 34 % were down-regulated >5-fold (the highest proportion of any replicon) (Table S7). In addition to the aforementioned nif ( RHLv8080–8 ) , fixABCX nifAB ( RHLv8118–28 ) and the RHLv8134–8142 fix genes (shown in red in Fig. 1 ), other genes up-regulated are RHLv8117 – 20 (about 5- to 30-fold), RHLv8130 – 1 (5- to 30-fold), RHLv8083 (about 20-fold), RHLv8121 (about 30-fold) and RHLv8138 (about 30-fold) (Table S8). The functions of the products of several of these genes are not known. Among the 75 % of down-regulated genes are RHLv8180–2 and RHLv8185–7 encoding putative rhizobiocins and possibly their type I export systems and other ABC transporters; RHLv8035–9 [PAAT (polar amino acid transport) family], RHLv8059–62 [CUT2 (carbohydrate uptake transporter 2) family] and RHLv8066–9 [CUT1 (carbohydrate uptake transporter 1) family] ( Figs 1 and 2 , Table S8). Differential expression of the common genome in mature bacteroids Differential expression of the common genome (i.e. everything other than the Sym plasmids) is summarized in Fig. 3 and Table S7 shows the numbers of genes differentially expressed >5-fold, by replicon, for bean and pea bacteroids. On each replicon, similar numbers of genes were up-regulated >5-fold in both bean and pea bacteroids (between 7 % on plasmid B and 2 % on plasmid A), except for plasmid C with 27 genes up-regulated (5 %) in bean compared to only 10 (2 %) in pea bacteroids. For down-regulated genes in the two bacteroid types, similar values were seen for the chromosome and plasmid B (1–2 %), but for plasmids A and C, a slightly higher percentage is down-regulated in bean (5–6 %) than in pea (1–3 %) (Table S7). (i) Shared genes up-regulated in both bean and pea bacteroids Pathways important for symbioses in both determinate and indeterminate nodules can be deduced from Table S10 showing the 89 genes >5-fold up-regulated in both bean and pea bacteroids. For comparison, this table includes data with likely orthologues in Rlv3841 from pea nodules [ 13 ]. Calcium-binding proteins RHL1101 and RHLb6093 encoding EF-hand calcium (Ca)-binding proteins were strongly up-regulated in bean and pea bacteroids (Table S10). Similar rhizobial proteins have two predicted EF-hand domains [ 50 ], one extending outside the cell. Ca-binding proteins have several roles including Ca homeostasis, signalling between bacteroid/plant and may be expressed as a result of nitrogen-starvation or stress (for reviews see [ 54, 55 ]). Repression of transcription DksA proteins bind to RNA polymerase and mediate the stringent response induced on nutrient limitation. RHLb6067 ( dksA1 ) and RHL1099 ( dksA2 ) were up-regulated about 7- to 40-fold. Mutation of dksA in S. meliloti reduced symbiotic nitrogen fixation in alfalfa nodules [ 56 ]. Formate dehydrogenase Genes encoding formate dehydrogenase subunits and associated proteins were up-regulated 5- to 20-fold ( RHL3212–16; fdhDA2BG ) (Table S10), and 110- and 20-fold ( RHLp7098 / RHLv8122; fdsA3 ) (Table S9), in bean and pea bacteroids, respectively. An exception is formate dehydrogenase subunit A, RHL3088 ( fdsA1 ), which was not differentially regulated (Table S4). Stress proteins Nine genes encoding stress proteins were up-regulated in both bean and pea bacteroids (Table S10, Riley code 1.6.1). RHLb6081 ( hspF ) was about 400- and 70-fold up-regulated in bean and pea bacteroids, respectively; RHLb6065 was about 30- and 40-fold up-regulated in pea and bean, respectively; RHL1259 was 12- and 20-fold up-regulated in bean and pea bacteroids, respectively. Transport systems Transport system genes are often induced in response to the transported solute; thus, giving an indication of the chemical environment. Twenty genes whose products are predicted to be involved in transport across membranes were up-regulated >5-fold in both bean and pea bacteroids (Table S11, selecting Riley code 1.5.x). To ensure the most robust data, we chose to examine transporters that were not only up-regulated, but also highly expressed (>200 000 reads); 15 genes fulfilled these criteria (Table S12, Fig. 3 ) and are described below. Bacteroids are fuelled by C4-dicarboxylates The C4-dicarboxylate transporter RHL2260 ( dctA ) was up-regulated about 14- and 5-fold in bean and pea bacteroids, respectively (Table S12) (appearing as bean-specific in Fig. 3 due to falling just below the 5-fold cut-off). It was the most highly expressed bacteroid transporter with >8×10 6 and >3×10 6 reads, respectively (Table S12); it is also the most highly expressed transporter in succinate-grown free-living RlvA34 and second most expressed in succinate-grown free-living Rlp4292 (Table S4). Therefore, increased expression of dctA in bacteroids, relative to even succinate-grown cultures, illustrates the importance of dicarboxylates as a carbon source in nodules. Amino acids Four genes encoding components of the Bra (branched-chain amino-acids) transporter [ABC HAAT (hydrophobic amino acid transporter) family] were up-regulated >5-fold in bacteroids. Although Fig. 3 shows RHL2378 ( braC3 ) and RHL2589 ( braC ) specifically up-regulated in bean bacteroids and RHL2591 ( braG ) and RHL2592 ( braF ) specifically in pea, closer inspection reveals that all genes are up-regulated by >2-fold in both bacteroid types (Table S12). Pea and bean bacteroids require the plant to supply branched-chain amino acids isoleucine and valine to allow bacteroid development [ 57 ]. The broad-specificity amino acid transporters Aap and Bra [ 57, 58 ] are essential for bacteroid branched-chain amino acid uptake and normal nitrogen fixation in Rlv3841 [ 36, 59 ]. The PAAT family ABC transporter Aap is unusual in that it transports a wide-range of substrates [ 60, 61 ]. Aap components encoded by RHL1044-6 ( aapPMQ ) were up-regulated about 4- to 7-fold in both bean and pea bacteroids (Table S12). The importance of both transport systems in nodules is illustrated by the observation that although strains Rlv3841 and Rlp4292 mutated in both Aap and Bra form nodules on peas and beans, respectively, they fix nitrogen at only about 30 % of the wild-type rate [ 21, 62, 63 ]. These data are indicative that supply of these amino acids to pea and bean bacteroids is similar. Quaternary amines and other nitrogenous compounds The ABC QAT (quaternary amine transporter) family transports quaternary amines, such as histidine and choline. In both bean and pea bacteroids, RHL2371 and RHLa5629 [which encode solute binding proteins (SBPs) GbcX (QatX1) and QatX3, respectively] were up (about 7- to 30-fold), as were the contiguous genes RHL2372–3 ( qatW1V1 ) (3- to 9-fold) suggesting that choline and/or glycine betaine are used by both bean and pea bacteroids. Mutation of the QAT encoded by RL3533–5 ( gbcXWV) inhibited uptake of choline and glycine betaine, and the residual low transport of glycine betaine was attributed to the Qat3 system (pRL120514 – 6) [ 64 ]. RHLa5629 shows 96 % id with pRL120516 and it may be that it forms part of a second glycine betaine transport system. RHL2564 encoding an SBP of an ABC transporter of the NitT (nitrate/nitrite/cyanate transporter) family was up-regulated in bacteroids of both Rlp4292 (about 13-fold) and RlvA34 (about 6-fold) ( Fig. 3 ); the orthologous gene in S. meliloti (SMc01827) is induced by uracil and uridine [ 65 ]. Magnesium and other cations Expression of mgtE ( RHL0406 ), encoding a Mg ++ transporter was up-regulated about 18-fold in bean and about 4-fold in RlvA34 pea bacteroids (the >5-fold cut-off making it appear bean-specific in Fig. 3 ). Cation-transporting ATPase proteins encoded by RHLb6066 and RHLb6068 were up-regulated about 20- to 30-fold and about 6- to 7-fold in bacteroids of Rlp4292 and RlvA34, respectively. MbfA (RHL3841), a putative rubrerythrin (contains ferritin fold) transmembrane protein, is related to proteins involved in iron and manganese transport (CCC1-like family), and RHL3841 was up-regulated about 23-fold in beans and about 5-fold in peas (Table S12, Fig. 3 ). Tat secretion The Tat protein exporter encoded by RHL0954 ( tatA ) and RHL0955 ( tatB ) was up-regulated about sixfold in RlvA34 pea bacteroids ( Fig. 3 ) and about threefold in bean bacteroids (Table S12). This transporter secretes cell wall amidases needed for rhizobial-wall integrity and nodule infection; it also exports the periplasmic Rieske electron transport protein, required for bacteroid respiration [ 66, 67 ]. Role of plasmid B in symbiosis Within a cluster of just over 30 genes encoded on plasmid B ( RHLb6065–6098 ), 24 are up-regulated >5-fold in both bean and pea bacteroids (Table S10). Although several genes in this cluster are related to stress responses: e.g. RHLb6065 and RHLb6072 encode universal stress proteins; RHLb6081 encodes a small heat shock protein, HspF (see section above); RHLb6066 and RHLb6068 encode cation transporters; and RHLb6098 encodes FeuP, part of a two-component sensor regulator (Table S10). The significance of this clustering of genes is not known. (ii) Shared genes up-regulated only in bean bacteroids One hundred and fifty genes were >5-fold up-regulated in Rlp4292 bean bacteroids and <2-fold up-regulated in RlvA34 from pea nodules (Table S13, Fig. 3 ). In this section, we deal with supply of P, S, Fe, Ca, C, N and O 2 , and then predicted stresses. Bean bacteroids are phosphate-limited Several phosphate-related genes were up-regulated in bean but not pea bacteroids, including: RHL3750–52 , RHL3755 (about 5- to 30-fold) encoding components of the PhoT (phosphate/phosphonate transporter) family ABC system; RHL0576 and RHL3757–9 (about 5- and 210-fold) encoding four putative phosphonate utilization proteins; RHL3549 (about 60-fold) encoding an alkaline phosphatase PhoA; and RHLb6029 (about 110-fold) encoding an acid phosphatase, possibly involved in glycerolipid metabolism (Table S13). Under phosphate limitation, S. meliloti induces the btaAB genes to make phosphate-free lipids from diacylglycerol (DAG) [ 68 ]. In bean (but not pea) bacteroids, btaA and btaB ( RHL2133–4 ) were up-regulated about 25- and 10-fold, respectively. Expression of btaAB is induced by PhoB–PhoU sensor-regulator proteins that are encoded by RHL4136–7 (up about 13-fold in bean). The contiguous genes ( RHL4132–5) encode a PhoT ABC transporter for uptake of phosphate and were up-regulated 15- to 75-fold in bean bacteroids (Table S13). Taken together, these data suggest that Rlp4292 bacteroids are phosphate-limited compared to RlvA34 bacteroids. In Sinorhizobium NGR234, genes encoding phosphate uptake systems and btaAB were up-regulated in both determinate and indeterminate nodules [ 18 ], so nodule bacteroids may be phosphate-limited in some legumes but not others. Bean bacteroids are sulphate-limited RHLb6112 encoding the sulphur transport ABC component SulA was up-regulated about sixfold in bean and about sixfold down-regulated in pea bacteroids (Table S12, Fig. 4 ). The sulA ( SMb21133 ) orthologue in S. meliloti is induced by sulphate limitation [ 65 ]. RHLc6500, a NitT family transporter that probably encodes an aliphatic sulphonate ABC transporter SBP, was up-regulated about sevenfold in bean bacteroids but down-regulated about threefold in pea ( Fig. 4 ). This suggests that bean bacteroids are sulphate-limited, while those of pea are not. Fig. 4. Transporter systems whose genes are up-regulated in Rlp4292 and RlvA34 bacteroids. Common nodule-specific transporters (up-regulated >5-fold in nodules of both strains) are shown in black, those specific to bean (up-regulated >5-fold in bean bacteroids and <5-fold in pea bacteroids) are shown in purple and those specific to pea (up-regulated >5-fold in pea bacteroids and <5-fold in bean bacteroids) are shown in green. In addition to being up-regulated in bacteroids, all genes are also highly expressed (>200 000 reads). Data for this figure is given in Table S12. Bean bacteroids are iron-limited Several uptake systems associated with iron limitation are up-regulated in bean but not pea bacteroids; none of these genes (described below) is among those up-regulated in free-living RlvA34 compared with Rlv4292 (Table S5). This means that there are at least two sets of transcriptional responses to iron. The ABC transporter FeT [Fe (III) transport] family gene RHL2160 and RHL2001 ( afuA3 ) were strongly up-regulated (about 20- and 40-fold, respectively) in bean but not pea bacteroids (Table S12, Fig. 4 ). RHL1379 ( sufC ), involved in [Fe-S] cluster assembly, was up-regulated about sixfold in bean and fourfold in pea bacteroids (Table S12). The PepT family dipeptide transporter, RHL3498 ( dppA3 ), was up-regulated about sixfold in bean and threefold in pea bacteroids (Table S12). Mutation of the rhizobial dpp operon reduces uptake of the haem precursor δ-aminolevulinic acid [ 69 ]. In Escherichia coli , the Dpp transport system transports iron via haem [ 70 ]. Calcium In addition to the Ca-binding proteins up-regulated in both bean and pea bacteroids (see above), RHLa5297 ( casA ) encoding the exported Ca-binding protein calsymin, was about 50-fold induced in bean but not pea bacteroids (Table S13). R. etli CasA (85 % id with RHLa5297) is important for the symbiosis with Phaseolus , because a casA mutation affected bacteroid development and decreased nitrogen fixation [ 55 ]. Transport systems up-regulated only in bean bacteroids Fifty-six genes encoding components of solute uptake systems were up-regulated >5-fold in Rlp4292 bean bacteroids and <5-fold in RlvA34 bacteroids (Table S14, Riley code 1.5.0–1.5.4) and 44 of these were highly expressed (Table S12, Fig. 3 ). Diverse carbohydrates available in bean nodules Expression of carbohydrate uptake transporters (CUTs) gives an insight into sugars available in nodules. There are two sub-classes of these ABC transporters: CUT1, transporting di- and oligo-saccharides; and CUT2, which generally transports monosaccharides. Eight genes encoding CUT1 components were up-regulated in bacteroids, seven of these in bean but not pea bacteroids, identifying six different CUT1 transporters ( Fig. 4 ). The SBPs RHLb5675 and RHL3007, respectively, probably bind galactosamine and mannitol, which induce the orthologous genes in S. meliloti [ 65 ]. RHL4353 , annotated as alpha-glucoside transporter ( aglE) , and RHL2640 and RHL2643 , annotated as glycerol-3-phosphate transporter components (ATP-binding component and SBP, ugpC2 and ugpB2 , respectively), were up-regulated about 80-fold in bean bacteroids (Table S12, Fig. 4 ). Ten genes encoding CUT2 components of eight transport systems were up-regulated >5-fold in bean bacteroids. Two systems were up-regulated in both bean and pea bacteroids; RHLc6553–4 (about 10- to 50-fold) and RHL1245 (about 10- to 25-fold). The solutes transported by these systems are unknown. Five CUT2 SBP genes were up-regulated in bean but not pea bacteroids: RHL1188 (about 60-fold), likely binds fucose (its orthologue is induced by fucose in S. meliloti [ 65 ]); RHL2450 , likely to bind arabinose and/or galactose (as does its orthologue in Rlv3841 [ 46 ]); RHLa5259 (unknown solute); RHLb6144 , encoding an SBP involved in competition for nodulation (annotated as a rhamnose transporter); and RHLc6725 , likely solute arabinogalactan/related compound (from homology with genes in Rlv3841) [ 46 ] ( Fig. 4 ). We conclude that bean bacteroids contain a variety of sugars [e.g. galactosamine, mannitol, alpha-glucoside(s), glycerol-3-phosphate, fucose, arabinose/galactose, rhamnose, arabinogalactan] absent from pea bacteroids. Taurine in bean nodules RHLc6333 ( tauA ), which encodes a predicted taurine uptake component, was up-regulated about sixfold in bean but down-regulated about eightfold in pea bacteroids ( Fig. 4 ). This is indicative that there is taurine in bean but not pea nodules because RHLc6333 shows 40 % id with the TauT family SBP SMb21526 from S. meliloti , which is induced by taurine [ 65 ] and forms the basis of a taurine-inducible expression system in rhizobia [ 71 ]. Other transporters induced in bean nodules Among the several putative POPT (polyamines, opines and phosphonate) family genes in the shared genome, only RHLa4848–9 encoding a putative POPT transporter was up-regulated 10- to 40-fold in bean but not RlvA34 pea bacteroids (Table S12, Fig. 4 ). Three PAAT predicted amino-acid SBP genes ( RHL1551 , RHLa5284 and RHLb5944) were up-regulated 5- to 10-fold in bean but not pea bacteroids ( Fig. 4 ). A predicted QAT system ( RHLc6320) was up-regulated about 160-fold in bean but not pea bacteroids. In all these cases it is likely that the unidentified solutes are present in bean but not pea nodules. Cytochrome oxidases Genes RHLc6648–53, encoding a transmembrane cytochrome d ubiquinol oxidase subunit I, a cytochrome bd -II oxidase subunit II, an ABC transporter system related to cytochrome bd export and a MarR family regulator of gene expression, were all more strongly up-regulated in bean bacteroids (about 12- to 90-fold, Table S4) than in pea bacteroids (about 2- to 5-fold) (Table S4). Genes encoding cytochrome c oxidase subunits RHL4623 – 4 (CtaC1 and CtaC2) were up-regulated about sixfold specifically in bean bacteroids (Table S13). Cytochrome cbb3 (encoded by the fixNOQP operon) is the high affinity oxidase essential for nitrogen fixation [ 72 ], but the expression of other respiratory pathways terminated by oxidases with a lower affinity for oxygen could be indicative that there may be a higher free oxygen level in (parts of) bean nodules. Lipid X Lipid A is the primary lipid in the outer layer of the Gram-negative bacterial membrane and acts as an anchor for lipopolysaccharide [ 73 ]. Synthesis of lipid A involves nine enzymes, one of which, LpxH, cleaves UDP-2,3-diacylglucosamine to 2,3-diacylglucosamine 1-phosphate (lipid X) and uracil-monophosphate (UMP) [ 74 ]. lpxH ( RHL1469 ) was up-regulated about 70-fold in bean but not pea bacteroids. Genes encoding the other eight Lpx enzymes were not up-regulated in Rlp4292 bacteroids (Table S4). Lipid A oxidase RHL4482 ( lpxQ ) was about sevenfold up-regulated in bean but not pea bacteroids (Table S13). Detoxification and stress Nine genes encoding stress proteins were elevated specifically in bean bacteroids (Table S13, Riley code 1.6.x). RHL3015 , encoding the osmotically-induced OsmC, and RHL1758 and RHLa5426, encoding two cold shock proteins, were up-regulated about 10-fold in bean but not pea bacteroids. Glutathione S -transferases (GSTs) are diverse enzymes involved in detoxification of oxidative stressors, antimicrobial agents and metabolic intermediates in bacteria. Three predicted GSTs, RHL0225 , RHL346 and RHL3926, were up-regulated about 10-fold in bean but not pea bacteroids (Table S13). Export is another way of removing toxic compounds; RHL0518 , RHL2130 and RHL3918 encode efflux systems that are up-regulated about 5- to 8-fold in bean but not pea bacteroids (Table S13, Riley code 1.5.5). These data could be indicative that rhizobia in bean nodules are more stressed by metabolites than rhizobia in pea nodules. Chaperonins are also often induced in response to stress [ 75 ] RH2128 , encoding a DnaJ family protein, and RHL4498–9, predicted to encode the chaperonins Cpn60 and Cpn10, were about sevenfold up-regulated in bean but not pea bacteroids (Table S13). Outer membrane ROPs Bacterial outer membranes and their proteins are crucial for cell–cell and cell–environment interactions. In S. meliloti , a putative transmembrane β-barrel porin, RopA1, is essential for viability, despite the presence of ropA2 , encoding a close homologue [ 76 ]. The Rlp4292 and RlvA34 share four homologues of RopA (RHL0466, RHL1573, RHL2878 and RHLb6113), each with about 50 % id with RopA1 or RopA2 from S. meliloti . Three of these genes, which we named ropA1 ( RHL0466 ) , ropA3 ( RHL2878 ) and ropA4 ( RHLb6113 ), were up-regulated (about 25-, 90- and 10-fold, respectively) in bean but not pea bacteroids (Table S4). Autoaggregation proteins RapA2 ( RHLc6544) and RapB3 (RHL2729) were up-regulated 40- and 12-fold in bean but not pea bacteroids (Table S13). Possibly the presence of multiple bacteroids within one symbiosome as observed in bean but not pea nodules influences expression of genes that affect cell–cell interactions. (iii) Shared genes up-regulated in pea but not bean bacteroids Table S15 shows the 116 genes that are >5-fold up-regulated in RlvA34 pea bacteroids and <2-fold up-regulated in Rlp4292 from bean nodules. These data are presented together with microarray data for those Rlv3841 genes showing >80 % amino acid id to those of Rlp4292/RlvA34 [ 13 ]. The pattern of up-regulated genes is different from that in bean, suggesting limitation of N and Mo and different gene induction associated with C metabolism and bacteroid development. Forty genes encoding components of solute uptake systems were up-regulated >5-fold in RlvA34 pea bacteroids and <5-fold in Rlp4292 bean bacteroids (Table S16, Riley code 1.5.0–1.5.4), with 26 of them highly expressed (Table S12, Fig. 4 ) Provision of nitrogen for pea bacteroids Several genes related to nitrogen utilization were up-regulated in pea but not bean bacteroids. These include gltDB ( RHL2865–6 ) encoding glutamate oxoglutarate amido transferase (GOGAT), which were up-regulated about 20-fold in RlvA34 (but were unchanged in Rlp4292 bean bacteroids; Fig. 5 , Table S17), the ammonium transporter gene amtB ( RHL3388 ) ( Fig. 3 ), and its cognate regulator glnK ( RHL3389 ) (about sevenfold and ninefold up-regulated, respectively). Genes (probably an operon) encoding the nitrate reductases/subunits, NasA (RHL0901), NirD (RHL0902)and NasD (RHL090 3 ), and NarK (RHL0904), a major facilitator subfamily (MFS) nitrate transport protein ( Fig. 3 ), were up-regulated 10–30-fold (Table S4). Legume nitrate transporter, nitrate reductase and nitrite reductase genes are also up-regulated in nodules [ 77 ], especially in the nitrogen-fixation zone [ 23 ]. Surprisingly, therefore, it seems that at least under some conditions there must be significant amounts of nitrate in nodules of some legumes. Fig. 5. TCA cycle and associated metabolic pathways. Enzymes whose genes are up-regulated >10-fold in RlvA34 pea bacteroids are shown in green. Data for this figure are given in Table S17. Phenylalanine could also be a source of N in pea bacteroids because RHL0852 ( phhA ), encoding a phenylalanine-4-hydroxylase, was up-regulated about 6-fold in pea but not bean bacteroids (it is also up-regulated about 40-fold in the pea rhizosphere; Table S4). Phenylalanine is a precursor of lignin synthesis and may be available in pea nodules due to cell wall synthesis being maintained in mature indeterminate (pea) but not determinate (bean) nodules. Pea bacteroids appear molybdate-limited The gene encoding SBP ModA ( RHL3521 ) was up-regulated about eightfold in pea but not bean bacteroids (Table S16) (this gene failed to meet the criterion for high expression and does not appear in Table S12 or on Fig. 4 ). Although in Rlv3841, expression of a molybdate transporter (MolT family of ABC transporters) encoded by modABC was also induced under low sulphate [ 78 ], the fact that ABC sulphur transporter SulT family gene RHLb6112 ( sulA ) was down-regulated (about 10-fold) in pea bacteroids of RlvA34 and Rlv3841 (pRL110374, 97 % id) (Table S12) suggests that although RlvA34 bacteroids are molybdate-limited, they have sufficient sulphate within pea nodules. Bacteroid development NCR peptides secreted by the plant [ 11 ] affect bacteroid development in peas but not beans, and the resulting differences in bacteroid differentiation are likely to cause differences in bean and pea bacteroid gene expression. Several lipid biosynthesis and metabolism genes were slightly up-regulated (about 2- to 3-fold) in pea, but not bean bacteroids. These include genes encoding the enzymes of the lipid A biosynthetic pathway: lpxB ( RHL1074 ), lpxD ( RHL1070 ) and lpxK ( RHL4516 ), lipid metabolic enzyme ( RHL2015 ), an ABC family lipid exporter ( RHL3351–2 ). An acyl carrier protein ( RHLc6550 ) was up-regulated about 10-fold in pea bacteroids and about 4-fold in bean bacteroids (Tables S4 and S13). The level of induction of most of these genes was modest and not particularly different from those seen in bean bacteroids. This may reflect the fact that changes attributable to NCR peptides have already occurred by the time nodules have matured, a conclusion reached with RNA from Rlv3841 bacteroids of 7, 15, 21 and 28 days post-inoculation analysed using microarrays [ 13 ]. Some genes encoding DNA replication functions were up-regulated in pea but not bean bacteroids, including gyrB1 ( RHL3590 ), (Table S15), dnaX ( RHL3716 ) and dnaG ( RHL2242 ) up-regulated about sixfold, sixfold and fourfold, respectively (Table S4). This would be consistent with increased DNA endoreduplication in pea bacteroids [ 11 ]. Detoxification and stress A predicted salicylate hydrolase gene ( RHLa4811) was about 12-fold up-regulated in RlvA34 pea bacteroids. A putative arsenate reductase gene ( RHL4205) was up-regulated about sevenfold in RlvA34 (Table S15). The heat shock protein RHL2870 (IbpA) may be more important in pea bacteroids as ibpA expression was about 15-fold up-regulated in RlvA34 pea bacteroids, but only about 2-fold up-regulated in bean bacteroids (Table S4). Numerous export systems that are up-regulated in pea but not bean bacteroids may remove unwanted and/or toxic compounds; these include two pea-specific GSTs (RHL1557 and RHL3865, sharing 32 % id), which were up-regulated about 35- and 10-fold in pea RlvA34 bacteroids (Table S15). Amongst those genes with the most highly elevated expression in pea but not bean bacteroids were the RND family efflux systems encoded by RHL2076 , RHL2565–6 RHL2619–20 ( mexF1 ), RHL2967 and RHL3012 (about 5- to 8-fold up-regulated, Table S12, Fig. 3 ), a HlyD family efflux pump, RHL2518 (about 10-fold), contiguous with an ABC export system RHL2519–21 (about 4- to 6-fold), a TetR family transcriptional regulator ( RHL2517, about 8-fold), another ABC export cluster RHL2324 (about 8-fold) and MFS (major facilitator subfamily) protein RHL2967 (about 5-fold). [For a full list of the 12 genes encoding proteins involved in export (Riley code 1.5.5) that are >5-fold elevated in pea bacteroids and <2-fold elevated in bean bacteroids, see Table S15.] Table S12 and Fig. 4 show up-regulated transporters that are also highly expressed. Central carbon metabolism In pea bacteroids, strongly up-regulated genes included those encoding TCA (tricarboxylic acid) cycle enzymes RHL1075 (GltA, citrate synthase), RHL3358 (AcnA, aconitase), RHL3260 and RHL3258 (SucAB, oxoglutarate dehydrogenase), RHL3261 (SucD, succinyl-CoA synthetase), RHL3268 (SdhA) and RHL3267 (SdhB) (both parts of the succinate dehydrogenase complex) and RHL3264 (Mdh, malate dehydrogenase) (Table S17, Fig. 5 ) were also seen in bacteroids of Rlv3841 [ 13 ]. In Rlp4292, these genes were up-regulated at most about twofold, except for citrate synthase (GltA) encoded by RHL1075 , which was up-regulated about fourfold (Table S17), while RHL1300 ( gltA2 ) and RHL1301 ( citZ ) were unchanged or twofold down-regulated, respectively. From these data, we can predict that bean bacteroids maintain a level of TCA cycle enzymes similar to that of their free-living cells, including glutamine/glutamate synthesis, whereas highly differentiated pea bacteroids have more perturbed central metabolism. It should be stressed that an increase in expression of genes of the TCA cycle does not give information on the flux through the cycle. The glyoxylate cycle is unlikely to be elevated in pea or bean bacteroids as the genes encoding enzymes RHL4371 (AceA) and RL3631 (GlcB) ( Fig. 5 ) were not differentially expressed in either Rlp4292 or RlvA34 bacteroids (Table S17). Aconitase and 2-ketoglutarate dehydrogenase enzymes are not required for nitrogen fixation in bacteroids of B. japonicum [ 79, 80 ]. GabD2T, a 2-oxoglutarate dehydrogenase-dependent γ-aminobutyrate (GABA) aminotransferase, converts GABA into glutamate and succinate, which feeds directly into the TCA cycle ( Fig. 5 ). As observed previously [ 63, 81 ], expression of gabDTR ( RHL3680–2 ) was up-regulated in pea bacteroids (about 80-, 65- and 7-fold, respectively), but this was not seen in bean bacteroids (Table S17) suggesting GABA metabolism is important only in pea nodules. GABA from pea nodules can be taken up using the Bra system [ 58 ], whose component genes were up-regulated in both pea and bean bacteroids (Table S12, Fig. 4 ). (iv) Shared genes down-regulated in both bean and pea bacteroids Table S18 shows 17 genes that are down-regulated >5-fold in both bean and pea bacteroids (summarized in Fig. 3 ) and these include the ribonucleoside reductase genes RHL3048–50 ( nrdEIH ) (down-regulated about 5- to-10-fold) that produce dNTPs required for DNA synthesis [ 82 ]. The six genes, RLHa5121–6 ( vbsLDAGSOP ), encoding the iron-scavenging siderophore vicibactin and proteins for its biosynthesis and export, were among the most down-regulated (about 5- to 10-fold) in both bean and pea bacteroids (Table S18). While these genes were down-regulated by approximately the same amount in both bean and pea, the fact that the RlvA34 strain had about fivefold more expression in free-living cells than in those of Rlp4292 (Table S5) means that the absolute expression in RlvA34 bacteroids in pea is about five times higher than in Rlp4292 bean bacteroids. The down-regulation of these genes in bacteroids is indicative of a regulatory mechanism epistatic to RirA, mutation of which caused their increased expression in free-living RlvA34. Other genes thought be affected by the rirA mutation in RlvA34 (Table S5) behaved differently; RHL2531–40 encoding haemin iron transport proteins were slightly down-regulated in bean bacteroids (about 2-fold) but not differentially regulated in RlvA34 pea bacteroids (compared to the elevated level in free-living bacteria); RHLa5475–7 , encoding a FeCT ABC transporter, was down-regulated in both bean and pea bacteroids by about 3-fold (meaning that the absolute level in RlvA34 pea bacteroids was about 2- to 5-fold higher that in Rlp4292 bean bacteroids) (Table S5). However, it is important to realise that RirA may act differently in bacteroids than in free-living bacteria and this should, therefore, be taken into account. Three genes strongly down-regulated in both pea and bean bacteroids were the quorum-sensing regulators encodes cinI and cinS, and the adjacent gene ( RHL2191 ) encoding a putative 3-hydroxybutyryl-CoA dehydrogenase (25 % id to HbdA). R HL2814 , encoding the chemotaxis transcriptional regulator CheY (98 % to RL4036), was down-regulated about fivefold, befitting an environment where chemotaxis is not possible. The polysaccharide lyase, encoded by RHL1848 ( plyA2 ), is down-regulated about 5- to 15-fold in bean and pea bacteroids (Table S18); this lyase cleaves acidic extracellular polysaccharide [ 83 ] minimising the high viscosity caused by extracellular polysaccharide (an issue that would be unimportant in bacteroids). (v) Shared genes down-regulated only in bean bacteroids Table S19 shows 14 genes that were >5-fold down-regulated in bean but not pea bacteroids (summarized in Fig. 3 ). These include genes encoding hypothetical proteins of unknown function: RHL0036 , RHL0040 and RHL0044, down-regulated >5-fold in beans, but unchanged in pea bacteroids, and RHLa4808–9 , RHLa4834–5 and RHL5558–60 (Table S19). (vi) Shared genes down-regulated only in pea bacteroids There are 18 shared genes that are >5-fold down-regulated in pea but not bean bacteroids (Table S20, summarized in Fig. 3 ). The gene encoding septum site-determining protein MinD (RHLb5723) was down-regulated about sevenfold in Rlv34 pea, but not Rlp4292 bean bacteroids (Table S20), consistent with endoreduplication without cell division in pea bacteroids. Other cell-division-related genes were down-regulated in pea but not bean nodules: minE ( RHLb5722 ) about 3-fold; minC ( RHLb5724 ) about 5-fold; ftsZAQ ( RHL2104–6 ) about 3- to 4-fold; a DNA translocase gene ( RHL3744 ) about 3-fold; and RHL1899 ( ftsZ2 ) about 2-fold (Table S4). Genes encoding FMN reductases, RHLc6323 and RHLc6678, were down-regulated about 5- to 8-fold in RlvA34 pea, but not Rlv4292 bean bacteroids (Table S20). The RHLb5787–9 genes, encoding a trifolitoxin-related protein and two hypothetical proteins, were down-regulated about fivefold in RlvA34 pea but slightly up-regulated in bean bacteroids. Genes encoding components of several solute uptake systems were down-regulated in pea but not bean bacteroids; RHL1566 (NitT), RHL3478 and RHLc6677 (PAAT), RHLb6112 (SulT), RHLc6283 and RHLc6625 (CUT2), and RHLc6332–3 (unclass) (about fivefold). These genes were more highly expressed due to solutes present in the liquid media and the observation that they were not differentially regulated in bean, correlates with the wide-range of solutes present in bean nodules apparent from induction of the large number and variety of bean-specific transporters ( Fig. 4 ). Conclusions (1) Against a general pattern of down-regulation of gene expression in bacteroids compared with free-living rhizobia, both bean and pea bacteroids showed increased expression of genes associated with nitrogen fixation and utilization of dicarboxylates, formate, amino acids and quaternary amines. The decreased expression of many genes may be associated with the increased expression of stringent response genes. (2) Gene expression patterns suggest that bean bacteroids were more limited for P, S and Fe than pea bacteroids, and the expression of cytochrome oxidase genes suggests that bean bacteroids are exposed to higher levels of oxygen than pea bacteroids. (3) Bacteroids in bean nodules expressed many genes whose products are predicted to be related to metabolite detoxification and export. (4) Bean bacteroids express high levels of phasin genes that are associated with storage of the large amounts of PHB that accumulate in bean nodules. (5) Pea nodules have strongly up-regulated genes associated with central metabolism and this is indicative of some fundamental differences in the use of the TCA cycle. (6) Surprisingly, pea bacteroids showed evidence for expression of nitrate and nitrite reduction enzymes. (7) Expression patterns of uptake transporters are indicative that bacteroids in pea and bean nodules are exposed to different sets of substrates specific to each nodule type."
} | 13,819 |
37894052 | PMC10609205 | pmc | 8,031 | {
"abstract": "In the pursuit of cultivating anaerobic anoxygenic phototrophs with unusual absorbance spectra, a purple sulfur bacterium was isolated from the shoreline of Baltrum, a North Sea island of Germany. It was designated strain 970, due to a predominant light harvesting complex (LH) absorption maximum at 963–966 nm, which represents the furthest infrared-shift documented for such complexes containing bacteriochlorophyll a . A polyphasic approach to bacterial systematics was performed, comparing genomic, biochemical, and physiological properties. Strain 970 is related to Thiorhodovibrio winogradskyi DSM 6702 T by 26.5, 81.9, and 98.0% similarity via dDDH, ANI, and 16S rRNA gene comparisons, respectively. The photosynthetic properties of strain 970 were unlike other Thiorhodovibrio spp., which contained typical LH absorbing characteristics of 800–870 nm, as well as a newly discovered absorption band at 908 nm. Strain 970 also had a different photosynthetic operon composition. Upon genomic comparisons with the original Thiorhodovibrio strains DSM 6702 T and strain 06511, the latter was found to be divergent, with 25.3, 79.1, and 97.5% similarity via dDDH, ANI, and 16S rRNA gene homology to Trv. winogradskyi , respectively. Strain 06511 (=DSM 116345 T ) is thereby described as Thiorhodovibrio litoralis sp. nov., and the unique strain 970 (=DSM 111777 T ) as Thiorhodovibrio frisius sp. nov.",
"conclusion": "4. Conclusions The whole circularized genomes generated in the present study allowed for a determination of accurate ANI and dDDH values, together with complete operon structures. While current annotation software missed numerous genes for photosynthesis, motility, sulfur-related enzymes, and likely others, our additional manual curation of genes in each Thiorhodovibrio strain revealed that observed phenotypes largely corresponded to the gene functions encoded. On the basis of the characteristics described above, strain 970 = DSM 111777 T constitutes a novel bacterial species designated Thiorhodovibrio frisius sp. nov. Our results also indicate that strain 06511 = DSM 116345 T must be considered a novel species, which is described here as Thiorhodovibrio litoralis sp. nov.",
"introduction": "1. Introduction Anaerobic anoxygenic phototrophic bacteria occur where light reaches anoxic layers in either stratified pelagic/ freshwater habitats or the surface layers of aquatic sediments. Various species of anoxygenic phototrophs have been found with significant adaptations to different physicochemical conditions and absorbing particular wavelengths and intensities of light [ 1 ]. In sediments, optical pathlengths are very short and water has comparatively little effect on the spectral composition. Rather, light attenuation is strongly influenced by the physical matrix, and in sandy sediments the intensity of blue wavelength light is rapidly diminished due to the reflection of quartz grains. In dense microbial mats, cyanobacteria and diatoms often colonize the sediment surface and further absorb light between 400 and 700 nm. As a result, mostly far-red and infrared light is available in the lower, sulfidic sediment layers of benthic microbial mats. Anoxygenic phototrophic bacteria in these deeper areas thus compete strongly for wavelengths between 700 and 1100 nm and have adapted through the evolution of specific photosynthetic pigments and protein complexes, with several species exhibiting markedly different absorption properties [ 1 ]. The photosynthetic antennae that are capable of absorbing the longest wavelengths contain bacteriochlorophyll a (BChl a ) or BChl b , and are commonly found in Alpha- , Beta- , and Gammaproteobacteria . When bound to polypeptide reaction center (RC) and light-harvesting (LH) complexes, BChl absorption is shifted to longer wavelengths and typically peaks at 800, 850, and 880 nm for antenna complexes containing BChl a , or around 1020 nm for those binding BChl b . While absorption between 900 and 1000 nm could be expected to provide selective advantage for benthic anoxygenic phototrophs [ 2 ], very few anoxygenic photosynthetic species have been found capable of exploiting this wavelength range to date. Only ” Roseospirillum parvum ” [ 2 ] and Thermochromatium tepidum [ 3 ] exhibit unusual long-wavelength absorption maxima of BChl a -containing LHI at 909 and 918 nm, respectively, whereas Rhodospira trueperi features an unusual blue-shifted in vivo absorption maximum at 986 nm for its BChl b -containing antenna complexes [ 4 ]. However, no species exploiting the wavelength gap between these peaks (918–986 nm) has been described so far. In a systematic search for novel types of phototrophic sulfur bacteria with different light absorption properties, highly selective illumination conditions with infrared light filters yielded a purple sulfur bacterium of the family Chromatiaceae ( Gammaproteobacteria ), provisionally named strain 970. This unique strain contains BChl a like most other anoxygenic phototrophic Proteobacteria, but shows an in vivo absorption maximum at 963 nm, which represents the largest infrared-shift documented for LH complexes [ 5 , 6 ]. So far, only the structure and biophysical functions of the photosynthetic apparatus of strain 970 have been studied [ 5 , 6 , 7 ]. Here, we report on the genomic, biochemical, and physiological properties of this unusual anoxygenic phototrophic bacterium, which is described as the novel species Thiorhodovibrio frisius sp. nov.",
"discussion": "3. Results and Discussion 3.1. Selective Enrichment and Isolation of a Novel Anoxygenic Phototroph Under highly selective illumination with infrared light of wavelengths >900 nm, anoxygenic phototropic sulfur bacteria developed in CRs medium after two weeks of incubation. An enrichment exhibiting unique in vivo absorption with a maximum around 970 nm was selected for the subsequent isolation attempts. The predominant bacterial cells were motile, harbored highly refractile sulfur globules, and contained BChl a as indicated by the characteristic long wavelength absorption peak in acetone extracts at 771 nm [ 38 ]. Of note, if these early enrichments were subsequently exposed to a full spectrum of light from tungsten lamps, additional types of purple sulfur bacteria appeared in each culture. This indicated that the bacteria absorbing around 970 nm had an advantage only under highly selective illumination conditions. Repeated deep agar dilution series yielded an isolate designated strain 970. Pure cultures of this strain exhibited an orange-red color ( Figure 1 b) similar to the sediment surface layer that had originally been sampled, but divergent from other Thiorhodovibrio isolates that are pink-red ( Figure 1 c). Cells were vibrioid to spirilloid, on average 3.6 µm long and 0.9 µm wide, and accumulated intracellular sulfur globules transiently during exponential growth ( Figure 1 e,f). While originally motile, subcultures lost their motility prior to cryopreservation, with no flagellation or locomotion detected under any of the growth conditions tested during subsequent characterization. 3.2. Phylogenomic Placement and Taxonomy of Strain 970 Initial 16S rRNA gene sequence comparisons [ 5 ] had shown that strain 970 was related to Trv. winogradskyi , DSM 6702 T . While an early draft genome sequence of strain 970 was found highly related to Tsp. jenense DSM 216 T [ 26 ], additional comparisons of photosynthetic reaction center protein pufM genes suggested an even closer relationship of strain 970 to Rch. marinum DSM 5261 T [ 26 ]. However, such phylogenomic considerations were only provisional, since both Trv. winogradskyi strains DSMZ 6702 T and strain 06511 lacked sequenced genomes, and strain 970 was only available as an incomplete draft. The assembly of circularized chromosomes presented here ( Table 1 ), thus helped to rectify all previous limitations. Using our new data, a phylogenomic UBCG analysis of 43 photosynthetic strains from Gammaproteobacteria , Betaproteobacteria , and Alphaproteobacteria ( Table S1 ) captured the phylogenetic depth and diversity of Chromatiaceae , as it comprised genomes of 19 different genera. The concatenated alignment of 92 unique marker proteins with 21,501 variable amino acid positions was used to infer the final phylogenomic tree ( Figure S1 ). The additional Alpha- and Betaproteobacteria sequences together with those of Halieaceae and Nevskiaceae from Gammaproteobacteria rooted the phylogenomic tree, whereas Ectothiorhodospiraceae served as an outgroup of the Chromatiaceae subtree ( Figure 2 ). With this approach, strain 970 was clearly placed in Chromatiaceae, a family found to be highly distinct within Gammaproteobacteria , having a long common branch supported by a 100% bootstrap value. The Chromatiaceae were further divided into two recognizable and maximally supported clades ranging from strain 970 to Thiohalocapsa sp. ML-1 (Clade A) and from Ach. vinosum DSM 180 T to Thioflavicoccus mobilis 8321 (Clade B) ( Figure 2 ). The separation of all taxa in Clade A including the three Thiorhodovibrio strains is supported by bootstrap values of 100%, corresponding to the highest possible confidence level. Within Clade A, the three Thiorhodovibrio strains formed a monophyletic subclade ( Figure 2 ). The closest relatives of strain 970 were Thiorhodovibrio winogradskyi DSM 6702 T , Thiorhodovibrio strain 06511 (formerly Trv. winogradskyi ; Overmann et al. 1992), Rch. marinum DSM 5261 T [ 22 , 23 , 39 ], and Tsp. jenense DSM 216 T [ 26 ]. These findings were additionally supported by 16S rRNA gene-, whole-genome-, and whole-proteome-based phylogenetic trees generated in the TYGS server ( Figure S3 ). All three Thiorhodovibrio strains contained two rrn operons in tandem with duplicate identical 16S rRNA genes within their circularized genomes. Pairwise comparisons of 16S rRNA gene sequences from Thiorhodovibrio strains 970 and 06511 with that of the only type strain of this genus, Trv. winogradskyi DSM 6702 T [ 8 ], yielded sequence identity values of 98.0 and 97.5%, respectively, and lower values for comparisons with Rch. marinum DSM 5261 T and Tsp. jenense DSM 216 T ( Table S2 ). These levels were below the conservative species delimitation threshold of 98.7% [ 40 ], suggesting that all three Thiorhodovibrio strains represent distinct species. This conclusion was validated with low calculated dDDH values, ranging between 25.3% and 34.2% for the three Thiorhodovibrio spp. ( Table S2 ), which was far below the species delimitation threshold of 67–73% [ 41 ]. Similarly, ANI values for pairwise comparison of the three strains were below the threshold for species demarcation of 95–96% [ 42 ] and ranged between 79.1 and 83.7% ( Table S2 ). Accordingly, Thiorhodovibrio strains 970, 06511, and Trv. winogradskyi DSM 6702 T must be considered three different species of the genus Thiorhodovibrio . Strain 970 was therefore designated the type strain of the new species Thiorhodovibrio frisius sp. nov. In the original description published 30 years ago, strain 06511 had been assigned to the species Trv. winogradskyi due to the absence of molecular data at that time [ 8 ]. However, with our updated approach, strain 06511 is also to be considered as the type strain of a new species for which we suggest the name Thiorhodovibrio litoralis sp. nov. 3.3. Phenotypic Differentiations and Their Genomic Basis within the Genus Thiorhodovibrio 3.3.1. General Morphological, Physiological, and Chemotaxonomical Characteristics Similar to the other two Thiorhodovibrio strains, cells of strain 970 were vibrioid or short spirilla and formed intracellular sulfur globules ( Figure 1 e,f,g). Transmission electron microscopy also revealed intracellular vesicular membranes akin to its closest four relatives ( Figure 1 g, Table 2 ), while strain 970 was covered by an additional extracellular capsule-like layer ( Figure 1 h). Photolithoautotrophic growth was observed with sulfide and hydrogen as electron donors as for the other two Thiorhodovibrio strains ( Table 2 ). Best growth was achieved at concentrations between 1 and 1.25 mM sulfide, limited bacterial replication occurred at 2 mM, and none was detected at higher sulfide concentrations. All three Thiorhodovibri o spp. had enhanced growth when supplied excess elemental sulfur, while thiosulfate was solely used by strain 06511. A very limited number of carbon substrates could support photolithomixotrophic growth. Out of the 44 tested substrates, only acetate, pyruvate, and glucose stimulated strain 970. During cultivation with glucose, cells thickened and formed elongated chains of spirilla. The temperature optimum during photosynthesis was 27 to 30 °C, with cultivation possible from 15 to 37 °C. Growth was fastest at high light intensities between 50 and 500 µmol·m −2 ·s −1 . The optimum pH was 7.3, with growth occurring between pH 6.8 and 8.3. Strain 970 showed a high salinity tolerance, enduring between 1.1 and 5.3% ( w / v ) NaCl (corresponding to 1.4 to 7% salts) and favoring 1.5–2.1% (2.0 and 2.8% salt content). The genetic adaptations of phototrophs to osmotic pressure were recently thoroughly reviewed [ 39 ], revealing a common production of betaine and ectoine solutes to protect cell osmolarity. Both Trv. strain 06511 and Rch. marinum were previously found to have glycine-sarcosine methyltransferase (GMT) and dimethylglycine methyltransferase (DMT) that synthesize betaine from glycine, also containing the associated betaine transporters BetT and ProVW1-OpuAC, but each lacking ectoine biosynthesis. Similar to Trv. strain 06511, strain 970 and Trv. winogradskyi DSM 6702 T contained GMT and DMT providing the capability to synthesize betaine as their major cellular osmotic pressure protectant ( Table S3 ). Furthermore, all three had proVW1-opuAC transporter genes, each lacked ectoine biosynthesis, whereas only strain 06511 encoded the additional BetT/L transporter reported earlier [ 39 ]. In comparison, betaine and ectoine biosynthesis and corresponding transport systems were not present in Tsp. jenense , as expected for a freshwater phototroph [ 39 ]. Regarding sodium efflux and transport mechanisms, every Thiorhodovibrio species additionally had various sodium symporters ( DASS, SSS, SNF ) and antiporters ( nhaD, mrpF, nhaK ) ( Table S3 ), many of which were among Rch. marinum and altogether absent in Tsp. jenense , further revealing specific adaptations to their saline environments. Uptake of osmolytes constitutes a less energy-consuming way of osmotic adaptation than their biosynthesis. Compatible solutes that leak from living cells or are released by lysing cells are expected to reach high concentrations in dense microbial mats [ 39 ]. Besides the biosynthesis of compatible solutes, systems for their uptake represent a key adaptation of bacteria colonizing microbial mats in marine sediments [ 43 ]. Even though strain 970 is an obligate anaerobic bacterium, it was shown to have a high tolerance toward oxygen, since a shaken open-flask culture had viable cells even after 48 h of exposure to air. Notably, the related Trv. winogradskyi DSM 6702 T could aerobically respire when intervals of anaerobic/microaerobic conditions were controlled within a chemostat [ 9 ]. Therefore, these Chromatiaceae have microaerophilic capabilities which are likely an adaptation to the conditions in the top layers of sediment, where the bacteria meet low oxygen concentrations [ 9 ]. While several enzymes specifically detoxify oxygen radicals, including superoxide dismutases, catalases and peroxidases, terminal oxidases in bacterial respiratory chains may also protect against ROS [ 44 ]. All three Thiorhodovibrio contained [Fe]-superoxide dismutase sodB , where both Trv. winogradskyi DSM 6702 T and Trv. strain 06511 had a pair of homologs in addition to a [Cu-Zn] variant sodC ( Table S4 ). These latter two strains also encoded catalase katG , while all three had peroxidases bsaA , cpo , and garA , but DSM 6702 T solely lacked ccpA . Of note, annotations for cbb 3 -type cytochrome c oxidase components were present in each Thiorhodovibrio sp., but only strain 970 had the assembly protein in addition to subunit II and all other parts, suggesting its capability to produce a functional enzyme. Moreover, each featured numerous oxidases, such as cydAB quinol and heme-based oxidases ( Table S4 ), likely contributing to their oxygen tolerance observed [ 44 ]. By contrast, the genome of oxygen-sensitive Tsp. jenense DSM 216 T only contained a diheme bacterial cytochrome c peroxidase, BCCP; [Fe]-superoxide dismutase, sodB ; and quinol oxidase, cydAB; whereas the genes for catalase and peroxidase were absent [ 26 ]. The fixNOQP type heme/copper cytochrome ( cbb 3 -type) oxidase found in most other Chromatiaceae was also lacking in Tsp. jenense DSM 216 T , which might explain its particular sensitivity towards molecular oxygen [ 26 ]. While the cultured representatives of all four related species were motile and flagellated ( Table 2 ), Trv. frisius strain 970 had lost its motility quite early during the enrichment and isolation process. Evaluating Thiorhodovibrio sp. genetic components, which comprised full sets of flg and fli gene cassettes for flagellated motility ( Table S5 ), Trv. frisius had two notable differences. KEGG-based PANDA annotation detected neither fliO (Thiofri_04660) required for flagellar biosynthesis [ 45 ], nor flgM (Thiofri_04678), a negative regulator of flagellin synthesis [ 46 ], yet both were indeed present in the RAST annotated genome ( Table S5 ). Upon review, the fliO gene of strain 970 had a ~60 bp insertion when compared to other Thiorhodovibrio , potentially upsetting its function. Furthermore, while all three had an operon with flgAMN-fliK-flhB , Trv. frisius contained an additional unique 135 nt open reading frame between flgM and flgN (Thifri_04679). This new gene may be disruptive due to its proximity to a regulator flgM or disturb the transcription of genes downstream in the operon, while the modified fliO may also be the cause of Trv. frisius loss in motility. Future work is needed to confirm either case. Earlier 31 P-NMR measurements had detected phosphatidylglycerol as the dominant phospholipid for Trv. frisius strain 970, followed by diphosphatidylglycerol and phosphatidylethanolamine [ 7 ]. While the other two Thiorhodovibrio spp. also had lysophosphatidylethanolamine and some unusual glycolipids, strain 970 did not ( Figure S2 ). All three contained the respiratory quinones MK-8 and Q-8 ( Table 2 ). The fatty acid profiles were also very similar for all three Thiorhodovibrio species, with the exception of myristic acid only detectable in strain 970 whereas Trv. winogradskyi DSM 6702 T and Trv. litoralis strain 06511 T both contained 11-methyl C 18:1 ω7c fatty acid and lauric acid. 3.3.2. Unusual Light Harvesting The long-wavelength absorption maximum of strain 970 membranes and whole cells was positioned at 963–966 nm, significantly different from the spectra of most closely related Trv. winogradskyi DSM 6702 T and strain 06511 ( Figure 1 d). So far, it represents the only anoxygenic phototrophic bacterium to employ BChl a -containing photosynthetic LH antenna complexes for the absorption of infrared light at wavelengths above 918 nm. Among the Chromatiaceae , red-shifted BChl a containing LH have only been observed in Thermochromatium tepidum ATCC 43061 T , which exhibits a long-wavelength absorption maximum at 918 nm [ 3 ], whereas Thiococcus pfennigii DSM 8320 T and Thioflavicoccus mobilis DSM 8321 T can utilize light at wavelengths above 1000 nm through the use of BChl b [ 47 ]. Based on previous structural modeling, a unique amino acid replacement (αLys 48 → αHis 48 ) in the α-polypeptide of strain 970 has been suggested to be involved in the strongly red-shifted absorption band of BChl a in its LHI [ 6 ]. Cryo-EM structure analysis revealed that the C-terminal domains of LHI bind 16 Ca 2+ ions that are coordinated by amino acid residues which, due to their vicinity and hydrogen-bonds to the BChl a molecule, also cause a red-shift of the strain 970 antenna complexes [ 7 ]. As indicated by the major absorption peak at 966 nm, strain 970 contains LHI as the only type of light-harvesting complex and lacks LHII. Trv. winogradskyi DSM 6702 T and strain 06511 were first found to exhibit peaks at 794 and 867 nm with instrumentation limited to measurements up to 900 nm [ 8 ]. Upon reanalysis with current equipment, Trv. winogradskyi DSM 6702 T and strain 06511 were both shown to have an additional shoulder at 908 nm ( Figure 1 d). Partially purified photosynthetic membranes of strain 06511 ( Figure 3 a) revealed an LHI at ~900 nm bound to RC ( Figure 3 b), and an easily disassociated LHII with maxima around 830–850 nm depending on detergent strength ( Figure 3 c). The LHII shift from 867 to 830 nm when in complex or alone was abnormal, as most LH do not drift as dramatically when purified [ 48 ]. This change may be due to specific complex formation of RC-LHI-LHII, potentially involving Ca 2+ stabilization as documented for strain 970 [ 7 ]. The related Ach. vinosum contains both LHII and LHI resulting in absorption peaks at 800 and 852 nm and a shoulder at 875 nm, respectively. However, these Thiorhodovibrio appear more similar to distantly related Thermochromatium tepidum , which has LH peaks at 800, 852, and 914 nm [ 49 ], comparable to the 796, 869, and 908 nm found here. Future study of Thiorhodovibrio strains DSM 6702 T and 06511 may elucidate by which molecular mechanism such a strong red shift occurs for LHII. Analyzing the Chromatiaceae genomes, it became evident that the photosynthesis genes were dispersed over each chromosome, rather than organized within a single contiguous cluster as in the anoxygenic phototrophic members of the Alpha- and Betaproteobacteria [ 50 ]. While all Thiorhodovibrio sp. had some pufBA genes (encoding the β and α polypeptides LHI) as part of a canonical operon structure with pufLMC , additional pufBA were found in different regions ( Table S6A–C ). First considering the LHI-related components, an earlier combined iPCR/cloning and sequencing strategy had demonstrated that some photosynthesis genes in the puf operon of strain 970 have a typical order where genes pufBA were followed by pufLMC , encoding the L- and M- subunits of the photosynthetic RC, and RC-bound tetraheme cytochrome, similar to most phototrophic Alpha- and Betaproteobacteria . However, the puf operon in strain 970 was atypical since it contained a second pair of LHI genes downstream, which yielded an overall operon structure pufB 1 A 1 LMCB 2 A 2 [ 6 ]. Multiple copies of pufBA sequences have similarly been reported for other Chromatiaceae such as Ach. vinosum and Lamprocystis purpurea [ 51 ]. Our comparative analysis of the photosynthetic gene cluster in related Gammaproteobacteria with closed genomes of Ach. vinosum DSM 180 T and Cgb. litoralis DSM 17192 T revealed that the pufB 1 A 1 LMCB 2 A 2 gene arrangement occurs in both Chromatiaceae subgroups A and B ( Figure 4 ). Based on a cryo-EM study at 2.82 Å resolution, 16 LHI complexes form a multimeric ring-like structure surrounding the RC [ 7 ]. A notable unique feature among all Chromatiaceae genomes, however, is the observation that the entire puf cluster is duplicated in strain 970, and both contain separate combinations of pufBA ( Figure 3 ). Overall, the closed genome of strain 970 encodes five pufA and four pufB genes ( Table S6A ). Interestingly, four (α1–4) and two (β1 and β4) of these polypeptides, respectively, have been detected in strain 970 cells where they occurred in the same LHC I-complex (6 × α1, 1 × α2, 8 × α3, 1 × α4, 3 × β1, 13 × β4; [ 7 ]). The various α- and β-polypeptides observed may be related to the multiple copies of pufBA genes in strain 970, which could be expressed at very different frequency, perhaps depending on the light intensity, and with their associated mRNA transcripts having individual stabilities [ 6 ]. In addition to BChl a , the photosynthetic pigments of strain 970 comprise four different carotenoids. Previous analyses had shown that 3,4,3′,4′-tetrahydrospirilloxanthin was the dominant carotenoid of strain 970, followed by two other carotenoids of the unusual spirilloxanthin pathway, namely 3,4-dihydroanhydrorhodovibrin and 3′,4′-dihydrorhodovibrin, with rhodopin detected in small amounts [ 5 , 43 ]. This carotenoid composition clearly differed from that of the four closely related species and indicated that strain 970 employs the unusual spirilloxanthin pathway ( Table 2 ). 3,4,3′,4′-tetrahydrospirilloxanthin occurs in only few phototrophic bacteria, including the BChl b -containing phototrophic Alphaproteobacterium Rhodospira trueperi [ 4 ] and Gammaproteobacteria Thiococcus pfennigii , Thioflavicoccus mobilis, and Thioalkalicoccus limnaeus [ 47 ], but has also been detected in small amounts in the BChl a -containing Alphaproteobacterium Rhodoplanes pokkaliisoli [ 52 ]. Spirilloxanthin, in contrast, occurs much more frequently and represents the dominant carotenoid in about half of the species of anoxygenic phototrophic Alpha- , Beta- and Gammaproteobacteria , and is also present in Trv. winogradskyi DSM 6702 T and strain 06511 T ( Table 2 ). Spirilloxanthin is synthesized from lycopene through the normal spirilloxanthin pathway involving two consecutive sequences of the acyclic carotene C-1,2 hydratase CrtC, the acyclic carotene C-3,4 desaturase CrtD, and the acyclic 1-hydroxycarotenoid methyltransferase CrtF [ 52 ]. A low activity or absence of CrtD results in the synthesis of carotenoids with saturated 3,4 and 3′,4′bonds, i.e., 3,4-dihydroanhydrorhodovibrin, 3′,4′-dihydrorhodovibrin, and ultimately 3,4,3′,4′-tetrahydrospirilloxanthin. These latter synthesis steps require only the activity of CrtC and CrtF. Correspondingly, crtD mutants of Rhodospirillum rubrum and Thiocapsa roseopersicina have been shown to produce 3,4,3′,4′-tetrahydrospirilloxanthin [ 52 ]. While all genomes had crtCEF located upstream from their bchCXYZ and pufB 1 A 1 LMCB 2 A 2 operons, Trv. frisius had an elongated crtC , but lacked crtD in this location. Instead, crtD was found next to a putative 8′-apo-beta-carotenal 15,15′-oxygenase crt gene (Thiofri_02479; Table S6A ) and hence might be involved in retinal rather than carotenoid synthesis, which would result in the unusual spirilloxanthin pathway becoming active. Another noteworthy alteration of the photosynthesis genes of Trv. frisius strain 970 is the species-specific genetic amalgamation of two proteins for carotenoid biosynthesis, the geranylgeranyl pyrophosphate synthetase, CrtE, and the hydroxyneurosporene methyltransferase, CrtF, to a CrtEF fusion protein ( Table S6A ). This fusion of two genes that are involved at the beginning and the end of the carotenoid synthesis pathway is expected to affect their regulation, which might lead to the accumulation of the intermediates 3,4-dihydroanhydrorhodovibrin and 3′,4′-dihydrorhodovibrin in the unusual spirilloxanthin pathway. 3.3.3. Sulfur and Hydrogen Metabolism As expected, Thiorhodovibrio genomes encoded proteins known to be involved in sulfide oxidation, including sulfide dehydrogenase fccAB , and sulfide:quinone oxidoreductase sqrD/ sqrF for the oxidation of sulfide to elemental sulfur ( Table S7 ), where the latter required manual annotation after comparisons to Thiocapsa roseopersicina [ 53 ]. In Ach. vinosum DSMZ 180 T , Tsp. jenense DSM 216 T , and other Chromatiaceae, the genes encoding dissimilatory sulfite reductase and associated enzymes required for oxidation of sulfur to sulfite are found in a gene cluster dsrABEFHCMKLJOPNRS [ 37 ]. Accordingly, dissimilatory sulfide reductase genes dsrABEF were found in the three Thiorhodovibrio strains, and all fifteen were present once compared to Ach. vinosum DSMZ 180 T ( Table S7 ). Polysulfide reductase psrA of the psrABC cassette was detected solely in strain 970 [ 54 ], peculiarly placed as one of the seven ORFs situated between its duplicate puf clusters. Heterodisulfide reductase hdrABCD -associated genes sdhCDAB were present in all three species [ 55 ]. Additionally, the genes involved in the final conversion of sulfite into sulfate during anoxygenic photosynthesis sat-aprMBA were found [ 56 ], of which aprM had to be curated and only KEGG detected aprBA ( Table S7 ). The genomes of the three Thiorhodovibrio strains also contained some genes involved in assimiliatory sulfate reduction, which is commensurate with the low sensitivity toward molecular oxygen. Sulfate is likely transported using CysA in all three Thiorhodovibrio species. The gene encoding the assimilatory form of adenylylsulfate reductase cysH was found in both Trv. winogradskyi and strain 06511, but these genes were notably flanked by transposases (thiowin_04138/04156; thiosp_02721), likely inferring recent acquisition, particularly due to the absence of any other cys genes. In comparison, Tsp. jenense DSM 216 T lacked all genes for assimilatory sulfate reduction ( cysAWTPBIHDN ) [ 57 ], including cysH , sulfite reductase ( cysI ), and those encoding a sulfate uptake system ( cysAWTP ) being absent [ 26 ]. Thiosulfate utilization is mediated by sox genes [ 58 ]. In Ach. vinosum , sox genes occur in three separate clusters, soxYZ , soxB , and soxXA , all of which are required for thiosulfate oxidation [ 37 ]. While each Thiorhodovibrio genome contained soxYZ , only Trv. litoralis strain 06511 had soxB as well as soxXA completing the thiosulfate oxidation pathway ( Table S7 ). This supported the observed physiology since only strain 06511 was observed to grow with thiosulfate ( Table 2 ). The presence of both soxYZ and soeABC in all three bacteria indicates each could perform sulfite oxidation similar to Ach. vinosum [ 59 ]. Sulfur globules have also been observed in all three Thiorhodovibrio strains ( Figure 1 e,g). Three hydrophobic proteins, sgpA , sgpB , and sgpC , have been suggested to be associated to sulfur-globule envelopes [ 60 ], of which sgpA was annotated twice in the KEGG pathways as sgpA-1 and sgpA-2 in both Trv. frisius and Trv. winogradskyi ( Table S7 ) but not in Trv. litoralis . However, Geneious-based alignment analysis showed these genes to be present in the latter species as well, where sgpA-1 and sgpA-2 correspond to the canonical sgpA and sgpB . A lack of sgpC could be the reason why the size of the intracellular sulfur globules in Thiorhodovibrio spp. is smaller than that in bacteria with all three genes [ 60 ]. Genes for several hydrogenases were discovered in the three species, including hndACE , hoxGHKY , hupC , hyaBC , hybCDO , hyfB , and hypABCDE explaining their use of molecular hydrogen ( Table S8 ). Tsp. jenense DSM 216 T contained the genes hoxHMFYUFE that encode a hydrogenase and used hydrogen, whereas Rch. marinum DSM 5261 T lacked most related genes and correspondingly did not use hydrogen. 3.3.4. Carbon Metabolism All three Thiorhodovibrio species had identical carbon fixation pathways using the complete Calvin–Benson–Bassham cycle including RuBisCo and phosphoribulokinase genes ( Table S9 ). In addition, they also contained a reductive tricarboxylic acid cycle and its associated enzymes idh12 , ppc , and por/nifJ ( Table S9 ), providing an alternative carbon fixation method. Regarding the tricarboxylic acid cycle, it seems to be incomplete and malate dehydrogenase is lacking, in line with the very limited capability to assimilate organic carbon substrates, similar to Tsp. jenense DSM 216 T . Furthermore, Thiorhodovibrio spp. also contained an entire glycolysis/gluconeogenesis pathway that could convert acetate to glucose. This was supported by phenotypic analysis, as both pyruvate and acetate were utilized by all three species ( Table 2 ). Interestingly, only Trv. frisius could metabolize glucose ( Table 2 ), developing atypical thicker cell walls and displaying a thin capsule-like extracellular formation when grown on this monosaccharide ( Figure 1 h). However, none of the Thiorhodovibrio strains contained the recognizable exogenous glucose uptake system crr , or any monosaccharide transporters for glucose such as glcSTUV or gtsABCmalK [ 61 , 62 ]. Upon further review of the KEGG-annotated ABC transporters, however, the Trv. frisius genome was unique as it contained genes for a complete capsular polysaccharide ABC-2 transporter system kpsEMT . These genes are known to transport polymers of glucose and saccharides for capsule formation [ 63 ]. Some ABC transporters have been suggested as bidirectional, capable of importing or exporting small organics such as amino acids [ 64 , 65 ]. The KpsEMT system may thus be involved in glucose uptake and/or the capsule formation of Trv. frisius , warranting follow-up analysis. 3.3.5. Nitrogen Metabolism As with carbon fixation, similar nitrogen-associated pathways existed in each Thiorhodovibrio spp. when analyzed using the KEGG online database, and within Geneious. A set of nifDKH genes for Fe-Mo dinitrogenase and dinitrogenase reductase was present [ 66 ], along with genes for specific regulators including draGT [ 67 ], conferring nitrogen fixation capability in anoxic environments ( Table S10 ). Found in Geneious but not in the KEGG annotation, was a complete set of “ Rhodobacter nitrogen fixation” rnfABCDEFG genes, factors important for electron transport to nitrogenase [ 68 ]. Each species could additionally perform dissimilatory nitrate reduction to nitrite with narI , but not completely to ammonia as they neither had nirBD nor nrfAH . All Thiorhodovibrio spp. lacked the pathways for denitrification, nitrate ammonification, nitrification or annamox capabilities. No assimilatory nitrate reduction was detected in the gene complements, but glutamine and glutamate synthases gltBD and glnA were found respectively, confirming nitrogen could be fixed into ammonia and then incorporated into amino acids. Similarly, Tsp. jenense DSM 216 T contained nifHDKT-nafY encoding Fe-Mo nitrogenase and the genes for nitrate ammonification [ 26 ]. These bacteria thus have a reliance on either an anoxic environment to fix nitrogen, or the presence of ammonia or other fixed nitrogen to grow."
} | 8,717 |
31483640 | null | s2 | 8,032 | {
"abstract": "An electrochemical process has been developed for chemoselective oxidation of primary alcohols in lignin to the corresponding carboxylic acids. The electrochemical oxidation reactions proceed under mildly basic conditions and employ 2,2,6,6-tetramethyl-1-piperidine N-oxyl (TEMPO) and 4-acetamido-TEMPO (ACT) as catalytic mediators. Lignin model compounds and related alcohols are used to conduct structure-reactivity studies that provide insights into the origin of the reaction selectivity. The method is applied to the oxidation of lignin extracted from poplar wood chips via a mild acidolysis method, and the reaction affords a novel polyelectrolyte material. Gel permeation chromatography data for the oxidized lignin shows that this material has a molecular weight and molecular weight distribution very similar to that of the extracted lignin, but notable differences are also evident. Base titration reveals a significant increase in the acid content, and the oxidized lignin has much higher water solubility relative to the extracted lignin. Treatment of the oxidized lignin under acidic conditions results in depolymerization of the material into characterized aromatic monomers in nearly 30 wt% yield."
} | 303 |
37594291 | PMC10508126 | pmc | 8,033 | {
"abstract": "ABSTRACT Here, we sequence and analyze a biofilm-forming strain of Enterococcus faecalis BAU_Ef01 isolated from a shrimp in Bangladesh. The whole genome of the strain had a length of 2,862,301 bp, 38 contigs, an average G+C content of 37.36%, 80.0× genome coverage, and 35 predicted antibiotic resistance and virulence genes each."
} | 83 |
30221210 | null | s2 | 8,034 | {
"abstract": "Microfluidic technologies have been used across diverse disciplines ("
} | 17 |
37577168 | PMC10416014 | pmc | 8,038 | {
"abstract": "Biochar is a carbonaceous porous material that is produced through the thermal processing of biomass under oxygen-limited environment. Nevertheless, biochar is known to be an inexpensive and sustainable raw material with a wide range of possible applications. Recently, biochar has been discovered as an efficient biological catalyst for anaerobic conversion, mainly due to its highly porous structure with micro and macro channels, which procures a viable living area for attached-grown microorganisms. Whereas it is never applied to improve the biological conversion of gas substances such as C1 (e.g., CO, CO 2 ) and H 2 , which is a promising research area with increasing commercial interest. However, considering that biological reaction is limited by the target water solubility of gas substrates, special attention is required when combining biochar for gas fermentation. The goal was to create a novel gas sparger where the biofilm grows on biochar, thus improving the interaction with the gaseous substrate. For this purpose, polystyrene foam and powdered biochar were compounded to form a mouldable composite, which was then cast as a porous monolith. • Biochar-made sparger (BS) was investigated for the homoacetogenic conversion of H 2 gas via microbial mixed cultures as opposed to a control test equipped with a stone sparger. • BS showed a significantly better performance in terms of biological gas fixation rate (36% more than control) and productivity (8.5 g COD L −1 d −1 )."
} | 374 |
35079683 | PMC8777261 | pmc | 8,039 | {
"abstract": "Abstract Diatoms are one of the most successful phytoplankton groups in our oceans, being responsible for over 20% of the Earth's photosynthetic productivity. Their chimeric genomes have genes derived from red algae, green algae, bacteria, and heterotrophs, resulting in multiple isoenzymes targeted to different cellular compartments with the potential for differential regulation under nutrient limitation. The resulting interactions between metabolic pathways are not yet fully understood. We previously showed how acclimation to Cu limitation enhanced susceptibility to overreduction of the photosynthetic electron transport chain and its reorganization to favor photoprotection over light harvesting in the oceanic diatom Thalassiosira oceanica (Hippmann et al., 2017, 10.1371/journal.pone.0181753). In order to gain a better understanding of the overall metabolic changes that help alleviate the stress of Cu limitation, we have further analyzed the comprehensive proteomic datasets generated in that study to identify differentially expressed proteins involved in carbon, nitrogen, and oxidative stress‐related metabolic pathways. Metabolic pathway analysis showed integrated responses to Cu limitation. The upregulation of ferredoxin (Fdx) was correlated with upregulation of plastidial Fdx‐dependent isoenzymes involved in nitrogen assimilation as well as enzymes involved in glutathione synthesis, thus suggesting an integration of nitrogen uptake and metabolism with photosynthesis and oxidative stress resistance. The differential expression of glycolytic isoenzymes located in the chloroplast and mitochondria may enable them to channel both excess electrons and/or ATP between these compartments. An additional support for chloroplast–mitochondrial cross‐talk is the increased expression of chloroplast and mitochondrial proteins involved in the proposed malate shunt under Cu limitation.",
"conclusion": "4 CONCLUSIONS The success of diatoms in the modern ocean is thought to be due to their complex genomic makeup and their successful integration and versatility of metabolic pathways. This was exemplified in the present study, where our proteomic data suggest how interaction among metabolic pathways act to maximize growth in T. oceanica (CCMP 1003) acclimated to severe Cu‐limiting conditions. The differential expression of glycolytic isoenzymes located in the chloroplast and mitochondria may enable them to channel both excess electrons and/or ATP between these compartments. We found additional evidence for chloroplast–mitochondrial cross‐talk in the reciprocal expression of chloroplast and mitochondrial isozymes involved in the proposed malate shunt, which could result in transferring both NAD(P)H‐reducing equivalents and carbon skeletons from the chloroplast to the mitochondria. The upregulation of Fdx was correlated with upregulation of plastidial Fdx‐dependent isoenzymes involved in nitrogen assimilation as well as enzymes involved in glutathione synthesis, thus integrating nitrogen uptake and metabolism with photosynthesis and oxidative stress resistance.",
"introduction": "1 INTRODUCTION Diatoms form an integral part of our oceans, influencing nutrient cycling and productivity of many marine foodwebs (Armbrust, 2009 ). Annually, marine diatoms fix as much carbon dioxide through photosynthesis as all terrestrial rainforests combined (Field et al., 1998 ; Nelson et al., 1995 ), thus having a significant impact on atmospheric CO 2 levels and global climate. One key to their success may lie in their complex evolutionary history (Moustafa et al., 2009 ; Oborník & Green, 2005 ), which resulted in a mosaic genome with genes derived from the original heterotrophic eukaryotic host cell, the engulfed green and red algal endosymbionts, and a variety of associated bacteria (Armbrust et al., 2004 ; Bowler et al., 2008 ; Finazzi et al., 2010 ). As a result, diatoms possess multiple isoenzymes in many metabolic pathways, especially in carbon metabolism (Ewe et al., 2018 ; Gruber et al., 2009 ; Gruber & Kroth, 2014 ; Kroth et al., 2008 ; Smith et al., 2012 ). The presence of multiple isoenzymes with different evolutionary histories also led to novel locations and interactions among metabolic pathways compared with green algal and animal ancestors (Allen et al., 2011 ; Gruber & Kroth, 2017 ). For example, in animals, the complete set of proteins involved in glycolysis is located in the cytosol, whereas in green algae, the first half of glycolysis (glucose to glyceraldehyde‐3‐phosphate, GAP) is located in the chloroplast and the second half (GAP to pyruvate) in the cytosol. In diatoms, an almost complete set of glycolytic proteins is found in both the cytosol and the chloroplast, with an additional set of proteins from the second half of glycolysis located in the mitochondria (Kroth et al., 2008 ; Río Bártulos et al., 2018 ; Smith et al., 2012 ). Furthermore, proteins involved in the ancient Entner–Dourodoff pathway, which is predominantly restricted to prokaryotes and catabolizes glucose to pyruvate, have also been identified in diatom genomes and are targeted to the mitochondria (Fabris et al., 2012 ; Río Bártulos et al., 2018 ). A study by Allen et al. ( 2012 ) illustrates the complexity of isoenzymes in diatoms further: The genome of Phaeodactilum tricornutum encodes five different fructose‐bisphosphate aldolase (FBA) isoenzymes, three targeted to the chloroplast and two to the cytosol (Allen et al., 2012 ). Each FBA has its own phylogenetic history. The expression pattern of these five isoenzymes changes depending on the nutritional status of the cell (Allen et al., 2012 ). One of the most surprising discoveries from diatom genome sequencing was a complete urea cycle (Allen et al., 2011 ; Armbrust et al., 2004 ). In contrast to the catabolic nature of the urea cycle in animals, in diatoms, it is an integral part of cellular metabolism and a hub of nitrogen and carbon redistribution within the cell. It is involved in amino acid synthesis, cell wall formation, and carbon and nitrogen recycling, and it interacts with the citric acid cycle (Allen et al., 2011 ; Armbrust et al., 2004 ). Most molecular studies on acclimation to nutrient limitation have focused on macronutrients, or on the essential micronutrient Fe, which limits phytoplankton in over 30% of the ocean (Moore et al., 2004 ). Some studies have shown an intricate interaction between Fe and Cu nutrition in phytoplankton (Annett et al., 2008 ; Guo et al., 2012 ; Maldonado et al., 2002 ; Maldonado et al., 2006 ; Peers & Price, 2006 ), but there are only a handful of studies on physiological adaptations to Cu limitation alone (Guo et al., 2012 ; Guo et al., 2015 ; Kong & Price, 2020 ; Lelong et al., 2013 ; Lombardi & Maldonado, 2011 ; Maldonado et al., 2006 ; Peers et al., 2005 ; Peers & Price, 2006 ). Our recent comprehensive investigation on the physiological and proteomic changes to the photosynthetic apparatus of two strains of the open ocean diatom Thalassiosira oceanica in response to chronic Cu limitation revealed both similar and different strategies compared with those observed in response to low Fe (Hippmann et al., 2017 ). Acclimation to low Cu caused a bottleneck in the photosynthetic electron transport chain that was accompanied by major increases in the electron acceptors ferredoxin (Fdx) and Fdx:NADP + reductase, which has major roles in counteracting reactive oxygen species (ROS). Along with changes in the composition of the light‐harvesting apparatus, this resulted in a shift from photochemistry to photoprotection. In our previous paper (Hippmann et al., 2017 ), we focused on the photosynthetic electron transport chain and light‐harvesting antennas as well as a number of physiological parameters changed in response to Cu limitation but did not ask how carbon and nitrogen metabolism are affected and may interact when Cu is limiting. We now expand our proteomics analysis to include proteins involved in various carbon and nitrogen metabolic pathways (e.g., Calvin–Benson–Bassham [CBB] cycle, glycolysis, tricarboxylic acid [TCA] cycle, nitrogen acquisition and assimilation, urea cycle, malate shunt, and glutathione metabolism), taking into account their predicted cellular compartments (Table 1 ). Although the decrease in Rubisco activase suggests the CBB is downregulated, there appear to be complex effects on the three‐compartment glycolysis machinery. Increased expression of enzymes involved in nitrogen acquisition and assimilation could act simultaneously as a sink for reducing equivalents and as a supplier of compounds needed to support dissipation of ROS. Finally, we present further evidence for cross‐talk between chloroplast and mitochondria in form of an active malate shunt. TABLE 1 Abbreviations of proteins discussed in this paper Abbreviation Name Abbreviation Name AAT Aspartate aminotransferase GSS Glutathion synthetase ACAS Acetyl‐CoA synthase GST Glutathione‐S‐transferase ACC Acetyl‐CoA carboxylase IDH Isocitrate dehydrogenase ACO Aconitasehydratase LDH \n l ‐Lactate dehydrogenase Agm Agmatinase MDH Malate dehydrogenase AMT Ammonium transporter ME Malic enzyme APX Ascorbate peroxidase NAD(P)H‐NiR Nitrite reductase (NAD(P)H‐dependend) Arg Arginase NR Nitrate reductase argD \n n ‐Acetylornithine aminotransferase NRT Nitrate/nitrite transporter AsL Argininosuccinatelyase OCD Ornithine cyclodeaminase AsuS Argininosuccinate synthase OdC Ornithine decarboxylase ATCase Aspartate carbamoyltransferase OGD 2‐Oxoglutarate dehydrogenase cbbX Rubisco expression protein OTC Ornithine carbamoyltransferase CS Citrate synthase PC Pyruvate carboxylase CYS Cysteine synthase PDH Pyruvate dehydrogenase CYS2 Cysteine synthase PDH‐E1 Pyruvate dehydrogenase‐E1 component DHAR Dehydroascorbate reductase PDH‐E2 Pyruvatedehydrogenase‐ E2 component (dihydrolipoamideacetyltransferase) DLDH Dihydrolipoamide dehydrogenase PEPC Phosphoenolpyruvate carboxylase EDA 2‐Keto‐3‐deoxy phosphogluconate aldolase PEPCK Phosphoenolpyruvate carboxykinase EDD 6‐Phosphogluconate dehydratase PEPS Phosphoenolpyruvate synthase ENO Enolase PFK Phosphofructokinase F2BP Fructose‐1‐6‐bisphosphatase PGAM Phosphoglycerate mutase FBA I Fructose‐bisphosphate aldolase class‐I pgCPSII Carbamoyl‐phosphate synthase FBA II Fructose‐bisphosphate aldolase class‐II PGK Phosphoglycerate kinase Fd Ferredoxin PGM Phosphoglucomutase Fe‐NiR Nitrite reductase (ferredoxin dependend) PK Pyruvate kinase FH Fumarate hydratase PPDK Pyruvate GAPDH Glyceraldehyde 3‐phosphate dehydrogenase rbcL Ribulose‐bisphosphate carboxylase GCS Glutamate‐cysteine ligase rbcS Ribulose‐bisphosphate carboxylase GDCP Glycine decarboxylase p‐protein RPE Ribulose‐5‐phosphate epimerase GDCT Glycine decarboxylase t‐protein RPI Ribose‐5‐phosphate‐isomerase GDH Glutmatae dehydrogenase RuBisCO Ribulose‐bisphosphate carboxylase GDH Glutmatae dehydrogenase SRM Spermidine synthase GOGAT Glutamate synthase SUCLA Succinate CoA synthetase GPI Glucose‐6‐phosphate isomerase TP Triosephosphate GR Glutathione reductase TPI Triosephosphate isomerase GRX Glutaredoxin TXN Thioredoxin GSI Glutamine synthase unCPS (CPSaseIII) Carbamoyl‐phosphate synthase GSII Glutamine synthetase Ure Urease GSIII Glutamine synthetase URT Na/urea‐polyamine transporter",
"discussion": "3 DISCUSSION In response to low Cu, T. oceanica (CCMP1003) restructures the photosynthetic electron transport proteins, resulting in a decrease in carbon assimilation (mg C mg Chl a \n −1 h −1 ), and increased susceptibility to overreduction of the photosynthetic electron transport chain (Hippmann et al., 2017 ). Susceptibility to overreduction of the photosynthetic electron transport chain at saturating light intensities was suggested by (i) the 17% reduction in photochemical quenching ( Fq ′/ Fv ′) and (ii) the light response curves that indicated that the light saturation point decreased well below the actual growth light of 155 umol quanta m −2 s −1 . Growth at saturating light conditions could therefore lead to an increase in ROS. Consequently, there would be an increased need to safely dissipate excess energy, for example, through additional electron sinks (Niyogi, 2000 ). Our findings of a ~40‐fold increase in Fdx (petF) and a 2.5‐fold increase in Fdx:NAD(P)H oxidoreductase (FNR) under Cu limitation (Hippmann et al., 2017 ) suggested that there is indeed a surplus of reduced Fdx (Fd red ) and NAD(P)H in the chloroplast. Here, on the basis of our now expanded proteomic analysis, we hypothesize how the interaction between various metabolic pathways (e.g., nitrogen assimilation, glycolysis, citrate, and the urea cycle) and the sophisticated coordination between the chloroplast and the mitochondria may facilitate the re‐oxidation of Fd red and NAD(P)H in the chloroplast. Protein abundance alone is not always indicative of protein activity, and where known, we have included information on posttranslational activity modulation. We discuss our results with this in mind while suggesting a plausible restructuring of key metabolic pathways in T.oceanica in response to copper limitation. 3.1 Carbon metabolism: The CBB cycle is downregulated via its activase, and glycolysis is used to redistribute ATP and NAD(P)H within the cell The three most thoroughly annotated diatom genomes ( T. pseudonana , Armbrust et al., 2004 ; P. tricornutum , Bowler et al., 2008 ; Fragilariopsis cylindricus , Mock et al., 2017) revealed many isoenzymes, particularly those involved in C metabolism. Indeed, homologous C metabolism isoenzymes exist among and between these diatoms (Gruber & Kroth, 2017 ; Kroth et al., 2008 ; Smith et al., 2012 ), and their differential expression is thought to manage cellular carbon flow. Furthermore, given that within the chloroplast, more than 50% of the proteins involved in glycolysis are also part of the CBB cycle (Smith et al., 2012 ), to regulate C flow, some isoenzymes might be preferentially involved in glycolysis over carbon fixation. For example, in P. tricornutum , the three plastidial FBAs are differently targeted and regulated under low versus high Fe conditions (Allen et al., 2012 ). Here, we hypothesize that to overcome Cu limitation, T. oceanica downregulates the CBB cycle, while modulating glycolysis to promote the redistribution of ATP and NAD(P)H‐reducing equivalents among cellular compartments. Similarly to P. tricornutum under Fe limitation, Cu‐limited T. oceanica also regulates the expression of FBA homologs (Table 4 ), albeit in a different way. While the chloroplast FBA (FbaC2 homolog, To12069) is upregulated, one of the pyrenoid‐associated FBAs is only mildly upregulated (FbaC1 homolog, To00388). This suggests that FbaC2 is preferentially involved in glycolysis over C assimilation, for the following reasons: (i) C assimilation decreased by 66% in Cu‐limited cultures compared with the control (Hippmann et al., 2017 ), suggesting it is less likely for the C fixation proteins to be upregulated; (ii) the three significantly upregulated proteins involved in the CBB cycle can also be part of glycolysis (i.e., PGK, TPI, and FBA, Table 2 ); (iii) none of the distinct CBB cycle proteins (i.e., Rubisco, ribose‐5‐phosphate‐isomerase [RPI], and ribulose‐5‐phosphate epimerase [RPE]) were differentially expressed; (iv) the red algal‐type Rubisco activase (cbbX) was downregulated by 2.25‐fold. The downregulation of cbbX results in slower carbon fixation and activity of Rubisco although Rubisco levels remain unchanged (Mueller‐Cajar et al., 2011 ). Since RPI and RPE abundance remain constant, ribulose‐bisphosphate would be bound to Rubisco. Consequently, once nutrient conditions are favorable, only the cbbX would need upregulation for C fixation to proceed. This strategy might be advantageous in nutrient limited environments with short‐lived nutrient‐rich conditions. TABLE 4 Fructose‐bisphosphate aldolase (FBA) isoenzymes in \n Phaeodactylum tricornutum \n (Pt) and homologs in \n Thalassiosira oceanica \n (To, CCMP 1003): Information on \n P. tricornutum \n as per Allen et al. ( 2012 ) Gene name (Pt) \n a \n \n FBA class \n b \n \n Phylogenetic ancestry \n c \n \n Location in Pt \n d \n \n Pt id \n e \n \n Pt mRNA lowFe \n f \n \n To homolog \n g \n \n Protein ratio lowCu \n h \n \n FbaC1 Class II Chromalveolate specific gene duplication of FbaC2 prior to diversification Chloroplast, Pyrenoid Bd825 ↑ > 25 To00388 ↑ (1.4) FbaC2 Class II Endosymbiotic gene transfer from prasinophyte‐like green algal ancestor Chloroplast, diffuse Pt22993 ↓ < 20 To12069 ↑ (2.0) Fba3 Class II Heterokont host of secondary endosymbiosis Cytosol Pt29014 ↑ > 10 To24977 ± Fba4 Class I Bacterial like (unknown in non‐diatom eukaryotes) Cytosol, putative cytoskeletal interaction Pt42447 ~1 To24978 ↓ (−2.8) FbaC5 Class I Endosymbiotic gene transfer from red algal ancestor (with selective gene loss in some centric diatoms) Chloroplast, Pyrenoid Pt51289 ↑ > 80 To02112 ± Abbreviations: FBA, fructose‐bisphosphate aldolase; Pt, Phaeodactylum tricornutum ; To, Thalassiosira oceanica . \n a \n As per Allen et al. ( 2012 ). \n b \n Class I uses a metal co‐factor, Class II uses a Schiff base. \n c \n As per Allen et al. ( 2012 ). \n d \n As per Allen et al. ( 2012 ) using GFP‐fusion proteins. \n e \n NCBI identifier. \n f \n Fold change of mRNA transcript levels in acute Fe limited versus Fe replete cultures; arrows indicating upregulation and downregulation. \n g \n As per blastP search. \n h \n Fold change of protein levels in chronic Cu limited versus Cu replete cultures. In general, most reactions facilitated by proteins in glycolysis can proceed in either directions, that is, glycolysis or gluconeogenesis. Smith et al. ( 2012 ) suggest that gluconeogenesis prevails in the mitochondria. However, assuming that the required metabolite transporters are present in the mitochondria (e.g., aspartate/glutamate shuttle, malate/2‐oxoglutarate shuttle, citrate/malate shuttle, and fumarate/succinate shuttle), modeling flux balances in P. tricornutum predict that glycolysis would indeed be more favorable than gluconeogenesis in the mitochondria (Kim et al., 2016 ). In T. oceanica , in each cellular compartment, different subsets of glycolytic proteins were upregulated or downregulated under Cu limitation (Figure 4 , Table S4 , overview Figure S5 ). Focusing on the upregulated proteins (Figure S3 ), a pattern emerges relating the possibility of increased ATP formation in the chloroplast and cytosol with NAD(P)H consumption in the chloroplast and its coupled formation in the mitochondria. By reducing chloroplast GAPDH (To13085) and increasing mitochondrial GAPDH (To33331), NAD(P)H‐reducing equivalents would be generated in the mitochondria, whereas increasing PGK (To07617) in the chloroplast would increase ATP in this compartment. Therefore, an increased ATP/NAD(P)H ratio in the plastid would be predicted under Cu limitation. The contrasting differential expression of GAPDH in plastid and mitochondrial compartments suggests the possibility of a key role for triose‐phosphate transporters. Several of them have been identified in T. pseudonana and shown to be located in the chloroplast or its bounding membranes (Moog et al., 2015). A search of our T. oceanica proteome showed one potential mitochondrial transporter, but so far, there is no experimental evidence that any of these is located in the mitochondrial outer membrane. Interestingly, Hockin et al. ( 2012 ) postulated that T. pseudonana increases glycolytic activity when nitrogen starved. However, when we mapped the involved proteins in T. pseudonana to their cellular target compartments, a regulation of isoenzymes similar to the response of Cu‐limited T. oceanica emerged (i.e., PK downregulated in mitochondria and upregulated in the cytosol, Figure S3 , Table S4 ). Thus, the coordinated regulation of particular glycolytic isoenzymes to distribute NAD(P)H‐reducing equivalents and/or ATP production might be a general trait in diatoms. 3.2 Nitrogen metabolism is essential for Fd red oxidation Another striking feature in the response to Cu limitation in T. oceanica was the upregulation of nitrogen acquisition and assimilation as seen in the increased expression of six out of eight proteins involved as well as the electron donor/acceptor Fdx (Figure 5 , Table S6 , overview Figure S5 ). In plants, nitrogen assimilation is an important sink for excess NAD(P)H (Hoefnagel et al., 1998 ). In T. oceanica , the increased expression may alleviate the stress incurred by low Cu, namely, by re‐oxidizing Fd red in the chloroplast. This could be achieved via upregulation of only those NiR isoenzymes that use Fd red as their cofactor (To00016, To02363). Glutamine synthase (GSII, To31900) and the Fd red ‐dependent GOGAT (To13288) were also upregulated, thereby potentially easing the chloroplast electron pressure. The importance of this proposed strategy for Cu‐limited cells is highlighted by the fact that both the membrane‐bound urea (To31656) and nitrate (To04919) transporters are among the 15 highest upregulated proteins in our dataset. 3.3 Counteracting ROS: Glutathione, TXN, and SODs An enhanced nitrogen assimilation increases glutamate, which can be incorporated into (or be a precursor of) glutathione (GSH, γ ‐ l ‐glutamyl ‐l‐ cysteine‐glycine) to detoxify ROS via either direct scavenging or the ascorbate‐glutathione cycle (Foyer & Noctor, 2011 ). Glutathione biosynthesis involves (i) the cytosolic GCL (also known as GCS) that combines glutamate and cysteine to γ‐glutamyl‐ l ‐cysteine and (ii) the plastid glutathione synthase (GSS) that adds glycine. Strikingly, both proteins were upregulated in Cu‐limited T. oceanica . However, in plants, the rate‐limiting step in glutathione production is cysteine biosynthesis (Zechmann, 2014 ). Under Cu limitation, two chloroplast CYS isoenzymes were upregulated (CS, To27524 and To10442; Figure 7 , Table 3 , Table S7 ) suggesting an increase in glutathione production. Furthermore, GST was one of the most highly upregulated proteins (To09062), which would be able to add glutathione to nucleophilic groups to detoxify oxidative stress (Gallogly & Mieyal, 2007 ). The upregulation of GR (To07268), which oxidizes the overabundant NAD(P)H in the chloroplast further supports our hypothesis that in T. oceanica , glutathione counteracts ROS. TXNs are important redox regulators in plants, especially in the chloroplast (Balmer et al., 2003 ), although their role in diatoms is unclear (Weber et al., 2009 ). In T. oceanica , the levels of three TXNs were increased, and each one was targeted to a different compartment: the chloroplast (TXN, To31425), the cytosol (To05213), and the mitochondria (To31425). Another defense mechanism against ROS is the production of SODs, which catalyze the conversion of superoxide radicals into hydrogen peroxide and oxygen. Of the three SODs identified in Cu‐limited cultures, two were upregulated: chloroplast Mn/Fe‐SOD (To02860) and cytosolic Ni‐SOD (To10112). Thus, under Cu limitation, cells may be able to control ROS levels by increasing the expression of both glutathione and SODs. The increase of TXN isoenzymes in all three major cellular compartments (i.e., cytosol, chloroplast, and mitochondria) points to their involvement in sensing the cellular redox state and regulating excess NAD(P)H. 3.4 The malate shunt drains NAD(P)H‐reducing equivalents from the chloroplast to the mitochondria, thus integrating the nitrogen and carbon metabolisms The efficiency of photosynthesis (both electron transport and carbon fixation) depends on an adequate supply of ATP/ADP and NAD(P)H/NAD(P) + (Allen, 2002 ). In plants, the malate shunt can channel excess NAD(P)H‐reducing equivalents from the chloroplast to other cellular compartments, via the differential regulation of MDH isoenzymes (Heineke et al., 1991 ; Scheibe, 2004 ). In this process, NAD(P)H in the chloroplast reduces oxaloacetate (OAA) to malate, a compound that can be transported across membranes and re‐oxidized, resulting in the production of NAD(P)H in the target compartment. NAD(P)H can then be used in reactions such as nitrate reduction in the cytosol or ATP production in the mitochondria. In diatoms, the interaction between the chloroplast and mitochondria is expected to be multifaceted, possibly with direct exchange of ATP/ADP (Bailleul et al., 2015 ) and indirect exchange of NAD(P)H via the ornithine/glutamate shunt (Broddrick et al., 2019 ; Levering et al., 2016 ) and the malate/aspartate shunt (Bailleul et al., 2015 ; Prihoda et al., 2012 ). Some support for the spatial interconnectedness between chloroplast and mitochondria in diatoms has been reported recently (Flori et al., 2017 ). However, the location of the potential transporters needed (e.g., malate/2‐oxoglutarate antiporter and glutamate/aspartate antiporter) have yet to be proven (Bailleul et al., 2015 ; Kim et al., 2016 ). The proteomic patterns we present here support the existence and activation of the malate shunt in T. oceanica in response to low Cu. We observe the increased expression of chloroplast and mitochondrial MDH (MDH2, To30817; MDH1, To03405), as well as mitochondrial AAT (AAT2, To15049, Figure 6 ). As described by Kim et al. ( 2016 ) in P. tricornutum , chloroplast OAA is reduced to malate via MDH2. Malate is then transported into the mitochondria via a putative malate/2‐oxoglutarate antiporter. NAD(P)H‐reducing equivalents are released in the mitochondria via the re‐oxidation of malate to OAA by mitochondrial MDH1. In turn, mitochondrial AAT2 transfers an amine group from glutamate to OAA, thereby releasing aspartate and 2‐oxoglutarate into the mitochondria. To close the cycle, aspartate is transported back, via a glutamate/aspartate antiporter, into the chloroplast where the plastidial AAT isoenzyme would resupply OAA (Kim et al., 2016 ). However, in T. oceanica , chloroplast AAT was significantly downregulated. We suggest that chloroplast OAA, the substrate for MDH2, would be resupplied in the chloroplast via the ATP‐dependent carboxylation of pyruvate due to the significant upregulation of PC. This would lead to a net decrease of NAD(P)H in the chloroplast and a net increase of NAD(P)H in the mitochondria. Furthermore, the channeling of NAD(P)H‐reducing equivalents towards respiration, instead of the CBB cycle, is supported by a 66% decreased in C fixation, while respiration rates remained constant (Hippmann et al., 2017 ). The expected increase in 2‐oxoglutarate and aspartate in the mitochondria, due to an upregulation of mitochondrial AAT2, could be helpful for the cell. If the putative malate/2‐oxoglutarate antiporter is indeed involved in the malate shunt, 2‐oxoglutarate would be transported back into the chloroplast. As chloroplast AAT is downregulated, 2‐oxoglutarate could be used as a substrate for the upregulated Fdx‐dependent GOGAT in nitrogen assimilation. Any surplus 2‐oxoglutarate in the mitochondria could feed into the citrate cycle. Fittingly, aconitase (To20545) and IDH (To34595), the two proteins involved in the citrate cycle immediately before 2‐oxoglutarate, were both significantly downregulated (Figure 3 ). Mitochondrial aspartate can be channeled into the urea cycle, where it will produce argininosuccinate, which can then be diverted back into the mitochondrial citrate cycle as fumarate via the aspartate/fumarate shunt (Allen et al., 2011 ). Thus, even though two of the first three steps in the citrate cycle were downregulated, we hypothesize that the malate shunt in combination with the urea cycle would ensure the continuation of this vital metabolic pathway by supplying it with essential carbon skeletons, that is, 2‐oxoglutarate and fumarate. In addition to the malate shunt, other pathways have been proposed to alleviate electron pressure in diatoms. In P. tricornutum , modeling experiments suggest the prevalence of the glutamine‐ornithine shunt over the malate shunt (Broddrick et al., 2019 ). However, none of the homologs involved in this shunt were identified in Cu‐limited T. oceanica (e.g., n ‐acetyl‐γ‐glutamyl‐phosphate reductase; n ‐acetylornithine aminotransferase). Furthermore, the activation of alternative oxidase (AOX) in Fe‐limited P. tricornutum to alleviate electron stress in the impaired mitochondrial respiration (Allen et al., 2008 ) was not observed in Cu‐limited T. oceanica (Hippmann et al., 2017 ). Future research is needed to elucidate the regulation of shuttle system/compartmental cross talks in diatoms."
} | 7,159 |
23039250 | null | s2 | 8,040 | {
"abstract": "We investigated the phenomenon of incomplete wetting of a high-energy liquid subphase by drops of pure amphiphilic molecules as well as drops of amphiphile solutions that are immiscible with the subphase. We show that amphiphiles escape across the contact line of the drop, move on the subphase/vapor interface, and form a submonolayer or full monolayer external to the drop. If this monolayer is sufficiently dense, then it can reduce the surface tension of the subphase, raise the contact angle of the drop, and prevent the drop from fully wetting the subphase. This phenomenon is called autophobing and has been extensively studied on solid substrates. For the liquid subphase studied here, we measure the surface tensions of the three relevant interfaces before and after the drop is deposited. The measured surface tension external to the drop shows that amphiphiles can move across the contact line and form a monolayer outside of the drop. In some cases, at equilibrium, the monolayer is in a sufficiently packed state to create the nonwetting condition. In other cases, at equilibrium the monolayer density is insufficient to lower the surface tension enough to achieve the nonwetting condition. Unlike on solid substrates where the formation of the monolayer external to the drop is kinetically hindered, the amphiphiles can move rapidly across the liquid subphase by Marangoni-driven surface transport, and local equilibrium is achieved. However, because the amphiphile inventory and subphase area are limited, the achievement of autophobing on a liquid subphase depends not only on the instrinsic subphase/amphiphile interaction but also on the total amphiphile inventory and area of the liquid subphase."
} | 428 |
29374483 | PMC5787283 | pmc | 8,042 | {
"abstract": "Background We previously developed an E. coli strain that overproduces medium-chain methyl ketones for potential use as diesel fuel blending agents or as flavors and fragrances. To date, the strain’s performance has been optimized during growth with glucose. However, lignocellulosic biomass hydrolysates also contain a substantial portion of hemicellulose-derived xylose, which is typically the second most abundant sugar after glucose. Commercialization of the methyl ketone-producing technology would benefit from the increased efficiency resulting from simultaneous, rather than the native sequential (diauxic), utilization of glucose and xylose. Results In this study, genetic manipulations were performed to alleviate carbon catabolite repression in our most efficient methyl ketone-producing strain. A strain engineered for constitutive expression of xylF and xylA (involved in xylose transport and metabolism) showed synchronized glucose and xylose consumption rates. However, this newly acquired capability came at the expense of methyl ketone titer, which decreased fivefold. Further efforts were made to improve methyl ketone production in this strain, and we found that two strategies were effective at enhancing methyl ketone titer: (1) chromosomal deletion of pgi (glucose-6-phosphate isomerase) to increase intracellular NADPH supply and (2) downregulation of CRP (cAMP receptor protein) expression by replacement of the native RBS with an RBS chosen based upon mutant library screening results. Combining these strategies resulted in the most favorable overall phenotypes for simultaneous glucose–xylose consumption without compromising methyl ketone titer at both 1 and 2% total sugar concentrations in shake flasks. Conclusions This work demonstrated a strategy for engineering simultaneous utilization of C 6 and C 5 sugars in E. coli without sacrificing production of fatty acid-derived compounds. Electronic supplementary material The online version of this article (10.1186/s12934-018-0862-6) contains supplementary material, which is available to authorized users.",
"conclusion": "Conclusions In this study, genetic manipulations were conducted to alleviate carbon catabolite repression in our most efficient methyl ketone-producing strain. A strain (XW1014) with constitutively expressed xylA and xylF plus a xylA promoter mutation showed well-synchronized glucose and xylose consumption rates. However, this newly acquired capability came at the expense of methyl ketone titer, which decreased fivefold. Further efforts were made to optimize methyl ketone production in this strain, and we found that chromosomal deletion of pgi (to enhance NADPH supply) and CRP downregulation by replacement of the native RBS both effectively improved methyl ketone production. Combining these strategies resulted in the most favorable overall phenotypes for simultaneous glucose–xylose consumption without compromising methyl ketone titer (Figs. 5 , 6 ). Further optimization of performance will entail improved fermentation process conditions as well as additional genetic modifications.",
"discussion": "Results and discussion Engineering simultaneous glucose–xylose utilization in methyl ketone-overproducing strain EGS1895 We engineered several strains by manipulating key genes in pentose metabolism (XW1014, XW1024, and XW1044; Tables 1 , 2 ) and evaluated their ability to simultaneously utilize glucose and xylose (Fig. 1 ). The control strain, EGS1895, presented a typical diauxic pattern in which xylose utilization began after glucose was fully depleted. In contrast, newly engineered strains displayed glucose–xylose co-utilization to varying degrees rather than a strict diauxic profile. Among these engineered strains, XW1014 (with constitutive expression of xylA and xylF plus a point mutation in the xylA promoter, xylA up ) showed the best performance for simultaneous utilization of glucose and xylose (Fig. 1 ). This strain had identical consumption rates for glucose and xylose at 1% sugar conditions, while a slight decrease in xylose consumption was observed at higher sugar concentration (2%). The inactivation of araE (XW1024; Tables 1 , 2 ) did not result in better sugar co-utilization than was observed for strain XW1014, nor did the manipulations made for strain XW1044 (alleviating AraC-mediated repression through four collective araC -related manipulations, including araC deletion from both the genome and plasmid as well as replacement of promoters for araB and araF ). Although both strains XW1024 and XW1044 showed favorable simultaneous consumption rates of glucose and xylose at 1% sugar conditions, their xylose consumption dramatically decreased at higher sugar concentration (2%). Fig. 1 Evaluation of glucose–xylose co-utilization in engineered strains (96 h). Symbols: glucose, blue lines; xylose, green lines; 1% total sugars, dashed lines; 2% total sugars, solid lines. Error bars indicate one standard deviation ( n = 3, except for XW1004, for which n = 2) \n In addition, because ptsG deficiency is a well-studied mechanism for mitigating CCR in E. coli [ 10 ], the glucose transporter EIIBC Glc encoded by ptsG was deleted from EGS1895 to investigate the effect on sugar co-utilization (strain XW1004; Table 1 ). Strain XW1004 did not display a better sugar co-utilization profile than strain XW1014 (Fig. 1 ). Methyl ketone production was also investigated among these strains engineered for hexose–pentose co-utilization. Compared with the titer of the control strain EGS1895 (~ 690 mg L −1 ), methyl ketone production was significantly reduced in all four modified strains (Fig. 2 ). The best performing strain for sugar co-utilization, XW1014, only produced ~ 140 mg L −1 total methyl ketones (1% total sugars), which is approximately fivefold lower than for strain EGS1895. Strains with more genetic manipulations produced even lower methyl ketone titers; for example, strains XW1024 and XW1044 produced < 60 mg L −1 methyl ketones. Although the Δ ptsG strain (XW1004) showed the highest methyl ketone titer among these four strains, its diminished glucose utilization was not optimal and it was not pursued further. Despite its relatively low methyl ketone titer, strain XW1014 had the most favorable combination of sugar co-utilization and methyl ketone production of the strains tested. Fig. 2 Methyl ketone production by strains engineered for glucose–xylose co-utilization (1% total sugars, 96 h). Error bars indicate one standard deviation ( n = 3, except for XW1004, for which n = 2) \n Optimization of methyl ketone production in strain XW1014 by enhancing NADPH availability Although strain XW1014 was successfully engineered for simultaneous glucose–xylose consumption, the significantly reduced methyl ketone titer in this strain necessitated further engineering to improve commercial relevance. We hypothesized that enhancing NADPH availability could be a fruitful engineering target because (1) the biosynthesis of fatty acids (methyl ketone precursors) in E. coli is an NADPH-demanding process and (2) xylose metabolism, particularly when simultaneous with glucose metabolism, could disrupt NADPH production in a host cell (e.g., strain XW1014) compared to conditions with glucose as a sole carbon source. Fatty acid biosynthesis results in net consumption of NADPH due to demand from two key reductases—FabG (β-ketoacyl-ACP reductase) and potentially, FabI (enoyl-ACP reductase), which can utilize either NADH or NADPH as a cofactor [ 1 , 26 ]. To illustrate the substantial NADPH demands of fatty acid/methyl ketone biosynthesis, production of 1 mol of a C 13 methyl ketone (2-tridecanone) from glucose using the relevant metabolic pathway [ 2 ] would result in net consumption of 6 (or 12) mol of NADPH and net production of 9 (or 15) mol of NADH, depending on FabI cofactor usage. By virtue of where xylose enters central carbon metabolism in E. coli , xylose metabolism tends to result in less flux than glucose metabolism through the oxidative, NADPH-generating steps of the pentose phosphate pathway (PPP), namely reactions catalyzed by glucose-6-phosphate dehydrogenase (Zwf) and phosphogluconate dehydrogenase (Gnd); however, xylose metabolism can take advantage of other sources of NADPH, such as malic enzyme and transhydrogenase [ 27 ]. The situation is likely more complex when considering sugar utilization and NADPH production in strain XW1014 compared to that in control strain EGS1895. Compared with the sequential metabolism from glucose to xylose during diauxic growth (strain EGS1895), simultaneous metabolism of glucose and xylose (strain XW1014) could alter NADPH production by re-distributing flux between glycolysis and the PPP. For example, it is possible that the flux of glucose carbon through the oxidative PPP might be reduced when xylose co-utilization is occurring, because xylose metabolism will satisfy the cell’s needs for downstream PPP metabolites required for anabolism, such as erythrose 4-phosphate (needed for aromatic amino acid biosynthesis) and ribose 5-phosphate (needed for nucleic acid biosynthesis). We implemented two strategies for increasing NADPH supply in strain XW1014: (1) deleting pgi (glucose-6-phosphate isomerase) from the chromosome to divert flux from glycolysis through the oxidative PPP (Fig. 3 ) and (2) overexpressing maeB (malic enzyme), which leads to NADPH generation by oxidative decarboxylation of malate to pyruvate (Fig. 3 ). 13 C Metabolic flux analysis studies in E. coli have shown that pgi deletion results in substantial production of NADPH by diversion of flux from glycolysis through the oxidative PPP, and that excessive accumulation of NADPH (cofactor imbalance) in Δ pgi strains can be at least partially ameliorated by NADPH consumption through transhydrogenase [ 28 , 29 ]. In our Δ pgi strain (XW1054; Table 1 ), it was anticipated that a portion of the NADPH made available by the pgi deletion might facilitate fatty acid/methyl ketone biosynthesis by better satisfying its high NADPH demands than did central carbon metabolism in strain XW1014. Fig. 3 Overview of central carbon metabolism in E. coli highlighting strategies (in red) to improve NADPH supply in the sugar co-utilizing strain XW1014. G6P, glucose 6-phosphate; F6P, fructose 6-phosphate; FBP, fructose 1,6-bisphosphate; DHAP, dihydroxyacetone phosphate; GAP, glyceraldehyde 3-phosphate; 13BPG, 1,3-bisphosphoglycerate; 3PG, 3-phosphoglycerate; 2PG, 2-phosphoglycerate; PEP, phosphoenolpyruvate; Pyr, pyruvate; AcCoA, acetyl-CoA; 2KG: 2-ketoglutaric acid; 6PGL, 6-phosphogluconolactone; 6PG, 6-phosphogluconate; Ru5P, ribulose 5-phosphate; R5P, ribose 5-phosphate; X5P, xylulose 5-phosphate; S7P, sedoheptulose 7-phosphate; E4P, erythrose 4-phosphate; pgi , glucose 6-phosphate isomerase; maeB , malic enzyme; zwf , glucose 6-phosphate dehydrogenase; gnd , phosphogluconate dehydrogenase \n Production results showed that the Δ pgi strain (XW1054) had dramatically improved methyl ketone titer (850 mg L −1 ) relative to strain XW1014 after 96 h at 1% total sugar conditions (Fig. 4 ); this methyl ketone titer was comparable to that of the control strain (EGS1895). Under 2% total sugar conditions, the methyl ketone titer of strain XW1054 (~ 1300 mg L −1 after 96 h) was also comparable to that of strain EGS1895 (~ 1600 mg L −1 ). However, xylose showed a slower consumption rate than glucose after pgi was deleted, and slower cell growth was also observed during production. In contrast to methyl ketone titer improvement for strain XW1054, the overexpression of maeB with or without pgi deletion (strains XW1055 and XW1018; Table 1 ) did not result in improvement in methyl ketone production (Additional file 1 : Figure S1). Fig. 4 Shake flask production data (growth, methyl ketone production, sugar consumption) for strains engineered for sugar co-utilization (Table 1 ) and control strain EGS1895. Symbols: glucose, blue lines; xylose, green lines; OD 600 , black lines; methyl ketones, red lines; 1% total sugars, dashed lines; 2% total sugars, solid lines. The starting OD 600 was ca. 0.01. Error bars indicate one standard deviation ( n = 3) \n Based upon the results for strain XW1054 (Δ pgi ), it is possible that NADPH is more limiting when xylose is used as a carbon source. Indeed, we observed that the control strain (EGS1895) produced very low methyl ketone titers when xylose was used as the sole carbon source in minimal medium (Additional file 1 : Figure S2). Optimization of methyl ketone production in strain XW1014 by mutating the RBS of crp While enhancing potential NADPH supply (via pgi deletion) substantially improved methyl ketone production with mixed glucose–xylose medium, several lines of evidence suggested that the engineered strains were experiencing suboptimal sugar utilization (e.g., strain XW1054 in Fig. 4 ), and potentially, suboptimal methyl ketone production, that had causes beyond NADPH limitation. For example, NADPH limitation alone does not seem to explain the dramatic reduction in methyl ketone titer in both strain XW1004 (Δ ptsG ) and strain XW1014 (introduced constitutive promoters to xylA and xylF ) (Fig. 2 ), as these genetic modifications are not clearly linked to NADPH supply. A possible explanation for these results is changes in intracellular distributions of the global regulator CRP. For strain XW1014, promoter replacement for xylA and xylF resulted in removal of a CRP binding site from the intergenic region between xylA and xylF [ 30 ]. As a global regulator, CRP not only plays an important role in carbon catabolite repression, but also controls the transcription of more than 100 genes in E. coli , such as key genes in fatty acid metabolism (e.g., fadD, fadH ) [ 31 ] and in central carbon metabolism (e.g., pgi , zwf , gnd ) [ 30 , 32 ]. Thus, the promoter change in strain XW1014 might have altered the level of free CRP and directly and indirectly affected the transcription of many other genes related to fatty acid metabolism. Similarly, changes to intracellular CRP pools might also explain why methyl ketone production was reduced in the Δ ptsG strain (XW1004): the absence of PtsG likely increased cAMP availability [ 33 ], and in turn, altered the level of free intracellular CRP, which interacts with cAMP to make the cAMP–CRP complex. Based on this reasoning, one possible strategy for improving methyl ketone production is to optimize the expression level of CRP in strain XW1014. We attempted to modulate CRP availability by replacing the native crp RBS with synthetic RBSs of varying strengths. We created a mutant crp RBS library with broad range of predicted TIR values (8–7290 au, Additional file 1 : Table S2). A total of 7 RBS variants with different TIRs were identified by sequencing from the mutant library. Screening of this library was conducted with 5-mL cultures in M9-MOPS medium (50-mL test tubes), and one mutant (strain XW1064) was selected that showed significant improvement in methyl ketone production (~ 900 mg L −1 after 96 h with 1% total sugars, Additional file 1 : Figure S3). Notably, the predicted TIR of strain XW1064 was 13 au, which is approximately 188-fold lower than the predicted native TIR (2441 au) of crp . Scaled up production of strain XW1064 in 250-mL shake flasks resulted in methyl ketone titers up to ~ 450 mg L −1 without compromised cell growth (Fig. 4 ). This result supported our hypothesis that optimized expression of CRP is able to improve methyl ketone production in the strains engineered for glucose–xylose co-utilization. However, we also noticed that the consumption rate of xylose in strain XW1064 was slower than that of glucose, especially under 2% total sugar conditions (Fig. 4 ). Seeking the best candidate by combining engineering strategies Given the complementary features of the above strategies (Δ pgi and CRP downregulation) on cell growth and methyl ketone production, and the fact that they both effectively improved methyl ketone production in strain XW1014, we decided to combine these two strategies to obtain an additive effect. Overall, combining Δ pgi and CRP downregulation (strain XW1074; Table 1 ) created superior phenotypes in cell growth and methyl ketone production compared to use of either strategy alone (Fig. 4 ). This strain produced up to 570 mg L −1 methyl ketones at 1% total sugar conditions, but reached a higher titer at 2% total sugars (~ 1600 mg L −1 ) that was comparable to that of the control strain (EGS1895). Glucose and xylose were simultaneously consumed by strain XW1074 (Fig. 4 ) after a lag period, but utilization of xylose was still slower than that of glucose. Surprisingly, the added maeB overexpression (strain XW1075) dramatically improved sugar co-utilization (albeit with the same lag period, likely caused by pgi deletion; [ 34 , 35 ]). As a result, strain XW1075 achieved synchronized consumption rates for glucose and xylose at both 1 and 2% total sugar conditions. Methyl ketone titers in strain XW1075 were up to 700 and 1100 mg L −1 at 1 and 2% total sugars, respectively. Thus, these two strains engineered with combined strategies (XW1074 and XW1075) represented a favorable phenotype displaying simultaneous utilization of glucose and xylose without substantially sacrificing methyl ketone production relative to the control strain (EGS1895) (Figs. 4 , 5 ). Fig. 5 Summary comparison of methyl ketone production and sugar consumption for engineered strains. Methyl ketone yield, methyl ketone productivity, and sugar consumption period are each normalized to the maximum value among the six strains (for cultivation with 2% total sugars). Blue, methyl ketone yield from glucose + xylose consumed (g methyl ketones g −1 total sugars); red, methyl ketone productivity during the sugar consumption period (from onset of sugar consumption to > 90% total sugar consumption; g L −1 h −1 ); green, the reciprocal of sugar consumption period (as defined for productivity; the reciprocal was used to make the most favorable consumption phenotype approach 1 instead of 0 for ease of comparison) \n Strain XW1075 performance during batch fermentation Strain XW1075 also compared favorably to control strain EGS1895 in batch fermentation mode. Glucose and xylose were utilized concurrently in strain XW1075 (albeit at unequal rates), whereas strain EGS1895 displayed a typical diauxic pattern, including sequential sugar utilization (Fig. 6 ). Correspondingly, strain XW1075 had a more consistent methyl ketone production yield (8.7–9.8%) than the control strain (6.9–10.0%). At 72 h, the methyl ketone titer of strain XW1075 was 2 g L −1 , which was ca. 33% higher than that of strain EGS1895 (1.5 g L −1 ). Fig. 6 Batch fermentation of strains EGS1895 and XW1075 in 2-L bioreactors. Symbols: glucose, blue line; xylose, green line; cell dry weight (CDW), black line; methyl ketones, red line; yield, purple line Comparison of the results in Fig. 6 with those of strains XW1075 and EGS1895 grown with pure glucose or xylose (Additional file 1 : Figure S2) reveals that co-utilization of glucose and xylose in strain XW1075 enabled substantially better methyl ketone production than did utilization of either sugar alone. In fact, methyl ketone production was negligible for strain XW1075 utilizing either pure glucose or pure xylose (Additional file 1 : Figure S2). Notably, strain EGS1895 also produced negligible methyl ketones when grown on pure xylose (Additional file 1 : Figure S2), but produced substantial methyl ketones while metabolizing xylose after diauxic depletion of glucose (Fig. 6 ). From Figs. 4 and 6 , it appears that glucose metabolism supported both growth and methyl ketone production in strain EGS1895, whereas xylose metabolism supported methyl ketone production but little or no growth."
} | 4,989 |
37938401 | PMC9723598 | pmc | 8,043 | {
"abstract": "Southern Ocean (SO) diatoms play an important role in global carbon flux, and their influence on carbon export is directly linked to interactions with epiphytic bacteria. Bacterial symbionts that increase diatom growth promote atmospheric carbon uptake, while bacterial degraders divert diatom biomass into the microbial loop where it can then be released as carbon dioxide through respiration. To further explore SO diatom-bacterial associations, a natural model system is needed that is representative of these diverse and important interactions. Here, we use concurrent cultivation to isolate a species of the ecologically-important SO diatom, Pseudo-nitzschia subcurvata , and its co-occurring bacteria. Although vitamin-depleted, axenic Pseudo-nitzschia grew poorly in culture, addition of a co-isolated Roseobacter promoted diatom growth, while addition of a co-isolated Flavobacterium negatively impacted diatom growth. Microscopy revealed both bacterial isolates are physically associated with diatom cells and genome sequencing identified important predicted functions including vitamin synthesis, motility, cell attachment mechanisms, and diverse antimicrobial weapons that could be used for interbacterial competition. These findings revealed the natural coexistence of competing symbiotic strategies of diatom-associated bacteria in the SO, and the utility of this tripartite system, composed of a diatom and two bacterial strains, as a co-culture model to probe ecological-relevant interactions between diatoms and the bacteria that compete for access to the phycosphere.",
"introduction": "Introduction Single-celled photosynthetic eukaryotes, particularly diatoms, are the main primary producers in polar oceans, forming massive annual blooms and comprising the base of the polar food chain [ 1 ]. Although these organisms are microscopic, their collective numbers are sufficient to influence the biogeochemistry of the planet, supplying a significant fraction of the Earth’s oxygen [ 2 ]. Marine bacteria are also highly abundant in seawater [ 3 ], playing important roles in assimilating and decomposing a significant portion of the organic carbon fixed by diatoms [ 4 – 8 ]. Together, phototrophic eukaryotes and heterotrophic bacteria constitute components of the “microbial loop”, where phytoplankton and bacteria contribute significantly to the cycling of carbon and other important nutrients [ 9 ]. Furthermore, bacteria are known to directly compete with phytoplankton for resources, such as iron (Fe); and resource availability (light, dissolved organic carbon, Fe) have been modelled to directly regulate ecological phytoplankton-bacterial interactions [ 10 ]. Emerging work has also revealed that important symbiotic relationships (i.e., “the living together of differently named organisms” [ 11 ]) exist between phytoplankton and heterotrophic bacterial cells [ 8 , 12 ]. For example, many diatoms cannot synthesize essential vitamins or detoxify byproducts from their own metabolism and require the help of specific symbiotic bacteria to fulfill these roles [ 13 , 14 ]. In turn, the bacterial partners receive organic carbon and other nutrients excreted from diatom cells that support bacterial growth [ 15 ]. Thus, these mutually-beneficial symbiotic relationships, or mutualisms, allow both phytoplankton and marine bacteria to flourish in an otherwise harsh environment. Some bacterial species can colonize the phycosphere, the diffusive boundary layer around individual diatom cells that is rich in the organic and inorganic compounds released by the diatom [ 8 , 16 ]. Indeed, several studies characterizing the prevalence and diversity of bacteria attached to diatoms in situ found the proportion of phytoplankton cells with attached bacteria varied widely (5–80%) with abundance of attached bacteria ranging from 1–61 bacterial cells per diatom [ 17 , 18 ]. The attached microbiome for a given cell contained between one and eleven bacterial phylotypes [ 17 ], and others showed that the relative abundance of attached bacterial phylotypes changed significantly with the growth state of the diatom host and nutrient availability [ 19 ]. Taken together, these studies suggest that phytoplankton commonly have attached bacteria and these associations can by influenced by both biotic and abiotic factors. Because the symbiotic relationship between phytoplankton and bacteria, which can be mutualistic or parasitic, is built around the chemicals exchanged between partners [ 5 , 8 ], mechanisms have evolved to promote select partner matching to favor mutual benefits [ 20 ]. For example, certain marine bacteria preferentially swim toward the unique chemical cocktail released by specific phytoplankton species [ 16 ]. Once the association is established, both partners are thought to have evolved strategies to maintain close physical contact: diatoms may retain bacterial symbionts in excreted mucus [ 21 ], or bacteria may use surface-exposed proteins to adhere directly to the phytoplankton cell [ 22 ]. Results from in situ characterization and coculture approaches have begun to dissect the specifics of these interactions and revealed that bacteria likely compete for access to the phycosphere, with the winner of this interbacterial competition having vastly different effects on the phytoplankton cell, based on their ecological role as a growth promoter (i.e., mutualistic) or a degrader (i.e., parasitic) [ 8 ]. For example, diatom-associated bacteria are known to provide nutrients (eg. vitamins, Fe and NH 4 ) [ 5 , 6 ], deter invasion by other opportunistic bacteria [ 23 , 24 ], or directly lyse/degrade diatom cells [ 25 ]. Although much of the past work on phytoplankton-bacterial interactions has focused on temperate regions, these symbiotic associations are also critical in polar habitats, such as the Southern Ocean (SO). The SO accounts for 40% of anthropogenic CO 2 uptake [ 26 ], but phytoplankton growth here is often limited by low Fe availability, with seasonal colimitation by light [ 27 , 28 ]. Additional evidence shows that diatom blooms are often B vitamin (e.g., B 1 , B 7 and B 12 ) limited, due to the roles these vitamins play as co-factors in essential enzymes [ 29 ]. Moreover, B vitamins are biologically derived, and therefore can be growth limiting to organisms that cannot synthesize their own B vitamins, relying on an external biological source for their own needs [ 30 ]. Pseudo-nitzschia is a genus of pennate diatom encompassing over 50 species that are globally distributed [ 31 ] and numerically abundant in the SO, where it comprises 13–71% of diatoms in the Weddell Sea [ 32 – 35 ]. Examined members of this genus have an obligate requirement for cobalamin (Vitamin B 12 ) as a co-factor in the methionine synthase enzyme (MetH), and do not contain the cobalamin-independent methionine synthase (MetE) [ 36 ], suggesting that the diatom obtains cobalamin externally, likely through interactions with B 12 -producing bacteria. However, in order to directly test such hypotheses, lab-based experiments would be preferred over those in situ because a lab setting would allow for better control of variables such as the presence of specific phytoplankton and bacterial species, as well as abundance of macronutrients, micronutrients, and trace metals. Despite the broad ecological importance of SO diatoms, we are lacking a natural, co-evolved culture-based model system that is representative of complex diatom-bacterial interactions that can be interrogated in the lab. Particularly for bacterial-diatom interactions that are close physical associations. Such a coculture model system would allow researchers to directly test in the lab hypotheses generated from in situ observations and even develop predictions as to how future climate conditions might impact these critical symbiotic associations and their contributions to nutrient cycling, oxygen production, and carbon export. To fill this knowledge gap, we reasoned that if growth promoters and degraders are physically associated with SO diatoms, we could design an approach to concurrently cultivate both partners in isolation and add them back together to determine the fate of the interactions. To this end, we identified four bacteria that are closely associated with the SO diatom Pseudo-nitzschia subcurvata , two of which have positive or negative growth effects under multi-vitamin-depleted conditions. Finally, the genomes of these bacterial isolates reveal insights into their metabolic strategies that may be coordinated by light-responsive transcriptional regulators and indicate their predicted capabilities to kill bacterial competitors.",
"discussion": "Discussion Our study revealed several successful strategies for concurrent isolation of diatom and closely-associated bacteria from SO water. First, we isolated bacterial representatives from the 3 µm fraction of a SO phytoplankton enrichment culture to favor bacteria that are attached to phytoplankton cells. We chose three phylogenetically diverse isolates obtained from this approach for our coculture experiments: Pseudoalteromonas sp. A1, Olleya sp. A30, and Colwellia sp. A38. Species of these genera have been previously isolated from other polar environments [ 30 , 54 , 57 , 58 ]. Moreover, species from the genera Pseudoalteromonas, Olleya , and Colwellia , have been reported to produce ecologically important exudates, including fatty acids/lipids, antimicrobials, agarolytics, and exopolysaccharides [ 54 , 57 , 59 , 60 ] Olleya species are well-known degraders and members of the ‘marine clade’ of the Flavobacteriaceae , which contribute significantly to the remineralization of organic matter [ 61 ]. Of the three isolates we selected, two were found to physically associate with P. subcurvata cells in coculture (Fig. 5 ), validating our method for isolating closely-associated bacterial strains. Our second approach to isolate a diatom-specific epiphyte was to culture directly from the xenic monoclonal diatom culture that was derived from the initial SO enrichment culture, and therefore carried its bacterial epiphytes through many passages in culture. Using this approach, we cultured two bacterial morphotypes: Sulfitobacter sp. SA1, and SA3, which was a mix of Glaciecola sp. and Salegentibacter sp. Among these cultured representatives, one promoted the growth of P. subcurvata (SA1) in the absence of B vitamins and both were seen to physically associate with P. subcurvata cells in coculture. Sulfitobacter species have previously been isolated from temperate Pseudo-nitzschia species [ 5 , 62 ], and are observed to induce a range of interactions including production of the growth hormone indole-3-acetic acid (auxin) and degradation of DMSP produced by the diatom host. Glaciecola species have previously been associated with diatom blooms in cold waters [ 58 ]. Thus, these approaches could be used to isolate physically-associated, ecologically-relevant partners from diverse aquatic habitats. Our data also indicate that the naturally associated bacterial community co-occurring with P. subcurvata in the xenic cultures is required for survival in stationary phase (Fig. 3B ). Stationary phase can be induced due to nutrient (N, Si or P) limitation in a closed system, such as the one used here. Previous work has shown that, under N-limitation, bacterial addition can reduce diatom mortality, suggesting that bacteria can help remineralize N to prolong diatom survival [ 63 ]. While the mechanism by which one or more of the native bacterial species promote P. subcurvata survival is not yet known, one possibility is that native bacteria are able to provide P. subcurvata with remineralized forms of nitrogen (e.g., ammonium) [ 63 ]. Together, these findings indicate that the relationship between bacteria and diatoms is complex, and the roles of each partner likely differ based on environmental conditions and physiological capabilities. Our concurrent isolation approaches identified two bacterial isolates that differentially affected diatom growth in positive and negative ways (Fig. 4E ). In B vitamin deplete cultures, Sulfitobacter sp . SA1 increased growth of the diatom compared to the control, suggesting that SA1 supports some of the vitamin requirements of this diatom, even though these cocultures did not achieve the same high growth rate as that of vitamin-replete cultures (Fig. S2 ). This result aligns with findings that diatom abundance in the SO responds positively to the addition of bacterial-derived B 12 and Fe [ 29 ], and others have reported the addition of B 12 -producing bacteria can enhance phytoplankton growth [ 13 , 30 ]. Evidence of biotin, thiamine, and B 12 biosynthesis genes were found in Sulfitobacter sp. SA1, supporting our observation that physically attached Sulfitobacter sp. SA1 can improve growth of a diatom under vitamin-limiting conditions, even though it appears Pseudo-nitzschia species may produce their own biotin [ 64 ]. Sulfitobacter sp. SA1 may promote diatom growth in other ways. For example, the Antarctic diatom Amphiprora kufferathii is found with attached Sulfitobacter and Colwellia species, and these epiphytic bacteria provided antioxidant functions in the form of catalase activity to promote diatom growth [ 65 ]. Our Sulfitobacter sp. SA1 isolate encodes catalase (Table 2 ), and could similarly help P. subvurvata detoxify metabolic byproducts, in addition to supplying the diatom with essential vitamins. It is not surprising that Olleya sp. A30 negatively impacted diatom growth, given that it lacks the genes to synthesize B 12 , but encodes genes to degrade diatom-derived organic compounds, and was commonly observed to occur within empty frustules, suggesting an ability to invade and consume diatom cells. If Olleya sp. A30 cannot synthesize its own B 12 it would contribute to the uptake of, and competition for B 12 in the SO; directly competing with diatoms for external sources of vitamin B 12. In addition to vitamin biosynthesis capabilities, bioinformatics analysis of A30 and SA1 genomes revealed additional predicted functions of ecological significance. For example, both isolates encode predicted bacteriophytochromes, or light-responsive photoreceptors (Table 2 ). Bacteriophytochromes sense light (usually red or far-red wavelengths), and depending on their N-terminal domain architecture, can mediate various physiological responses by controlling downstream gene expression or enzymatic function [ 66 ]. Although it is unknown how these photoreceptors regulate the cellular system for strains SA1 and A30, one prediction is that the bacteriophytochromes could provide a mechanism for these bacteria to coordinate their own physiology and metabolic capabilities with their phototrophic host. Strains SA1 and A30 also displayed some interesting differences in their functional predictions. For example, while both isolates encode motility mechanisms, SA1 is predicted to use swimming motility while A30 encodes genes suggesting gliding capabilities. Furthermore, they appear to encode different iron acquisition and storage strategies: SA1 encodes distinct predicted iron uptake systems, compared to A30, and SA1 encodes several ferritin-like proteins for possible iron storage (Table 2 ). Interestingly, SA1 encodes a homolog of PhyR (phylosphere-induced regulator), which was first described in another alphaproteobacterium, Methylobacterium extorquens AM1, where it regulates stress response genes and is required for epiphytic growth on its plant host [ 67 ]. Moreover, SA1 and A30 encode predicted biosynthetic genes for different small molecules shown to be used in cell-cell interactions and competition in other bacteria (Table 2 ). For example, SA1 is predicted to make a homoserine lactone (HSL) quorum sensing molecule for interbacterial signaling [ 68 ], while A30 encodes a putative quorum quenching lactonase that is predicted to degrade or “silence” HSL quorum sensing signaling [ 69 ]. Finally, SA1 and A30 both encode predicted biosynthetic gene clusters for putative antimicrobial molecules, including bacteriocins and beta-lactones, which could be used for interbacterial competition in situ, or as potential new therapeutics [ 70 ]. Taken together, these differences in predicted functions suggest that, although SA1 and A30 both are capable of using diatom-derived nutrients for growth (Fig. 4G ), they have evolved divergent strategies for motility, cell-cell interactions, and iron acquisition and storage, which limits phytoplankton growth in the SO. In Fig. 6 , we summarize our experimental and bioinformatics results to illustrate how the members of this tripartite model system, composed of a diatom and two bacterial isolates, interact with each other and their environment. Fig. 6 Model summarizing experimental and bioinformatics findings for bacterial-diatom interactions. Diagram shows a single P. subcurvata cell with associated Olleya sp. A30 (blue) and Sulfitobacter sp. SA1 (green). Abbreviations: a iron and other inorganic nutrients; b organic carbon, DMSP polypohosphate; c vitamins, detoxification (ex. catalase), iron, protection; d organic carbon, polyphosphate, iron; e HSL-mediated quorum sensing. Our discovery that a naturally co-occurring growth promoter and degrader physically associate with the diatom host has significant implications for the fate of diatom carbon. For SO diatoms like P. subcurvata , which require a biologically derived source of vitamins to thrive, their attached beneficial symbionts (like SA1) can act as extracellular organelles, traveling with the diatom throughout the water column. This work only assayed growth effects under constant light conditions, but given the presence of predicted light-sensing proteins for SA1, it is tempting to hypothesize that SA1 may shift its physiology in response to light quantity and quality, and such a shift could have effects on the host diatom cell. Moreover, if the diatom is no longer able to fix carbon and provide its epibiont with organic carbon, might the nature of its relationship change? Such a shift has been reported in other Roseobacter-phytoplankton interactions where at first the roseobacter promotes phytoplankton growth, only to kill and consume it once the phytoplankton cells begin to senesce [ 25 ]. Similar considerations should also be made for degraders, like A30, that can physically associate with the diatom and appear to reside within the cells. The ability to physically contact a host cell would allow degraders like A30 to use extracellular enzymes to degrade not only compounds in the phycosphere, but molecules found inside the cell. Indeed, in our cocultures with A30 and P. subcurvata , we did not see the usual intracellular structures (like chloroplasts, Fig. 5C ), and the RFU decreased over time with increasing A30 cell abundance (Fig. 4 ). These results suggest that A30 is able to infiltrate the diatom cell and consume and grow on intracellular content. In support of this finding, a recent study showed that Flavobacteriales (like A30) preferentially consumed 13 C-labeled diatom lysate, compared to labeled exudate [ 71 ], suggesting degraders like A30 may have evolved to fill a niche that utilizes intracellular diatom DOM, either by cell lysis via other organisms or mechanisms, or by directly invading cells. Such physical associations with diatoms have implications for possible interbacterial cooperation and competition within this microhabitat. At a concentration of 10 6 cells ml −1 in seawater, free-living bacteria are diffuse enough in the water column not to come into physical contact with one another [ 72 ]. However, if bacterial cells become associated with a particle, or a diatom cell, competition for space within the phycosphere is highly probable. Indeed, our microscopy images showed instances where bacterial cells were in physical contact on or inside the diatom cell (Fig. 5D, E ). For cases where many bacteria of the same strain may crowd together in a low-diffusion microhabitat within the phycosphere or diatom cell, such interactions could facilitate cell-cell communication via HSL signaling molecules like those encoded in SA1. By contrast, touching cells might compete for access to the environment, perhaps by using some of the predicted antimicrobial functions found in the SA1 and A30 genomes. If contact occurs between competing bacterial species, one can imagine that lethal weapons, such as bacteriocins predicted in SA1, could be used to defend the host niche. Indeed, the ability of roseobacters to kill competing bacterial cells has been reported in other isolates from free-living and host-associated habitats [ 73 – 79 ]. The use of genetically modified bacterial symbionts will facilitate tracking and quantifying interbacterial competition in the phycosphere and allow researchers to observe whether these cells are also communicating with each other via bacterial pheromones. Finally, we considered how this symbiotic association may be impacted by future climate conditions. Climate models predict an increase in sea surface temperature (SST) of 0.3–1.6 °C by 2100 for the Southern Ocean [ 80 ], however, the impact of rising temperatures on the SO microbial community is largely unknown. A recent study by Tonelli et al. used machine learning to model predicted effects of future SST on pelagic microbial communities in the SO [ 80 ]. The model predicted a decrease in microbial diversity, including a decrease in groups of biogeochemically important bacteria and archaea, which could have cascading effects on ocean chemistry and impact primary production, and thus higher trophic levels. Our isolates were able to grow well at higher temperatures (up to 10–12 °C was tested), suggesting an increase in SST alone is not inhibitory, but it is unknown how the cascading effects described above might impact these attached symbionts. Experiments using SO phytoplankton have shown that tolerance to increasing SST can be influenced by light, Fe, and CO 2 [ 81 , 82 ], thus it is likely that bacterial fitness at higher temperature would also impact phytoplankton growth and carbon flux. Future experiments using this co-culture model system could help determine how the mutualistic SA1 or parasitic A30 might impact P. subcurvata growth and survival under future climate conditions. In summary, we were able to successfully isolate diverse co-occurring bacterial strains that form physical attachments to an ecologically-relevant diatom genera in the Southern Ocean that is globally distributed. Our initial characterization of a growth-promoter ( Sulfitobacter sp. SA1) and a degrader ( Olleya sp. A30) establishes this interaction as a tractable and informative co-culture model system that can be used to further probe important questions relating to carbon export under current and future climate scenarios."
} | 5,758 |
38232281 | PMC10823229 | pmc | 8,044 | {
"abstract": "Significance Addressing the challenges of global sustainability and alleviating energy shortages requires pioneer methods for efficient methane production. Methanogenic archaea, central to this endeavor, are constrained by the inherent energy conservation and strict substrate specificity. Our light-driven biohybrids, synergizing engineered methanogenic archaea with photocatalysts, not only overcome substrate limitation but also markedly enhance energy conversion and glucose-to-methane conversation. This biohybrid provides a versatile platform to connect editable archaeal metabolism with photocatalytic innovation, setting a standard for sustainable energy conversion and value-added chemical production.",
"discussion": "Discussion We present a pioneering light-driven biohybrid system, integrating CdS nanoparticle with rationally constructed methanogenic archaeon, to directly facilitate exogenous glucose for methanogenesis ( Fig. 5 D , and SI Appendix , Tables S2 and S3 ). Furthermore, the photo-excited electrons of this biohybrid system promote the metabolism of pyruvate to AcCoA and inhibits the flow of AcCoA to TCA cycle, allowing more portion of glucose-derived carbon to the methanogenesis. This system amplifies Na + and H + ion flux across the membrane, enhancing ATP synthesis for glucose phosphorylation. Theoretically, M. a 3fk metabolizes 1 mol of glucose into 2 mol of pyruvate through glycolysis, which subsequently yields 2 mol of AcCoA via decarboxylation ( SI Appendix , Fig. S12 ). This precursor then metabolized to 2 mol of CH 4 through aceticlastic methanogenesis ( SI Appendix , Fig. S12 ). With our light-driven biohybrid, we achieved a conversion of 1 mol of glucose from 0.7 mol of CH 4 in M. a 3fk to 1.3 mol in 3FK –CdS ( SI Appendix , Table S4 ). Although we have revealed the potential pathways for the internalization of the photo-excited electrons in M. acetivorans , there is a variety of mechanisms existing for extracellular electron transport in methanogenic archaea. For example, Song et al. recently showed the potential role of cell surface pyrroloquinoline quinone (PQQ)-binding proteins in facilitating electron transfer across the membrane of M. acetivorans ( 30 ). These proteins may also be viable candidates for accepting extracellular photo-excited electrons. Future research could delve deeper into elucidating the precise mechanisms governing the transfer of photo-excited electrons in M. acetivorans . In the engineered bioreactors, methanogenic archaea are restricted to the simple compounds (single and two carbon substrates) for growth and methanogenesis ( 31 , 32 ), which require microbial consortia to decompose complex organic substrates like glucose ( 33 – 36 ). However, the interdependency is often broken by a number of factors in the environment, potentially compromising stability. Our biohybrid system can simplify the microbial food chain and improve the stability of bioreactors. Broadly, the integration of tailored nanomaterials with microbial engineering gives a promising avenue for manufacturing high-valued chemicals efficiently and economically."
} | 781 |
30056004 | null | s2 | 8,046 | {
"abstract": "Signal transmission among cells enables long-range coordination in biological systems. However, the scarcity of quantitative measurements hinders the development of theories that relate signal propagation to cellular heterogeneity and spatial organization. We address this problem in a bacterial community that employs electrochemical cell-to-cell communication. We developed a model based on percolation theory, which describes how signals propagate through a heterogeneous medium. Our model predicts that signal transmission becomes possible when the community is organized near a critical phase transition between a disconnected and a fully connected conduit of signaling cells. By measuring population-level signal transmission with single-cell resolution in wild-type and genetically modified communities, we confirm that the spatial distribution of signaling cells is organized at the predicted phase transition. Our findings suggest that at this critical point, the population-level benefit of signal transmission outweighs the single-cell level cost. The bacterial community thus appears to be organized according to a theoretically predicted spatial heterogeneity that promotes efficient signal transmission."
} | 304 |
39233720 | PMC11371424 | pmc | 8,047 | {
"abstract": "Stigmergy, the indirect communication between agents of a swarm through dynamic environmental modifications, is a fundamental self-organization mechanism of animal swarms. Engineers have drawn inspiration from stigmergy to establish strategies for the coordination of swarms of robots and of mixed societies of robots and animals. Currently, all models of stigmergy are algorithmic, in the form of behavioural rules implemented at an individual level. A critical challenge for the understanding of stigmergic behaviour and translation of stigmergy to engineering is the lack of a holistic approach to determine which modifications of the environment are necessary to achieve desired behaviours for the swarm. Here, we propose a mathematical framework that rigorously describes the relationship between environmental modifications and swarm behaviour. Building on recent strides in continuification techniques, we model the swarm and environmental modifications as continua. This approach allows us to design the environmental modifications required for the swarm to behave as desired. Through analytical derivations and numerical simulations of one- and two-dimensional examples, we show that our framework yields the distribution of traces required to achieve a desired formation. Such an approach provides an adaptable framework for different implementation platforms, from robotic swarms to mixed societies of robots and animals.",
"introduction": "1 . \n Introduction Stigmergy—defined as a ‘mechanism of indirect coordination in which the trace left by an action in a medium stimulates subsequent actions’ [ 1 ]—is a fundamental means of self-organization in complex systems [ 2 ]. The concept of stigmergy originated from the study of coordination in groups of animals [ 3 ]. For example, ants release pheromones in the environment [ 4 ] to guide other ants back to the nest once they find food [ 5 ], or to cooperatively transport large food items [ 6 ]. Likewise, pumas and other large Felidae leave traces in the environment to mark territory so that other conspecifics would avoid the area [ 7 ]. In animal colonies that build structures [ 8 , 9 ], such as wasps [ 10 ] and termites [ 11 , 12 ], stigmergy allows the incredible coordination of thousands of individuals to build intricate nests, without any pre-planning and central coordination. With the advent of robotic systems, engineers have taken inspiration from stigmergy in natural swarms to build self-organizing groups of robots that coordinate to achieve a desired goal [ 13 – 15 ]. In stigmergy, robots in a swarm not only coordinate to sense the environment [ 16 , 17 ], but they actively modify it to communicate with each other. Through stigmergy, robotic swarms can gather objects [ 18 ], sort them [ 15 ], navigate unknown environments [ 19 ], and search and track a moving target [ 20 ]. Stigmergy is particularly promising for collective construction, as the structure that is being built can be utilized as the stigmergic signal itself [ 21 , 22 ]. In this vein, extensions of stigmergic approaches have been proposed to achieve precise and accurate collective construction [ 23 , 24 ]. Stigmergy is an important coordination strategy not only in biological and robotic systems but also in so-called ‘mixed societies’ that integrate biological and robotic individuals [ 25 , 26 ]. Therein, robots are used to create new collective responses or to elicit a desired behaviour from the animal group [ 27 ]. In addition to direct social interactions between animals and robots, stigmergic stimuli released by robots have been often used to achieve the desired swarm behaviour, for example through light signals [ 28 ] or pheromone release [ 29 ] by robots. A fundamental challenge for biologists is to reconstruct how environmental modifications implemented at an individual level, without a central coordination, trigger a complex behaviour of the swarm, such as the construction of a nest or food gathering. The literature relies on agent-based modelling grounded in individual behavioural rules [ 13 – 15 ], which do not allow a holistic analysis of the swarm. Currently, no stigmergic model allows the study of the overall distribution of environmental modifications that enable these complex behaviours. Similarly, engineers are faced with the design problem of how to control robotic agents toward achieving a desired behaviour for the swarm, be it robotic or mixed. Such a challenge requires the development of a mathematically tractable and interpretable framework for stigmergy that could complement existing algorithmic implementations, which rely on a sequence of discrete behavioural rules implemented at the individual level. Here, we put forward a control-oriented mathematical backdrop to holistically describe environmental modifications in animal swarms and engineer stigmergic interactions in robotic and mixed swarms, where units of the swarm interact with each other and with dynamic modifications of the environment that we identify as ‘traces’. Our mathematical framework is based on recent advancements in the field of control of large multi-agent systems, which relies on a ‘continuification’ of the equations of motion of the swarm [ 30 , 31 ] (see figure 1 ). In this vein, rather than modelling and controlling individual motions [ 32 ], we model the swarm as a continuous fluid and describe the spatio-temporal evolution of its density, similar to thermodynamic approaches for large-scale systems [ 33 ] and former robot density control algorithms [ 34 – 38 ]. Our work differs from previous studies on continuification-based control of large swarms [ 30 , 31 ] as we do not apply a control action to each swarm unit. In animal swarms and mixed societies, it is not possible to directly control biological units, and even in robotic swarms controlling each unit would require a centralized approach or, at least, some form of connectivity in the swarm [ 39 ]. Based on these groundings, we focus on the realistic case where the control engineer can only design dynamic modifications of the environment, such that no centralization or communication between the units is needed. Figure 1 . \n Schematics of the control problem and proposed framework for our mathematical model of stigmergy. The control problem that we seek to address is achieving a desired configuration of a large swarm in terms of position of its discrete units. Such a desired configuration is continuified (1) to provide the desired density of the swarm. The density of the traces is computed (2) based on the desired density of the swarm, and is then discretized (3) to allow actual deployment of the traces. The final, desired configuration of the swarm arises from the interaction between units of the swarm and the traces left (4). Schematics of the control problem and proposed framework for our mathematical model of stigmergy. While our work shares the same backdrop of continuified swarms as that in Maffettone et al . [ 30 ], it tackles the control problem through a totally different perspective. Our control action is not directly applied to the swarm agents; rather, it is mediated by the deposition of traces in the environment. Such a continuified view of stigmergy is an original contribution of this paper, which allows us for the first time to explicitly compute the trace distribution necessary to achieve a desired swarm configuration. In this vein, we offer closed-form solutions of the control input in the form of density of traces. We examine a prototypical example of a task that can be achieved through stigmergy: shape formation [ 21 , 40 ]. We seek to compute the distribution of traces that make the swarm achieve a desired formation, that is, a prescribed density profile. To this end, we propose a general procedure to compute the density of traces that allows us to retrieve the prescribed density of the swarm. Once the density of traces is known, it is discretized to allow for deployment in a real environment, in a discrete form. We do not focus on implementation details of how such density profile of traces can be generated, as we concentrate on the mathematical modelling of the overarching stigmergic control strategy, generalizable to a variety of practical implementations. While one could describe the dynamics of deposition of the traces, such a process would be heavily context-dependent (for example, the dynamics of ants’ pheromone release [ 13 ] is different from that of robotic collective additive manufacturing (AM) [ 23 ]), thus hindering the generality of our theory. We demonstrate the potential of our approach through a series of one- (1D) and two-dimensional (2D) case studies. In the 1D benchmarks, we show that our approach allows for the swarm to achieve a stationary formation and generate travelling waves [ 41 ]. The 2D simulations validate our approach in a more realistic scenario. We select a historical, fascinating example, by replicating the complex, non-uniform motion of the robotic lion of Leonardo da Vinci along a wavy circle [ 42 ] with our swarm.",
"discussion": "4 . \n Discussion and conclusions Complex systems composed of many units often display surprising self-organization phenomena [ 53 ]. Self-organization is inevitably associated with information transfer between the units of the system, which occurs through direct social interactions or indirect cues mediated by the environment [ 54 ]. Stigmergy encapsulates the ability of the units of a system of transferring information among them by modifying the surrounding environment [ 1 ]. This concept has found a broad range of application in animal [ 2 ] and robotic [ 18 ] swarms, mixed societies of animals and robots [ 26 ], and even human social systems [ 55 ]. A particularly challenging endeavour in biology is the analysis of how stigmergic signals left in the environment lead to self-organization and execution of complex tasks, even in the absence of central coordination. Such a challenge persists in engineering design of stigmergic modifications of the environment in order for the swarm to behave as desired. This problem requires the formulation of mathematically tractable and interpretable models to be used in the analysis of swarms and the design of control systems. However, literature on stigmergy typically focuses on agent-based models, where each unit of the swarm follows a set of behavioural rules. These models are difficult to use for holistic analyses of environmental modifications and control purposes. Here, we propose a new mathematical framework to study stigmergy in swarms. Through this framework, we lay out how traces should be left in the environment to enable the coordination of a swarm, provided a mathematical model for the motion of the swarm is available. Such a framework is rooted in recent ideas for the control of large multi-agent systems [ 30 , 31 ], which draw on the analogy between robots and particles in a fluid. While for small groups of particles we can describe the motion of each individual unit, when considering large systems a continuum description is preferable. Thus, we continuify the problem by modelling the swarm as a fluid, design the control at a continuum level in terms of density of traces, and discretize this distribution to deploy them in the environment. This approach transforms the control problem on a large number of coupled ordinary differential equations to that on a single partial differential equation, which becomes analytically tractable. One of the potential applications of the proposed setting is collective construction in robotic swarms through collective AM, where buildings and infrastructure are built through layer-by-layer deposition [ 56 – 59 ] by a team of robots [ 60 ]. This paradigm has been inspired by other efforts in collective construction with teams of robots using pre-made parts [ 61 , 62 ], amorphous deposition [ 63 ], or the robots themselves [ 64 ]. While initial efforts focused on ground-based robots [ 65 – 67 ], the recent breakthrough in Zhang et al. [ 68 ] demonstrated the possibility of aerial AM for large-scale buildings and infrastructure, going far beyond previous efforts that only focused on structure assembly through drones [ 69 ]. Robots in construction teams ought to reach a specific location and coordinate with each other. Our work provides a pathway to achieve these goals, making a first step toward collective AM algorithms. Within the context of collective AM, traces may be left in the environment by the swarm or by one or more exogenous robots, not directly involved in the construction. While stigmergic cues could be provided by the built structure itself [ 22 , 23 ], it is tenable that in many applications the trace deposition process should be independent from the printing. A potential implementation of the trace deposition entails the use of a separate nozzle, utilizing a coloured dissoluble material that can be identified by other robots. Traces can be left as signs on printed structures or as thin marks on the ground and removed after construction, similar to supporting material used in desktop 3D printers [ 70 ]. Beyond collective AM, the traces needed for our algorithm may assume different forms. For example, they may represent actual fixed, physical objects, an additional swarm of mobile robots, spatially extended continuous robots that can actively deform or other environmental modifications that affect the swarm (such as changes in background lighting in light-foraging swarms [ 71 ]). Regardless of the application, we assume that units in the swarm are not able to distinguish between other units and traces. Such a possibility is in practice verified in large swarms where individual units have limited computing power and may only perform simple operations to avoid collisions with surrounding entities, be they other units or traces. When a unit can discern traces from other units, we have an additional degree of freedom, as we can modify the type of interaction units have with traces. For example, should units be able to distinguish different types of traces, negative densities of traces may be implemented in practice by using traces encoding interactions via an attraction potential. Interestingly, we find that the distribution of traces has several degrees of indeterminacy. Such indeterminacy is not a drawback, but rather an advantage of the method, as it provides additional degrees of freedom for the control and swarm designer. For example, if traces represent fixed, physical objects that cannot be removed or relocated after they have been released, their density can only increase over time at each point of the domain: the indeterminacy of the distribution of traces allows to satisfy this condition. We demonstrate the validity of our framework in a variety of simulations in 1D and 2D. In 1D, we show that the swarm can achieve a stationary formation, and that we can make this stationary formation rigidly translate similar to a travelling wave in a non-dispersive medium. We validate our coordination strategy with even more complex scenarios, as we studied a concurrent modification of the formation during the translation of the wave, simulating a travelling wave in a dispersive medium, where different harmonics of the waves travel at a different speed, thus modifying the waveform over time. Analogous simulations at a discrete level demonstrated the validity and practical viability of our approach, even in very large-scale swarms with thousands of units. In 2D, we selected a historical example to show the potential of our approach. Specifically, we replicated the behaviour of Leonardo da Vinci’s lion-shaped automaton, which was designed to pay homage to the King of France through its complex movements. We showed that our approach allows the swarm to perform composite, time-modulated tasks, tracking an uneven trajectory, stopping at a precise location, modifying the formation in time, and resuming its motion along the trajectory. All these behaviours can be easily achieved through a stigmergic approach. Our approach does not come without limitations. In particular, we acknowledge that further work is needed to support real-world implementation. The lack of an explicit model for the trace deposition process benefits the generality of the theory, but it limits a prompt translation of the proposed approach to practice. Further, robustness of the approach to different forms of disturbances should be tested, and additional research is required for deployment in collective AM. Further, we acknowledge that the proposed control strategy is not suitable for all collective tasks, especially for small teams in which coordination and localization within an absolute frame are more easily achieved. Nevertheless, we believe that the proposed mathematical framework offers a powerful and adaptable tool to design environmental modifications for swarm coordination, leaving designers the versatility to implement them in different ways."
} | 4,256 |
40232537 | PMC12000269 | pmc | 8,048 | {
"abstract": "The normal development of mycorrhizal symbiosis is a dynamic process, requiring elaborately regulated interactions between plant roots and compatible fungi, mandatory for both partners´ survival. In the present study, we further elucidated the mycorrhizal development of the desert truffles Terfezia claveryi with the host plant Helianthemum almeriense as an ectendomycorrhizal symbiosis model under greenhouse conditions. To investigate this, we evaluated the morphology of mycorrhizal colonization, concomitantly with the dynamic expression of selected marker genes (6 fungal and 11 plant genes) measured every week until mycorrhiza maturation (three months). We were able to determine 3 main stages in the mycorrhization process, 1) pre-symbiosis stage where mycelium is growing in the soil with no direct interaction with roots, 2) early symbiosis stage when the fungus spreads along the roots intercellularly and plant-fungal signaling is proceeding, and 3) late symbiosis stage where the fungus consolidates and matures with intracellular hyphal colonization; this is characterized by the regulation of cell-wall remodeling processes. Supplementary Information The online version contains supplementary material available at 10.1007/s00572-025-01205-8.",
"conclusion": "Conclusions In this work we report the ectendomycorrhizal continuum development in T. claveryi x H. almeriense in pot conditions, revealing three well defined stages. Each stage is characterized by different morphological structures, with no fungal colonization in presymbiosis stage, exclusively intercellular colonization in early stages of the interaction and concomitant inter- and intracellular colonization during the late stage of symbiosis. The expression of certain molecular markers during these stages helps us better understand the mechanisms of EEM symbiosis development. In the future, more refined molecular tools for the H. almeriense x T. claveryi system together with more in-depth analyses are needed to clarify the function of the pinpointed marker genes in the establishment of EEM symbiosis.",
"introduction": "Introduction Desert truffles are edible hypogeous fruit bodies produced by certain Ascomycete fungi inhabiting arid and semiarid areas. They establish mycorrhizal symbiosis with roots of annual and perennial shrubs belonging to the Cistaceae family (Gutiérrez et al. 2003 ; Kovács and Trappe 2014 ; Roth-Bejerano et al. 2014 ). They are one of the few edible mycorrhizal fungi that have been domesticated (Guerin-Laguette 2021 ), transforming them in an important resource to enhance the use of arid lands and fight the adverse conditions related to climate change and desertification in the Mediterranean basin and the Middle East (Ferreira et al. 2023 ). Among them, Terfezia spp. are among the most prized species to be cultivated, due to their high nutritional value, delicious taste, anticancer and immunomodulatory activity (Bokhary and Parvez 1993 ; Al Obaydi et al. 2020 ; Morte et al. 2021 ; Veeraraghavan et al. 2021 ). Desert truffle cultivation faces different agroclimatic challenges in the field (Andrino et al. 2019 ), but the success of human-managed desert truffle fields first requires nursery plantlet production with enough mycorrhizal development (Morte et al. 2010 ). The whole process of producing mycorrhizal plantlets is made in three stages (Navarro-Ródenas et al. 2016 ) and may last from four to eight months and a half, depending on the techniques used (Morte et al. 2017 ). Mature mycorrhiza is normally observed after eight to twelve weeks, when it reaches a steady state (Morte et al. 2017 ). Helianthemum almeriense x Terfezia claveryi mycorrhizal plants are the most used mycorrhizal system for desert truffle cultivation in the Mediterranean area (Morte et al. 2021 ). They establish ectendomycorrhizal (EEM) symbiosis, which is characterized by the presence of both intercellular hyphae establishing a Hartig Net (HN), similar to the structures observed in ectomycorrhizal fungi (ECM), and intracellular hyphae penetrating the cortex cells and forming a symbiotic surface between the fungal cell wall and the intact host cell plasmalemma (Gutiérrez et al. 2003 ). They can also present a thin and disorganized fungal mantle surrounding the colonized roots (Dexheimer et al. 1985 ; Morte et al. 1994 ; Yu et al. 2001 ; Gutiérrez et al. 2003 ; Roth-Bejerano et al. 2014 ; Louro et al. 2021 ). Although different morphologies of mycorrhizal root tips have been described for T. claveryi (Gutiérrez et al. 2003 ), its colonization is not limited to root tips but can be found throughout the whole system of fine roots of the host (Navarro-Ródenas et al. 2012a , 2013 ). In this sense, the EEM symbiosis of T. claveryi has previously been described as a continuum , a dynamic structure that changes depending on mineral nutrition, water availability or hormonal signal (Gutiérrez et al. 2003 ; Zaretsky et al. 2006b ; Navarro-Ródenas et al. 2012a , 2013 ; Roth-Bejerano et al. 2014 ). No morphological time lapse of the initial steps of H. almeriense x T. claveryi EEM formation has been explored yet and how the mentioned EEM continuum switches during the mycorrhizal development in nursery conditions is unknown. In other mycorrhiza systems, such as ECM, the normal mycorrhiza development both before (pre-symbiotic) and after (symbiotic) physical contact is associated with an intense molecular crosstalk to determine the outcome of the symbiosis (Marqués-Gálvez et al. 2022 ). Main actors of this interkingdom crosstalk include fungal effectors (Plett et al. 2011 , 2020 ; Kloppholz et al. 2011 ; Kang et al. 2020 ), both fungal and plant carbohydrate active enzymes (CAZymes) in charge of the plant cell wall remodeling (Veneault-Fourrey et al. 2014 ) and other genes related to response to biotic stimulus and signaling and hormone regulation (Labbé et al. 2019 ; Basso et al. 2020 ). Transporters are known to play a role in mycorrhiza functioning, as it is the case of the mycorrhizal inducible phosphate transporter PT4 (Harrison et al. 2002 ) However, other transporters, such as aquaporins (AQP), could also be involved in the first steps of development of the mycorrhiza. For instance, Laccaria bicolor AQP1 plays a key role for the establishment of ECM symbiosis, since knocked-down mutants are impaired in HN formation (Navarro-Ródenas et al. 2015 ). Just as the morphological development of T. claveryi EEM is poorly understood, so too are the molecular mechanisms associated to this process. During the preinfection stage between Terfezia boudieri and Helianthemum sessiliflorum , high concentrations of indole- 3-acetic acid (IAA) secreted by the fungus induced lateral root formation (Sitrit et al. 2014 ; Turgeman et al. 2016 ). In the T. boudieri x Cistus incanus symbiosis, certain genes associated with several signal transduction pathways, could be linked to the regulation of hyphal proliferation and adaptive modifications (Zaretsky et al. 2006a ). After contact, during root colonization between T. claveryi and H. almeriense , a correlation between the fungal aquaporin TcAQP1 expression and the degree of mycorrhization has been observed (Navarro-Ródenas et al. 2012b ). A recent fungal and plant transcriptome analysis of H. almeriense x T. claveryi has enabled new information about putative mechanisms implicated in the development of the desert truffle EEM symbiosis (Marqués-Gálvez et al. 2021 ). Most of the molecular markers of mycorrhizal molecular crosstalk mentioned above, including fungal putative effectors (also known as mycorrhiza-induced small secreted proteins or MiSSPs), plant and fungal CAZymes, the fungal aquaporin TcAQP1, and other genes related to pathogenesis response, signaling and regulation of hormonal pathways, were documented, suggesting commonalities with better studied ECM systems. In the present study, we aim to further describe the morphological development of desert truffle EEM. We hypothesized that, as with other mycorrhizal interactions, H. almeriense x T. claveryi EEM presents well differentiated morphological stages during its development. To explore this, H. almeriense plants were inoculated with T. claveryi in greenhouse settings. We evaluated the morphology of mycorrhizal colonization together with the expression levels of selected genes, including plant and fungal aquaporins and genes previously identified to be related with the mycorrhiza development and highly differentially expressed in previous RNA-seq analysis (Marqués-Gálvez et al. 2021 ). To provide a temporal scale to the dynamic EEM developmental process, we followed these morphological and molecular traits every week until mycorrhiza maturation and discussed their biological implications.",
"discussion": "Discussion Over the experimental procedure period, the development of the ectendomycorrhizal symbiosis between H. almeriense and T. claveryi can be divided into three stages in base of the structure and colonization degree: the pre-symbiotic stage, early symbiosis stage and late symbiosis stage, each of them with their own traits. The pre-symbiotic stage of H. almeriense x T. claveryi lasts three weeks in pot conditions We did not detect presence of the fungus via microscopy, nor by RT-qPCR in the plant until the fourth week, suggesting that the pre-symbiotic stage of H. almeriense x T. claveryi EEM lasted around three weeks. In this period, it is plausible that T. claveryi was establishing in the rhizospheric soil interacting with the roots of H. almeriense . The lack of data from T. claveryi gene expression in soil prevents us to evaluate the expression of any of the selected fungal genes as molecular markers of this stage. However, mycorrhizal development is a dynamic process, and not all the hyphae enters direct plant-fungal contact with the roots simultaneously. In weeks four to eight, between 10 and 40% of hyphae observed were still extraradical and, thus, this data could also be used as a proxy of the genetic regulation before plant-fungal direct contact. According to this, the progressive increase of TcNiR , TcSSP and TcPIN1 levels from week four to eight may suggest a role also in the pre-symbiotic stage. Among these three genes, the putative role of TcPIN1 remains of particular interest, since auxin of fungal origin (indole- 3-acetic acid or IAA) is one of the most important phytohormones that remodels root architecture and facilitate fungal accommodation (Felten et al. 2009 ; Sukumar et al. 2013 ; Fusconi 2014 ). Our results regarding TcPIN1 levels are in accordance with previous reports showing that Terfezia spp. produce IAA, and this plays a role in the dynamics of the EEM continuum (Zaretsky et al. 2006a ; Sitrit et al. 2014 ; Turgeman et al. 2016 ). From the plant side, most of the gene expressions remain stable during pre-symbiotic stage, except for AOX1 . It has been reported that non-mycorrhizal plants increase the production of AOX under stressful conditions to eliminate reactive oxygen species (ROS) (Vanlerberghe 2013 ; Li et al. 2013 ). Although the role of AOX has not been fully elucidated yet, evidence suggests that AOX function in metabolic and signaling homeostasis is particularly important during stress. The roots of H. almeriense exhibit high levels of AOX1 just during the first week only, but its expression rapidly declines. This decrease in AOX1 expression could be comparable to the AM-suppression of AOX activity previously reported (Liu et al. 2015 ; Del-Saz et al. 2018 ), although its biological insights remain unresolved. These results could also be coupled with the progressive resolution of stress conditions originated by transplant or substrate manipulation during fungal inoculation. In either case, more dedicated experiments with proper controls would need to be performed to unveil the putative role of H. almeriense AOX during pre-symbiotic stage. The early symbiotic stage is characterized by intercellular colonization and the upregulation of several marker fungal genes of colonization At this stage, mycorrhization can be detected both at the molecular and microscopic levels and takes four weeks. During this period the percentage of colonized roots increases linearly from 20 to 70%. However, the ratio of fungal biomass over roots biomass remains constant. During the early symbiotic phase, all root colonization occurs intercellularly, and the fungus appears to prioritize spreading along the whole system of fine roots rather than establishing itself. Even as the percentage of colonized roots increases, fungal biomass tends to become diluted within them as mycorrhization development progresses, we find more roots with intercellular colonization and less extraradical mycelium. Regarding the expression of molecular markers TcPIN1 , TcNiR , TcSSP and TcAQP1 seem to play an important role at this stage, according to their expression profiles. The possible implications of TcPIN1 have been discussed in the previous phase, while those of TcAQP1 are discussed in Sect.\" The role of AQPs in mycorrhizal symbiosis \". TcNiR shows the most stable upregulated pattern from all the selected genes, making it probably the best candidate to be used as mycorrhization marker, regardless of its developmental stage. TcSSP expression levels are also high during this phase. Fungal effectors are normally orphan genes, with low-sequence homology (Kohler et al. 2015 ), preventing us from inferring its function by homology. However, its expression pattern is similar to those of previously characterized fungal effectors in other ECM species, that facilitate the fungal colonization by interfering with the plant immune system, such as LbMiSSP7 (Plett et al. 2014 ). The expression pattern of defense-related HaTLP1 may support this same role for TcSSP , since it shows a marked decline at early symbiosis stage, coinciding with the start of colonization and the upregulation of TcSSP. However, this was not the case for another defense-related gene HaTLP2 . Recent research has shown that LbMiSSP7 is capable of interfering with the activity of poplar ( Populus tremula × alba) defense master regulator MYC2 and thus maintain the repression over specific pathways of plant jasmonate-related defense, but not for others (Marqués-Gálvez et al. 2024 ). This could explain the different pattern of expression between HaTLP1 and HaTPL2, but more in-depth studies are needed to evaluate this. Intracellular colonization is the hallmark of the late symbiotic stage and it is accompanied by the expression of fungal and plants cell-wall remodelling genes At this stage, there is an increase in the percentage of mycorrhization (reaching its maximum) and changes in fungal biomass and in mycorrhiza morphology, since fine roots with intracellular colonization were firstly observed and increased progressively in percentage. The concomitant increase in intracellular colonization and fungal biomass suggests that intracellular colonization is denser, containing more biomass per gram of root than intercellular colonization. Thus, mycorrhization moves from a phase of expansion of new roots to a phase of settlement and maturation within the root system. Due to the method used to analyze the morphology of the roots, we could not determine if the transition from inter to intracellular colonization follows a direction from tip to base, as suggested for Pinus spp. x W. mikolae EEM (Yu et al. 2001 ). Although our results suggest that this transition is homogenous within the whole root system, in the future, it would be interesting to determine whether the presence of intracellular colonization follows a local gradient or if it is correlated to the maturity degree of the host root. The presence of the first intracellular hyphae coincided with an interesting pattern of expression of both fungal and plant cell wall remodeling genes TcPME1 , TcEXPL1 and HaPE1. Their expression profiles suggest their involvement in the transition from early to mature mycorrhiza, although in different ways. Previous reports have proposed a role for pectin methyl esterases in the growth of hyphae within the roots (Chowdhury et al. 2022 ), which is in line with the expression pattern observed for TcPME1 . The progressive upregulation of TcPME1 could be related both to the increase of the degree of colonization and to the apparition of intracellular colonization. Both TcEXPL1 and HaPE1 present a prominent peak of expression at week 7, during the transition phase from fully ecto to ectendomycorrhiza. Expansins are proteins involved in cell wall loosening and increasing cell wall extensibility (Kerff et al. 2008 ; Georgelis et al. 2014 ), and for example, in tomato roots, they are considered a prerequisite for the accommodation of the fungus in the plant (Dermatsev et al. 2010 ). Pectin esterases play a fundamental role in remodeling plant cell walls and have also been shown to play a role in plant defense (Micheli 2001 ). As intracellular colonization appears, both genes could serve as markers of the ecto to endo transition, either because of their role in plant cell wall remodeling, or as a defense response to the more intimate intracellular colonization. The further characterization of these genes could shed light to the molecular mechanisms related to the plant cell wall remodeling activities needed to accommodate fungi intracellularly. During the symbiosis between T. boudieri and C. incanus roots, an endogenous application of a synthetic auxin produced a change from intercellular to intracellular colonization (Zaretsky et al. 2006b ). In our study, the auxin efflux carrier TcPIN1 , which reached its maximum peak during intracellular colonization, supporting the role of auxin as a determinant of the ecto to endo switch of Terfezia spp. EEM. While its expression drops sharply, high auxin levels have been shown to lead to reduced root cell elongation, and this attenuation in taproot growth may contribute to the equalization of growth rates between the fungus and the host root, thereby enhancing the likelihood of successful mycelial-root interaction (Campanoni and Nick 2005 ; Turgeman et al. 2016 ). The role of AQPs in mycorrhizal symbiosis We also observed important transcription profiles for both fungal and plant aquaporins. TcAQP1 is the sole gene encoding for AQP in T. claveryi genome (Marqués-Gálvez et al. 2021 ) and, thus, we could hypothesize that this gene plays multipurpose roles depending on the mycorrhization stage in which T. claveryi is found. In fact, the double expression peak observed for TcAQP1 in early and late symbiosis stage supports this contention. This AQP is known to facilitate de passage of both water and CO 2 (Navarro-Ródenas et al. 2012b ) which can act as a signaling molecule in various fungal processes, including growth, differentiation, ascocarps development and mycorrhiza development (Bahn and Mühlschlegel 2006 ; Navarro-Ródenas et al. 2015 ; Xu et al. 2016 ). In L. bicolor , the upregulation of AQPS is pivotal for the transition from pre-symbiotic phase to functional symbiosis (Navarro-Ródenas et al. 2015 ). Whereas in the early phase it could be favoring the transport of signaling molecules, as it has been suggested for its homologue LbAQP1 (Navarro-Ródenas et al. 2015 ), at the end of this stage, when the mycorrhiza is already mature and the molecular signaling is less intense, functions related to water transport are expected (Navarro-Ródenas et al. 2012b ). Regarding the expression profile of plant AQPs, we found a general downregulation of 6 different genes throughout the course of the mycorrhization development. This can be related to molecular reprogramming in response to the presence of the fungus. We can hypothesize that one of the reasons of this phenomenon is that younger and non-mycorrhizal plants are more dependent on their own water transport systems, while more adult mycorrhizal plants may rely more on the water-acquisition benefits provided by T. claveryi colonization (Navarro-Ródenas et al. 2013 ). More dedicated analyses evaluating the whole transcriptional landscape of plant AQPs will be needed to determine which H. almeriense AQP isoforms play a role during mycorrhizal development. Conclusions In this work we report the ectendomycorrhizal continuum development in T. claveryi x H. almeriense in pot conditions, revealing three well defined stages. Each stage is characterized by different morphological structures, with no fungal colonization in presymbiosis stage, exclusively intercellular colonization in early stages of the interaction and concomitant inter- and intracellular colonization during the late stage of symbiosis. The expression of certain molecular markers during these stages helps us better understand the mechanisms of EEM symbiosis development. In the future, more refined molecular tools for the H. almeriense x T. claveryi system together with more in-depth analyses are needed to clarify the function of the pinpointed marker genes in the establishment of EEM symbiosis."
} | 5,321 |
25650278 | PMC4314589 | pmc | 8,050 | {
"abstract": "During the past several decades, Escherichia coli has been a treasure chest for molecular biology. The molecular mechanisms of many fundamental cellular processes have been discovered through research on this bacterium. Although much basic research now focuses on more complex model organisms, E. coli still remains important in metabolic engineering and synthetic biology. Despite its long history as a subject of molecular investigation, more than one-third of the E. coli genome has no pathway annotation supported by either experimental evidence or manual curation. Recently, a network-assisted genetics approach to the efficient identification of novel gene functions has increased in popularity. To accelerate the speed of pathway annotation for the remaining uncharacterized part of the E. coli genome, we have constructed a database of cofunctional gene network with near-complete genome coverage of the organism, dubbed EcoliNet. We find that EcoliNet is highly predictive for diverse bacterial phenotypes, including antibiotic response, indicating that it will be useful in prioritizing novel candidate genes for a wide spectrum of bacterial phenotypes. We have implemented a web server where biologists can easily run network algorithms over EcoliNet to predict novel genes involved in a pathway or novel functions for a gene. All integrated cofunctional associations can be downloaded, enabling orthology-based reconstruction of gene networks for other bacterial species as well. Database URL : http://www.inetbio.org/ecolinet",
"introduction": "Introduction Escherichia coli is perhaps the most intensively studied species of bacteria, due to its utility in both exploring the molecular mechanisms underlying fundamental biological processes and manufacturing useful metabolites for the biomedical industry. Numerous molecular genetics techniques have been developed in E. coli over the past several decades, making it the standard bacterial species in which to study genetics and the molecular mechanisms underlying cellular phenotypes. This attention has led to the elucidation of many conserved metabolic pathways in E. coli , resulting in its use as a metabolic engineering platform. Despite its importance in science and engineering, a significant portion of the E. coli genome remains uncharacterized. For example, as of September 2014, the Gene Ontology database ( 1 ) had no biological process annotations supported by either experimental evidence or manual curation for ∼2000 protein coding genes. A holistic E. coli pathway map could significantly improve our ability to engineer metabolic phenotypes by providing a genetic circuit design that accounts for the entire system. Although traditional forward and reverse genetic approaches have played major roles in gene-to-phenotype association mapping in E. coli , a more efficient and sensitive genetics approach would facilitate characterization of the part of the genome whose function is not yet known. Network-assisted predictive genetics is an example of such an approach whose popularity is growing ( 2 , 3 ). Here, we present a functional gene network for E. coli , dubbed EcoliNet, which includes 95 520 cofunctional associations and covers ∼99% of the genome. EcoliNet has high predictive power for a wide variety of bacterial phenotypes, including response to various stresses and drugs. To make EcoliNet freely available as a hypothesis-generating tool, we have implemented a web server where users can conduct network algorithms, prioritizing novel genes for a pathway or novel functions for an E. coli gene. The EcoliNet server ( http://www.inetbio.org/ecolinet ) provides not only public prediction tools but also a database of cofunctional associations between E. coli genes, derived from diverse biological data. Moreover, cofunctional gene networks for other bacterial species can be constructed via orthology-based transfer of information from EcoliNet.",
"discussion": "Discussion Although E. coli is one of the most intensively studied and utilized model organisms, a large portion of its genome remained uncharacterized. Computational prediction models will facilitate identification of novel gene functions. For instance, a recently initiated COMBREX project, the goal of which is to improve our understanding of microbial protein function by bridging computational and experimental approaches, chose E. coli as one of its two focus organisms ( 32 ). Network-based functional prediction tools, such as EcoliNet, will play key roles in such community-wide efforts. Expansion of our knowledge of pathways will contribute to better E. coli metabolic engineering. In addition, EcoliNet’s freely available functional gene associations can be used to reconstruct cofunctional gene networks for other bacterial species via orthology-based methods ( 31 ). Therefore, EcoliNet will be a useful research resource for not only E. coli but also other bacterial species."
} | 1,235 |
26257881 | PMC4523364 | pmc | 8,051 | {
"abstract": "Variation in population size over time can influence our ability to identify landscape-moderated differences in community assembly. To date, however, most studies at the landscape scale only cover snapshots in time, thereby overlooking the temporal dynamics of populations and communities. In this paper, we present data that illustrate how temporal variation in population density at a regional scale can influence landscape-moderated variation in recolonization and population buildup in disturbed habitat patches. Four common insect species, two omnivores and two herbivores, were monitored over 8 years in 10 willow short-rotation coppice bio-energy stands with a four-year disturbance regime (coppice cycle). The population densities in these regularly disturbed stands were compared to densities in 17 undisturbed natural Salix cinerea (grey willow) stands in the same region. A time series approach was used, utilizing the natural variation between years to statistically model recolonization as a function of landscape composition under two different levels of regional density. Landscape composition, i.e. relative amount of forest vs. open agricultural habitats, largely determined the density of re-colonizing populations following willow coppicing in three of the four species. However, the impact of landscape composition was not detectable in years with low regional density. Our results illustrate that landscape-moderated recolonization can change over time and that considering the temporal dynamics of populations may be crucial when designing and evaluating studies at landscape level.",
"introduction": "Introduction The spatial and temporal scale at which ecological studies are performed can greatly influence our understanding of the composition of natural communities and their dynamics (Wiens 1989 ; Levin 1992 ; Chase and Leibold 2002 ; Hastings 2004 , 2010 ; Hortal et al. 2010 ; Wang and Loreau 2014 ). The time scale of a process increases with the spatial scale at which it is operating, i.e. broad-scale processes operate on longer time scales (Wiens 1989 ). The temporal extent of a study will, therefore, limit the patterns and processes that can be discovered (Wiens 1989 ; Hastings 2010 ). Hierarchy theory predicts that processes operating on finer spatial scales can be constrained by those that influence the system on broader spatial scales; e.g., variation between landscapes can be averaged out as climate and topography becomes increasingly important (Allen and Starr 1982 ; Sutcliffe et al. 1996 ). Due to such hierarchical effects, the temporal scale of a study must be adjusted to capture also large-scale variation, or there is a risk that fine-scale patterns are wrongly estimated. Our current understanding of how population and community processes relate to landscape patterns relies to a large extent on studies of disturbance–recolonization events (Turner 2010 ). The degree of recolonization following a local extinction reflects the population dynamics in surrounding more stable patches in the landscape (Tscharntke et al. 2012 ). However, the probability of identifying variation in these fine-scale processes can be affected by regionally synchronized population growth. For example, extreme weather events can push population densities in all landscapes below thresholds where density-dependent dispersal is limited, which will reduce the detectability of landscape-moderated recolonization. Most studies in landscape ecology to date only cover snapshots in time, despite the risk of identifying false patterns by overlooking the dynamics of populations and communities (Chaplin-Kramer et al. 2011 ). The few studies that do utilize repeated measures in time, e.g., Menalled et al. ( 2003 ) and Chaplin-Kramer et al. ( 2013 ) conclude that the temporal extent of the study was critical for the results. In this study, we used a longer time series and utilized the natural variation between years, to explore the relationship between landscape composition and population density during patch recolonization at different regional density levels. As a model system, we used willow short-rotation coppice (SRC) bio-energy stands with a four-year coppice cycle and compared these to undisturbed natural willow stands in the same region. Populations of four interacting insect species were monitored over 8 years: two leaf feeding willow beetles Phratora vulgatissima L. and Galerucella lineola F. (Coleoptera: Chrysomelidae) and two of their main predators, the omnivorous bugs Orthotylus marginalis Reut. and Closterotomus fulvomaculatus De Geer (Heteroptera: Miridae). Our aim with this study was to explore the implications of temporal variation in population density synchronized at a regional scale, in order to understand the importance of patch context for recolonization and community assembly. We hypothesized that regionally high population densities increase the – detectable – impact of landscape composition on insect recolonization of disturbed habitat patches. We predicted that: 1. Recolonization and population growth among all interacting species following a coppicing disturbance event should be landscape-moderated when regional densities are high. Population densities of both species of omnivorous mirids should be higher in landscapes with a high proportion of open habitat, while densities of both species of willow leaf beetles should be higher in more forest-dominated landscapes, i.e., with a lower proportion of open habitat. This pattern was expected because population densities of omnivorous mirids are higher and more stable over time in natural grey willow stands growing in nitrogen-rich environments, i.e., open agriculture-dominated landscapes (A-S. Liman et al. unpubl. data). Willow leaf beetle densities are lower in natural grey willow stands in open habitats partly due to high predation pressure from omnivorous mirids (Dalin 2006 ). 2. When population densities, for whatever reason, are regionally low, there will be no difference in population densities of mirids and willow leaf beetles between landscapes with different proportions of open habitat. This is because density-dependent dispersal should be low in all landscape types when regional population density is low. To our knowledge, this is the only study at landscape scale to date that utilizes a time series approach in order to explore how the relationship between patch context and population density varies at different levels of regional density.",
"discussion": "Discussion Recolonization of SRC willow stands after coppicing was related to landscape composition; population densities of the most common mirid species increased, whereas densities of both willow leaf beetles decreased with increasing proportion of open habitat in the surrounding landscape. However, these patterns were only detected in years with high regional population densities. A reasonable explanation for the variation in outcomes over time is the occurrence of a regional-scale factor, e.g., unfavorable weather conditions could have reduced populations below thresholds where density-dependent dispersal from populations in all landscapes becomes limited. This suggests that awareness of variation in population density, due to e.g., regional synchrony, can be highly relevant for understanding landscape-moderated patterns of recolonization. Ritchie ( 2000 ) illustrated how extremes in abiotic conditions can mask the bottom-up control of herbivore abundance in a nitrogen-limited system. The author concluded that interactions between abiotic conditions and local ecological processes can blur spatial variation at patch level. We interpret our results as probably arising from a somewhat similar phenomenon, but extended to a landscape scale pattern. In years when populations are regionally synchronized at low density levels, bottom-up and top-down effects (e.g., host plant nitrogen status and predation pressure) in source habitats explain less of the variation in population density among SRC willow stands. Despite the apparent problems with ignoring the dynamics of populations, most landscape scale studies use snapshot estimates (Chaplin-Kramer et al. 2011 ). There are currently very few studies based on repeated measures over several years, taking into account different levels of regional density. In addition, few previous studies have looked simultaneously at temporal dynamics of interacting species at a landscape scale, but see Oliver et al. ( 2010 ) and Chaplin-Kramer et al. ( 2013 ), or have considered the actual effects of interactions between weather and landscape composition, but see Cormont et al. ( 2014 ). Our study illustrates several advantages of considering not only snapshot estimates of single species, but rather longer periods of temporal dynamics of interacting populations, as patch context can have such a variable impact on community composition over time. However, because of the low temporal replication, these results can only be used to demonstrate, rather than explicitly test, how regional density levels can influence the conclusions of a landscape study. A possible disadvantage with using a time series approach is, as previously mentioned, potential changes in land-use and management regimes over time. Another problem is to determine how many repeated observations are needed to capture “enough” variation. There are alternatives to using time series data, e.g., could snapshot studies be designed to capture different levels of population density by increasing the spatial scale. This could, e.g., be done through comparisons between different geographic areas that experience different abiotic conditions. However, a spatial approach has the disadvantage of increasing the number of confounding factors and thus the variability in the data. Using two consecutive time series, we have indirectly related variation in recolonization of managed habitats to regional density levels in undisturbed natural habitats, the source of many recolonizing individuals. Our willow–insect model system is likely to be representative of a range of systems, as induced patterns of spatially synchronized population dynamics have been reported for numerous taxa and trophic levels (Liebhold et al. 2004 ). We have assumed, although not explicitly tested, that synchronous exogenous random factors (e.g., temperature) produce the observed patterns. However, the causes of spatial synchrony are often difficult to disentangle as it may, e.g., also arise from dispersal among populations or be indirectly mediated through trophic interactions (Kendall et al. 2000 ; Bjørnstad and Bascompte 2002 ; Liebhold et al. 2004 ). Our results support the idea of bringing together studies on population dynamics with landscape ecology to gain a better understanding of the spatial dynamics of populations in managed landscapes. We conclude that the overall importance of the landscape setting for species recolonization and abundance can be wrongly interpreted if the temporal scale of the study is too short. The results presented here support the suggestion that ecologists would benefit from considering the dynamics of populations and communities, e.g., using longer time series of observations in landscape ecology (Tscharntke and Brandl 2004 ; Chaplin-Kramer et al. 2011 )."
} | 2,835 |
27996047 | PMC5187423 | pmc | 8,053 | {
"abstract": "Kinetic models of metabolism at a genome scale that faithfully recapitulate the effect of multiple genetic interventions would be transformative in our ability to reliably design novel overproducing microbial strains. Here, we introduce k - ecoli457, a genome-scale kinetic model of Escherichia coli metabolism that satisfies fluxomic data for wild-type and 25 mutant strains under different substrates and growth conditions. The k - ecoli457 model contains 457 model reactions, 337 metabolites and 295 substrate-level regulatory interactions. Parameterization is carried out using a genetic algorithm by simultaneously imposing all available fluxomic data (about 30 measured fluxes per mutant). The Pearson correlation coefficient between experimental data and predicted product yields for 320 engineered strains spanning 24 product metabolites is 0.84. This is substantially higher than that using flux balance analysis, minimization of metabolic adjustment or maximization of product yield exhibiting systematic errors with correlation coefficients of, respectively, 0.18, 0.37 and 0.47 (k-ecoli457 is available for download at http://www.maranasgroup.com ).",
"discussion": "Discussion Here, we developed k-ecoli457, a kinetic model of E. coli metabolism that approaches genome-scale coverage (457 reactions and 337 metabolites). Comparisons of k-ecoli457 with a previously constructed core model 15 revealed significant improvement in prediction accuracy despite the significantly expanded model scope and the corresponding paucity of fluxomic data for distal pathways. We found that the global inventory of highly participating metabolites (that is, cofactors), the large number of resolved reaction fluxes coupled to the biomass measurement and the complete description of the proportions of metabolites sequestered within biomass contributed to the prediction improvements in k-ecoli457. A comparison between predicted fluxes, however, revealed that the average relative error of k-ecoli457 when applied to only the core reactions is higher compared with the core model (3 versus 10%). This is because the core model has been tuned exclusively for these reactions whereas k-ecoli457 must describe four times more fluxes in (25 versus 7) experimental data sets. Cofactor concentrations in k-ecoli457 now participate in hundreds of reactions making it very difficult to pinpoint a unique value that matches all experimental data. Significant uncertainty in the experimental data sets across multiple pathways also contributes to the inability to perfectly match the core reaction set. Despite these challenges, 61% of the predicted fluxes by k-ecoli457 (78% in the core model) are within 1 s.d. of the experimental data. In addition, the agreement of the experimental yields (see Fig. 5 ) provides additional confidence for the robustness of the developed model. Prediction deficiencies remained for pathways lacking metabolic flux data sets in response to genetic perturbations (for example, membrane lipid metabolism and ED pathways). For example, we observed that even after the inclusion of additional flux data sets for k-ecoli457 parameterization compared with that of core model, the activity of the ED pathway was not properly captured. As the majority of the training flux data sets (that is, 22 out of 25) had an inactive ED pathway, the k-ecoli457 model predicted the same. While simple inclusion of additional data sets with nonzero ED flux may have rectified this limitation, this a posteriori correction may not be a fair representation of the proposed model and methodology. These limitations are likely to be ameliorated as expanded metabolomic (for example, MetaboLights 34 ) and fluxomic (for example, CeCaFDB 35 ) data sets are becoming increasingly available. Given data sets that span the metabolic capabilities of E. coli , the proposed machine-learning inspired parameterization strategy demonstrated that it is indeed possible to train a single model to predict the genetic and environmentally perturbed phenotypes with fidelity. In the same spirit, the same multi-data set parameterization concepts can be leveraged for applications of kinetic models in personalized healthcare 36 , biomarker identification 37 , drug discovery 38 and modelling of microbial communities 39 . Remaining challenges not addressed in this effort include allowing for substrate(s) uptake rates to become an output of the kinetic model. In k-ecoli457 all mutant fluxes in the training data sets were scaled with the corresponding substrate uptake rate. Given substrate uptake rates data sets 24 40 for different mutations and growth conditions, a kinetic formalism that describes carbon uptake could be constructed and parameterized largely independent of internal reactions. In addition, large-scale metabolomic data sets for absolute or even relative concentrations 34 can directly be ported in the machine-learning algorithm to further constrain model parameter values. This was not attempted here as we chose to treat metabolomic data a posteriori as a model consistency check. In addition, the assembled compilation of experimental product yields for 320 designed strains could serve as a starting point for more comprehensive compilations 41 that will help to fairly assess follow-up efforts aimed at improving the accuracy and coverage of k-ecoli457. Kinetic model parameterization using such comprehensive data sets, however, must be carefully interpreted. For example, there exists substantial evidence for the presence of pathway channelling 42 43 44 in metabolism as a mechanism for increasing the local concentration of metabolites and thus boost reaction rates (for example, channelling of glycolysis intermediates in E. coli 45 ). As a result, if the relevant metabolite participates in other reactions, then the kinetic model will simply pool all the ‘local' concentrations of the metabolite within a single ‘average' concentration. This difference between local and average concentrations will propagate in the value of k cat so as the reaction flux value is matched. This means that the values of the estimated metabolite concentrations and k cat values may not always reflect in vivo kinetics but rather represent cell-averaged values. In addition, many other factors such as growth stage of the strain or even experimental group carrying out the fluxomic analysis can affect the quality and reproducibility of the flux data sets. These factors can lead to different flux data sets for exactly the same genotype (for example, different flux distributions for wild-type strain in ref. 20 versus ref. 46 or the different effect of pfkA and pfkB knockouts on glycolytic activity in ref. 20 versus ref. 47 ). Including conflicting flux data sets would cause significant problems in parameter estimation as the model will try to match the average values between the two data sets that are likely not physiologically relevant. Accounting for such variations remains an important topic to be addressed in follow-up studies. Looking beyond substrate-level regulation, the increasing availability of data sets that provide genome-wide collections of interactions between mRNAs 48 , proteins 49 and metabolites 50 has dramatically expanded our knowledge of transcriptional, (post)translational and substrate-level interactions. Although the relative contribution of each of these regulatory layers is likely to be context dependent 51 , systematic implementation of regulatory events across multiple layers will ultimately be needed. Successful implementation of allosteric modification 52 and substrate-level regulation 11 with elementary kinetic mechanisms described in this paper establish a foundation for including additional layers. Developing efficient methods for reducing the complexity of models into more manageable ones without any information loss would also increase usability and community acceptance. This will also reduce computation complexity of integrating kinetic information into computational strain design protocols 4 11 . In particular, we have recently integrated 36 reactions with a kinetic description in the core model for strain design using the k-OptForce procedure 11 . Moving towards strain design with a full kinetic representation will ultimately require advances in solution techniques and accelerated ways of reaching steady-state fluxes and concentrations."
} | 2,107 |
26364915 | null | s2 | 8,055 | {
"abstract": "Foremost among the challenges facing single molecule sequencing of proteins by nanopores is the lack of a universal method for driving proteins or peptides into nanopores. In contrast to nucleic acids, the backbones of which are uniformly negatively charged nucleotides, proteins carry positive, negative and neutral side chains that are randomly distributed. Recombinant proteins carrying a negatively charged oligonucleotide or polypeptide at the C-termini can be translocated through a α-hemolysin (α-HL) nanopore, but the required genetic engineering limits the generality of these approaches. In this present study, we have developed a chemical approach for addition of a charged oligomer to peptides so that they can be translocated through nanopores. As an example, an oligonucleotide PolyT20 was tethered to peptides through first selectively functionalizing their N-termini with azide followed by a click reaction. The data show that the peptide-PolyT20 conjugates translocated through nanopores, whereas the unmodified peptides did not. Surprisingly, the conjugates with their peptides tethered at the 5'-end of PolyT20 passed the nanopores more rapidly than the PolyT20 alone. The PolyT20 also yielded a wider distribution of blockade currents. The same broad distribution was found for a conjugate with its peptide tethered at the 3'-end of PolyT20, suggesting that the larger blockades (and longer translocation times) are associated with events in which the 5'-end of the PolyT20 enters the pore first."
} | 379 |
32714758 | PMC7375236 | pmc | 8,056 | {
"abstract": "Abstract A remarkable feature of modern electronic and photonic devices is the ability to maintain their geometric and physical properties in various circumstances for practical applications. However, there is an increasing demand for reconfigurable devices and systems that can be triggered or switched by external stimuli to change geometric, physical, and/or biochemical properties to meet specific requirements such as compact, lightweight, energy‐efficient, and tunable features. Here, a set of phototunable and photoreconfigurable electronic and photonic devices composed of reconfigurable arithmetic circuits and programmable coding metamaterials at terahertz frequencies, empowered by a diffractive optics platform using naturally extracted silk proteins, is reported. These protein‐based diffract optics are precisely manufactured into special microstructures for phase modulation of incident light and can be programmed to degrade at controlled rates. This allows spatial and temporal transformation of the incident light into desired intensity profiles to modulate the electrical properties of multiple photosensitive elements/components within the device simultaneously or discretely. Thus, the optoelectronic functionality of fabricated devices can be tailored to specific applications. Therefore, the approach makes it possible to efficiently fabricate tunable, reconfigurable transient electronic and photonic devices and systems."
} | 361 |
39606108 | PMC11600729 | pmc | 8,057 | {
"abstract": "Introduction Fusarium wilt disease (FWD) of tobacco is a destructive disease caused by Fusarium spp. in tobacco-growing regions worldwide. The Fusarium spp. infection may alter the composition and structure of the tobacco root microbial community; however, the relationship between these factors under large-scale geographical conditions in China remains underexplored. Methods In the context of this investigation, soil samples from the rhizosphere of tobacco plants were procured from fields afflicted with FWD and those devoid of the disease in the Hanzhong region of Shaanxi province, as well as in the Sanmenxia and Nanyang regions of Henan province. These regions are recognized for the commercial cultivation of tobacco. The examination focused on discerning the influence of tobacco FWD on the composition and configuration of the rhizosphere microbial community, along with their co-occurrence patterns. This scrutiny was underpinned by targeted PCR amplification and high-throughput sequencing (amplicon sequencing) of the 16S rRNA gene and the ITS1 region. Results The amplicon data analyses showed that FWD influenced the microbial structure and composition of the tobacco rhizosphere soil. FWD had a greater impact on the microbiome of the tobacco fungal community than on the microbiome of the bacterial community. Healthy plants had the ability to recruit potential beneficial bacteria. Diseased plants were more susceptible to colonization by other pathogenic fungi, but they still had the capacity to recruit potential beneficial bacteria. The analysis of microbial intra- and inter-kingdom networks further indicated that FWD destabilized microbial networks. In the overall microbial interaction, microorganisms primarily interacted within their boundaries, but FWD increased the proportion of interactions occurring across boundaries. In addition, FWD could disrupt the interactions within microbial network modules. Discussion This study provides evidence that FWD can cause changes in the composition and network of microbial communities, affecting the interactions among various microorganisms, including bacteria and fungi. These findings contribute to our understanding of how plant microbiomes change due to disease. Furthermore, they add to our knowledge of the mechanisms that govern the assembly and interactions of microbial communities under the influence of FWD.",
"conclusion": "5 Conclusion In the present study, we reported the effect of FWD occurrence on the composition and structure of the tobacco root microbial community in diseased tobacco plants compared to healthy plants. The amplicon data analysis showed that FWD influenced the microbial structure and composition of the tobacco rhizosphere soil. Several genera of potentially pathogenic fungi, including Fusarium, Penicillium, Plectosphaerella , and Thielavia from the Ascomycota phylum, were enriched in diseased tobacco rhizosphere soils. Potentially beneficial bacteria, such as Rhizobium, Sphingobium , and Ensifer from the Proteobacteria phylum, were enriched in healthy tobacco rhizosphere soils. Bacteria occupy a crucial position in microbial networks, and their interactions with pathogens play a vital role in sustaining healthy microbial ecosystems. The current study provides a good understanding of microbiome assembly and function under FWD and reveals the potential for utilizing soil microbiomes to promote plant health and sustainable agricultural production.",
"introduction": "1 Introduction Fusarium wilt of tobacco is a destructive plant disease, and it is caused by the soil-borne pathogen Fusarium spp. in tobacco-growing regions worldwide (Pandey, 2023 ). The Fusarium spp. lives as dormant chlamydospores in soil or mycelia on crop residues of infected plants (Toussoun et al., 1963 ). After overwintering, the fungi infect plant roots where the lateral root emerges from the primary root or in wounds. Once the vessels have been infected, the vascular tissues become blocked, resulting in the typical wilting (Boddy, 2016 ). More than seven species of Fusarium , which are known to infect tobacco plants, have been reported in China, namely F. oxysporum (Dean et al., 2012 ), F. fujikuroi (Shen et al., 2023 ), F. tricinctum (Qiu et al., 2023 ), F. brachygibbosum (Qiu et al., 2021 ), F. meridionaleall (Gai et al., 2023 ), F. solani (Yin et al., 2022 ), and F. falciforme (Qiu et al., 2022 ). The FWD occurrence caused serious economic losses in tobacco production in several provinces in China (Yao et al., 2021 ), and disease incidence ranges from 3 to 30% in Yunnan province (Gai et al., 2023 ). An integrated approach involving resistance breeding, cultural measures, and biological and chemical controls is extensively used for effectively managing the FWD. However, the use of resistant varieties, the most efficient approach, may have a negative impact on the yield (Salameh et al., 2011 ; Li et al., 2020 ); cultural measures are limited, while the use of chemical fungicides carries the risk of pathogen resistance development (Lucas et al., 2015 ). By comparison, biological control is considered a promising alternative to fungicides, and understanding microorganism interactions in rhizosphere soil is fundamental to developing innovative biocontrol methods against plant pathogens (Mitter et al., 2019 ). The rhizosphere, a complex and dynamic ecosystem, is home to a diverse microbial community (Chen et al., 2023 ). Microbial interactions in the rhizosphere environment can either suppress or promote plant diseases (Fitzpatrick et al., 2018 ). Microbial communities form intricate networks in the soil, building a biological barrier that facilitates microbe interactions and aids plant defenses against pathogen invasion near the root surface (Raaijmakers et al., 2009 ). Weibing Xun et al. used the “reductionist” and “strain knock-out” strategies to simplify the microbiota and demonstrate that keystone bacterial strains play an important role in maintaining plant health (Xun et al., 2023 ). While root microbiota are predominantly beneficial, certain members can act as pathogens, inducing plant diseases through mechanisms, thereby exerting detrimental effects on plant growth and overall performance (Fitzpatrick et al., 2018 ; Nadarajah and Abdul Rahman, 2021 ). The invasion of pathogens can affect strongly the relationships of the plant rhizosphere microbiome (Xiao et al., 2024 ). In the rhizosphere, soil microbes engage in interactions with pathogens, eliciting community responses that culminate in disease (Nobori et al., 2018 ). For instance, the non-pathogenic bacterial species Erwinia toletana, Pantoea agglomerans , and Erwinia oleae collaborate with the primary pathogen Pseudomonas savastanoi pv. savastanoi, exacerbating disease severity in olive trees (Buonaurio et al., 2015 ). Studies have shown that Fusarium can alter the composition and function of plant rhizosphere microorganisms, thereby influencing the occurrence of plant diseases (Chang et al., 2021 ; Gao et al., 2021 ). Fusarium invasion influences the enrichment of specific beneficial microbial taxa in the plant rhizosphere, which may contribute to the plant's resistance to pathogen infection (Li et al., 2021 ). Symbiotic network analysis is increasingly utilized to deduce potential microbial interconnections and serves as a fundamental tool for gaining insights into microbial responses to pathogen invasions (Guimerà and Nunes Amaral, 2005 ). It is vitally important to our research into the potential interactions between microbiota and their responses to pathogen invasion. Currently, limited research has focused on the changes in tobacco rhizosphere microbial communities and their interactions after Fusarium invasion. In this study, therefore, the rhizospheric soil samples of tobacco plants with FWD occurrence or without were collected from the tobacco-growing regions of Shaanxi and Henan provinces, China, where FWD incidence was high. We hypothesized that the disease occurrence influenced changes in the microbiome composition. To test this hypothesis, we explore the diversity and composition differences between the microbiomes of healthy and diseased plants based on the amplicon sequencing data. Moreover, the co-occurrence networks of healthy and diseased plant microbiomes were also compared, and this will provide new insight into the stability of communities as well as microbial succession under different environmental conditions.",
"discussion": "4 Discussion 4.1 Effect of FWD on rhizosphere microbial composition of tobacco The rhizosphere microbiome plays an important role in plant health. Understanding the differences in microbial communities between diseased and healthy plants in rhizosphere soils as well as investigating key taxa and their correlations are necessary for exploring the interactions between plants and pathogens (Huang et al., 2022 ). In this study, significant differences were found in the microbiomes between the diseased (FWD) and healthy rhizosphere soils ( Figure 2 ). Usually, plants provide nutrients and niches for microbes; in return, these microbes play pivotal roles in promoting plant growth and tolerance against biotic and abiotic stresses and forming a barrier against the invasion of pathogens. For instance, species of Chitinophaga, Flavobacterium , and Pseudomonas were enriched with sugar beet to suppress the root pathogen Rhizoctonia solani (Carrión et al., 2019 ). Recent studies have proven that flavobacterium is significantly associated with Fe (III) Hcl , potentially influencing multiple nitrogen cycle variables, and proving useful for the root sheath of barley grown in acidic soil (Yu et al., 2021 ; Xu et al., 2023 ). The abundance of Rhizobium and Sphingomonas was positively correlated with nitrogen fixation (Liu et al., 2023 ). This can enhance the plant's nitrogen utilization and consequently promote plant health (Vries et al., 2022 ). Our results also showed diversity and abundance of beneficial microbes were higher in healthy tobacco plants than in diseased plants ( Figure 4 ). Beneficial flora indirectly enhances plant growth and nutrient uptake by modifying the structure and function of native rhizosphere microbial communities (Hu et al., 2021 ; Pang et al., 2021 ). However, pathogen infestation may cause changes in the composition of plant root secretions and in the structure of biological communities. In this study, The LEfSe analysis revealed that genera of beneficial bacteria Flavobacterium, Rhizobium, Sphingobium , and Ensifer were enriched in the diseased and healthy tobacco plant rhizosphere, but their abundances were significantly higher in the healthy tobacco plants than that in the diseased plants. Colonization and host infestation of pathogenic Fusarium spp. causing FWD in soil can influence changes in the structure of rhizosphere microbial communities. In addition, few studies showed that plants with FWD have more lateral roots (Silva Lima et al., 2019 ). The flavobacterium enriched in diseased rhizosphere soil may be associated with the generation of more lateral roots in tobacco plants. Therefore, these results displayed that changes in diversity and abundance of beneficial microbes in the bacterial and fungal community structures were associated with diseased and healthy tobacco plants. Analyses of diseased and healthy microbiome structures provide evidence for soil-beneficial microorganisms that maintain plant health; it is necessary to conduct culture-based experiments to prove the hypothesis. Specifically, it is important to isolate potentially beneficial bacteria that are enriched in the rhizosphere soil and evaluate their antifungal activity against pathogens. 4.2 Effect of FWD on the rhizosphere microbial network structure of tobacco According to theoretical modeling and simulations, microbial networks with lower positive correlations and higher negative correlations among members are more stable (Coyte et al., 2015 ; Hernandez et al., 2021 ). The healthy microbial network demonstrated a higher percentage of negative correlations than the diseased microbial network, including its core taxa, except for the fungi intra-kingdom co-occurrence network. In this study, we found that pathogenic fungi in the health network have stronger negative correlations with other microorganisms. The stability of healthy microbial networks may be maintained by bacteria that compete with pathogenic fungi for access to the same root secretions (Huang et al., 2017 ). The proportion of interactions between bacteria and fungi in the pathogenic network increased. Burkholderia glumae , a seed-borne plant pathogenic bacterium, and Fusarium graminearum , an air-borne plant pathogenic fungus, interact to enhance bacterial survival, dispersal of both bacteria and fungi, and promote disease progression on rice plants (Ruiz-Bedoya et al., 2023 ). The interaction between bacteria and fungi in the disease network can potentially facilitate the dissemination of Fusarium and contribute to the progression of FWD. In the interaction network, bacteria occupy more nodes and correlations. The top 10 nodes in the health network consist solely of bacteria, whereas the disease network has fungi. Bacteria were more dominant in the healthy network than in the diseased network. The findings indicate that bacteria are the predominant group in the soil, indicating their potential role in preserving soil health. 4.3 Effect of FWD on the modularity of microbial networks Community stability is influenced by modularity and microbial interactions (Coyte et al., 2015 ). In this study, the modularity of the disease network exceeded that of the health network. The analyzed results also indicated that the connections among modules in the health network are more intricate, whereas the connections within modules in the disease network are more complex. In microbial networks, there is a high probability that different modules have different functions in the ecological niche. A healthy microbiome may promote interactions between different functional microbes to maintain plant health (Fan et al., 2019 ). Furthermore, we conducted network analysis to visualize modules with high interactions. Notably, the largest module observed in the network was deemed as the central module in our study (Huang et al., 2019 ). This central module serves as a crucial hub of microbial interactions, likely playing a significant role in shaping the overall microbial community dynamics and subsequently influencing plant health. By focusing on this central module, our analysis revealed that the central module in the health network exhibited a higher number of nodes and edges than the other modules. In addition, Proteobacteria occupy a higher proportion in the largest module of the health network than the pathogenic network. Several potentially beneficial microorganisms belong to the Proteobacteria. Microdiversity can result in the emergence of distinct ecotypes within a single species. These ecotypes are hypothesized to confer temporal and spatial stability to the species. In previous research, we found that ecotypes within the Proteobacteria shared the same OTUs but exhibited different distribution patterns across space and time (García-García et al., 2019 ). These microorganisms may play a crucial role in strengthening the interrelationship between the network structures and key microbial community functions, thereby contributing to the maintenance of network stability (Yuan et al., 2021 )."
} | 3,903 |
31138721 | PMC6584873 | pmc | 8,058 | {
"abstract": "Within the last decade, there has been an explosion of multi-omics data generated for several microbial systems. At the same time, new methods of analysis have emerged that are based on inferring networks that link features both within and between species based on correlation in abundance.",
"conclusion": "CONCLUSIONS AND FUTURE DIRECTIONS Interspecies interactions within microbiomes are extremely complex, and identifying interactions and understanding their contribution to the overall community can be very difficult. However, as community response is a culmination of specific interactions, their delineation is critical. With the large increase in the availability of omics analysis, we now have the tools to use network inference to predict and understand interspecies interactions in natural microbial communities. Some of my own work and other recent studies have shown that such networks are powerful ways to view how processes are related between species. They can predict where metabolites might be shared between species or where there may be instances of division of labor and metabolic coordination by looking for instances of coordinated production and uptake. Through the application of centrality, they can also be used to identify genes, and thus processes, that are particularly important to a system. The success of networks that have been seen with simple systems (phototroph/heterotroph, host/pathogen) shows the utility of this approach, and by understanding the challenges and where the pitfalls are, we are well positioned as a community to apply network techniques to more complex systems comprised of many species. Moving forward, it will be critical to ensure that the right network method is being applied to the right experiments. We can see here that many inference approaches have particular strengths over others, and the correct application of these approaches will be needed to gain the most robust insight into the systems we are interrogating. As we continue to apply network approaches to more complex systems, the hurdles of these more species-rich networks will likely require a greater incorporation of metagenomics and metabolomic data, either knowledge of certain pathways (KEGG databases) or the collection of metabolomics, to query what molecules are present. Over the next decade, I expect to see several new network studies that specifically attempt to link not only species but specific transcripts and proteins across species in complex systems such as soil, marine environments, or human anatomical sites. The increase in metagenomic data as well as critical work being done on how to use network inference tools for these complex multispecies systems will make multispecies networks easier to infer, interrogate, and interpret. The very detailed and specific knowledge that multispecies networks can offer opens up the possibility for increased understanding of a number of microbiomes, allowing us to modify and harness them to improve human health and wellbeing."
} | 749 |
38023904 | PMC10676204 | pmc | 8,059 | {
"abstract": "Over the years, microbial community composition in the rhizosphere has been extensively studied as the most fascinating topic in microbial ecology. In general, plants affect soil microbiota through rhizodeposits and changes in abiotic conditions. However, a consensus on the response of microbiota traits to the rhizosphere and bulk soils in various ecosystems worldwide regarding community diversity and structure has not been reached yet. Here, we conducted a meta-analysis of 101 studies to investigate the microbial community changes between the rhizosphere and bulk soils across various plant species (maize, rice, vegetables, other crops, herbaceous, and woody plants). Our results showed that across all plant species, plant rhizosphere effects tended to reduce the rhizosphere soil pH, especially in neutral or slightly alkaline soils. Beta-diversity of bacterial community was significantly separated between into rhizosphere and bulk soils. Moreover, r-strategists and copiotrophs (e.g. Proteobacteria and Bacteroidetes) enriched by 24-27% in the rhizosphere across all plant species, while K-strategists and oligotrophic (e.g. Acidobacteria, Gemmatimonadete, Nitrospirae, and Planctomycetes) decreased by 15-42% in the rhizosphere. Actinobacteria, Firmicutes, and Chloroflexi are also depleted by in the plant rhizosphere compared with the bulk soil by 7-14%. The Actinobacteria exhibited consistently negative effect sizes across all plant species, except for maize and vegetables. In Firmicutes, both herbaceous and woody plants showed negative responses to rhizosphere effects, but those in maize and rice were contrarily enriched in the rhizosphere. With regards to Chloroflexi, apart from herbaceous plants showing a positive effect size, the plant rhizosphere effects were consistently negative across all other plant types. Verrucomicrobia exhibited a significantly positive effect size in maize, whereas herbaceous plants displayed a negative effect size in the rhizosphere. Overall, our meta-analysis exhibited significant changes in microbial community structure and diversity responding to the plant rhizosphere effects depending on plant species, further suggesting the importance of plant rhizosphere to environmental changes influencing plants and subsequently their controls over the rhizosphere microbiota related to nutrient cycling and soil health.",
"conclusion": "5 Conclusions Our study demonstrates a significant distinction in the microbial community structure between the bulk and rhizosphere soils, which simultaneously vary depending on plant species. In particular, r-strategists (e.g. Proteobacteria and Bacteroidetes) enriched in the rhizosphere but K-strategists (e.g. Acidobacteria, Gemmatimonadete, Nitrospirae, and Planctomycetes) depleted in the rhizosphere. In contrast, the responses of some microbiota (e.g. Actinobacteria, Firmicutes, Chloroflexi, Verrucomicrobia, Ascomycota, and Basidiomycota) to plant rhizosphere effects were dependent on plant types through species-specific manner. This meta-analysis has revealed that plants generally exert a rhizosphere acidification effect through the release of organic acids via root exudates, which may particularly affect certain microbial species in the rhizosphere. Further investigations are needed to identify various environmental factors that influence plants and, subsequently, their influences on the rhizosphere microbiota associated with nutrient cycling and soil health.",
"introduction": "1 Introduction The rhizosphere is the soil volume around the root with a rich diversity of microorganisms, which is strongly affected by root functioning ( Philippot et al., 2013 ; Kuzyakov and Razavi, 2019 ; Qu et al., 2020 ). The individual and interconnected processes occurring in the rhizosphere have been extensively characterized, encompassing exudate release, nutrient acquisition, and water uptakes ( Philippot et al., 2013 ; Sasse et al., 2018 ; Kuzyakov and Razavi, 2019 ). These processes have contributed to the development of a distinct microbial community structure in the rhizosphere compared to the bulk soil, commonly referred to as the rhizosphere effect ( Aira et al., 2010 ; Fan et al., 2017 ; Sasse et al., 2018 ; Ling et al., 2022 ). The rhizosphere microbiome can exert significant influences on plant health, nutrition, and growth ( Berendsen et al., 2012 ; Philippot et al., 2013 ; Finkel et al., 2017 ). Plants benefit from rhizosphere microorganisms to help acquire nutrients and suppress pathogenic invasions ( Bulgarelli et al., 2013 ; Poole, 2017 ; Ling et al., 2022 ). For example, plant growth-promoting rhizobacteria (PGPR) promotes plant growth through a wide range of mechanisms, which is beneficial for the sustainability of agriculture as the biofertilizers and biopesticides ( Pii et al., 2015 ). Similarly, legumes require rhizobia and mycorrhizal fungi to improve plant productivity and N 2 fixation ( van der Heijden et al., 2008 ; Kaschuk et al., 2010 ). Although genotypes, root architecture, and growth stages tend to affect the plant recruits relatively distinct rhizobacterial communities ( Aira et al., 2010 ; Li et al., 2014 ), plant itself exerts a highly selective effect to shape the microbial community composition in the rhizosphere, so the community composition can be greatly similar across different environments ( Marschner et al., 2004 ; Costa et al., 2006 ; Berg and Smalla, 2009 ; Ling et al., 2022 ). In addition, soils covered with vegetation, as one of the sources of atmospheric CO 2 , may strongly contribute to the CO 2 efflux by root and rhizomicrobial respiration ( Kuzyakov, 2006 ; Werth and Kuzyakov, 2008 ; Trivedi et al., 2013 ). The distinct rhizomicrobial respiration processes (microbial respiration or respiration by heterotrophs), regulating soil organic matter (SOM) decomposition, was identified as one of the important fine-scale components of the global carbon (C) cycle ( Cheng, 1999 ; Kuzyakov, 2006 ; Huo et al., 2017 ; Jackson et al., 2019 ). The microbial community control over C cycling in the rhizosphere has been extensively studied ( Kuzyakov, 2002 ; Schimel and Schaeffer, 2012 ; Schindlbacher et al., 2015 ; Kumar et al., 2016 ; Hunninghaus et al., 2019 ; Semenov et al., 2019 ). Notably, some microbiota exhibited strong resistance to perturbations, while other specific microorganisms respond rapidly to changing environmental conditions ( Jiang et al., 2017 ). This caused a weak but measurable effect on the rhizosphere microbial community even within a single plant species ( Bokulich et al., 2014 ). Therefore, comprehending the taxonomic profiles of microbial communities in the rhizosphere and bulk soil is critical to understand the microbial functions to support plant growth and manage C cycling in the rhizosphere. However, the information in the rhizosphere and bulk soils with respect to the taxonomic profiles of microbial communities remains largely unexplored. Both plant species and soil properties affect the diversity and structure of rhizosphere microbial community ( Garbeva et al., 2008 ; Jiang et al., 2017 ; Vorholt et al., 2017 ). The impact of soil characteristics on rhizosphere microbial community is as significant as that of the plant itself ( Marschner et al., 2004 ; Fan et al., 2018 ). In general, plant root systems alter the rhizosphere pH by releasing H + or OH − , and affecting the equilibrium between cations and anions at the root-soil interface ( Hinsinger et al., 2003 ; Kuzyakov and Razavi, 2019 ). The pH of the soil is a key factor in determining changes in the structure and diversity of the microbial community ( Tripathi et al., 2018 ; Kuzyakov and Razavi, 2019 ; Lopes et al., 2021 ). As previous studies reported that soil pH was the best predictor of soil microbial community diversity ( Fierer and Jackson, 2006 ). Therefore, investigating rhizosphere microbiomes is critical for establishing a more complete knowledge of the role of soil pH on microbial ecology. However, information is lacking on the association of rhizosphere soil pH with the plant species. Recently, sequencing and phylogenetic analysis of cultivation-independent 16S rRNA genes provided the foundation for modern studies of microorganisms living in the soil ( Lundberg et al., 2012 ; Fan et al., 2017 ; Fan et al., 2018 ; Ling et al., 2022 ). High-throughput sequencing enables quantitative insights into microbial community diversity and structure in high resolution ( Singer et al., 2016 ). Compared to traditional microbial community analyses, high-throughput sequencing is known for its labor efficiency and cost-effectiveness ( Reuter et al., 2015 ). Most studies must be deposited the raw data in a public gene bank, causing a huge and extensive rhizosphere sequencing data set, which has cracked the way to further research into the broad principles of rhizosphere microbiome selection from bulk soils ( Ling et al., 2022 ). Thus, it was urgently needed for a comprehensive study synthesizing previous findings to infer the difference in the microbial community structure between rhizosphere and bulk soils to a wide range of plants and environmental conditions. Here, we conducted a global meta-analysis of microbial communities in the rhizosphere and bulk soil, with a specific focus on bacteria and fungi due to their high prevalence and the extensive attention they have received in comparison to other members of the community (e.g., archaea, protists, and nematodes, etc.) ( Ling et al., 2022 ). The 16S and ITS rRNA amplicon-based sequencing data were collected from published articles to date. Specifically, our objective was to answer the following questions: (i) how plant rhizosphere affects soil pH and microbial diversity and composition, (ii) to what extent major microbial taxa respond to plant rhizosphere effects, (iii) whether the plant rhizosphere effects on microbial community were dependent on plant species?",
"discussion": "4 Discussion 4.1 Soil pH responding to rhizosphere effects in various plant species Our meta-analysis revealed that both the effect sizes of bulk soil pH > 6 and the mean effect sizes of soil pH were significantly negative ( \n Figure 2 \n ). These findings imply that most plants tend to decrease the rhizosphere soil pH compared with the bulk soil across all studies. A previous study has reported that the release of H + by roots is a dominant mechanism for plants to mobilize nutrients and maintain electrochemical potential on the root surface in slightly acidic, neutral, and alkaline soils ( Marschner, 2012 ). Under the extreme soil pH condition (too low or too high), plant roots can mitigate the constraints, such as plant roots that could alleviate Al 3+ or Fe 3+ toxicity in acidic pH conditions, and also Fe or Mn deficiency in alkaline pH conditions ( Philippot et al., 2013 ; Kuzyakov and Razavi, 2019 ). Thus, our results that the effect sizes of rhizosphere were significantly lower than zero in soil pH > 6 further suggested that plant roots could alleviate constraints under neutral or slightly alkaline conditions. Moreover, our result showed the effect sizes of rice and vegetables were significantly lower than zero, which implies that the roots of rice and vegetables tend to acidify the rhizosphere soil more severely than other plants. This is in line with the fact that rice root exudates organic acid decreasing rhizosphere soil pH, increasing amino acid availability, and promoting ammonia release and subsequent nitrification ( Dohrmann et al., 2013 ; Di Salvo et al., 2018 ). Furthermore, legumes acidify the rhizosphere soil through excess cation uptakes during N 2 fixation and photosynthetic activity to alter cation-anion uptake ratios ( Bolan et al., 1991 ; Rao et al., 2000 ; Rao et al., 2002 ). Similarly, it has been found that the rhizosphere soil pH of pak choi decreased by root exudates, which mainly consist of organic acids and amino acids (e.g., citric acid, ferulic acid, cinnamic acid, glutamic acid, alanine, and valine) ( Kim et al., 2017 ; Jeon et al., 2018 ; Cai et al., 2019 ). As previous studies report most plant species tend to acidify the rhizosphere soil ( Kuzyakov and Razavi, 2019 ), our results further provide substantial evidences to support that these pH variation may significantly contribute to the assembly of soil microbial community in plant rhizophere. 4.2 Distinct microbial community diversity and structure in the rhizosphere In our analysis, PCoA of the Bray-Curtis distances showed significant clustering of bacterial communities between rhizosphere and bulk soils, with decreased community diversity (Shannon index) observed in the rhizosphere soil across different plant species ( \n Figures 3 \n , \n 4B \n ). This is consistent with previous findings that diversity decreased from the bulk soil to the roots ( Poole, 2017 ; Semenov et al., 2019 ). The significant contrast between the bulk soil and rhizosphere soil is a crucial factor contributing to variations in microbiota composition ( Yan et al., 2017 ; Ren et al., 2020 ). For example, Fan et al. (2017) reported that the distance decay relationship (from the root surface to bulk soil) can reflect variations in microbial community composition. In addition, it has been suggested that the decrease in diversity from the bulk soil to roots could be attributed to root “rhizosphere effect” ( Bulgarelli et al., 2012 ; Lundberg et al., 2012 ; Barajas et al., 2020 ; Attia et al., 2022 ; Santoyo, 2022 ). Specific microorganisms are commonly selected by plant roots to colonize the rhizosphere, which can attract beneficial microorganisms to improve nutrient acquisition and combat pathogenic taxa for plants ( Dennis et al., 2010 ; Berendsen et al., 2012 ; Fan et al., 2017 ). Generally, the rhizosphere is a highly selective environment that can select microbiome through two distinct processes ( Fan et al., 2017 ; Fan et al., 2018 ). The first process involves the general recruitment of microbes to the proximity of the root, whereas the second process involves the transition of microbes from external to internal occupancy in the root ( Edwards et al., 2015 ). Molecular signals from plants, including components of root exudates and possibly cell wall or membrane proteins ( Edwards et al., 2015 ; Edwards et al., 2018 ; Kuzyakov and Razavi, 2019 ), are involved in the selection of microbial communities. Notably, the DNA extraction protocols for metagenomic DNA, particularly in relation to rhizosphere and soil samples, may introduce inherent biases due to variations in rhizosphere soil sampling procedures and differences arising from DNA extraction methods. Despite the presence of disparities, our study represents a comprehensive synthesis of over 100 studies, thus mitigating any potential systematic biases. Additionally, the results of the present meta-analysis showed that rhizosphere soil microbial community structure varies depending on plant species ( \n Figure 4C \n ). This is in agreement with previous studies that the plant species and the genotypes of individual plants can exert a profound influence on the composition of their associated microbial communities in the rhizosphere ( Schweitzer et al., 2008 ; Lau and Lennon, 2012 ; Bever et al., 2013 ). However, our meta-analysis showed the phyla Proteobacteria and Bacteroidetes are consistently enriched in the rhizosphere ( \n Figure 5 \n ). This result suggests that the phyla Proteobacteria and Bacteroidetes are well-suited to the rhizosphere, which provides C-rich conditions for high metabolic activity, fast growth, and propagation ( Pausch et al., 2013 ; Kuzyakov and Razavi, 2019 ). The phyla Proteobacteria and Bacteroidetes are generally considered r-strategists and copiotrophs that respond to labile C sources, and fast-growing microbiota with population opportunity fluctuations ( Fierer et al., 2007 ; Peiffer et al., 2013 ). In contrast, our meta-analysis showed that the phyla Acidobacteria, Gemmatimonadete, Nitrospirae, and Planctomycetes are consistently depleted in the rhizosphere ( \n Figures 6 \n , \n 7 \n ). It has been previously reported that the phyla Acidobacteria were depleted in wheat rhizosphere under the field of North China Plain ( Fan et al., 2017 ). Moreover, a previous study reported that the phyla Acidobacteria were enriched in the bulk soil, while depleted in the rhizosphere soil under the Central European grasslands and forests ( Kaiser et al., 2016 ). Similar results have been revealed in Mexico’s agroecosystem, German grassland, and forest soil as well ( Foesel et al., 2014 ; Embarcadero-Jimenez et al., 2016 ; Dawson et al., 2017 ). As a result, these phyla are extremely similar in rhizosphere soil across varied plant species ( Ling et al., 2022 ). Similarly, Planctomycetes are more abundant in the rhizosphere than in bulk soil ( Fierer et al., 2007 ). The phyla Gemmatimonadete, Nitrospirae, and Planctomycetes have been extensively detected as K-strategists (slow-growing microbiota) and oligotrophic that are adapted to survive when resource was limited or low substrate concentrations ( Fontaine et al., 2003 ; Bernard et al., 2007 ; Blackburne et al., 2007 ), and generally considered to be enriched in the bulk soil with less energy and nutrients compared with the rhizosphere soil. Overall, our meta-analysis implied that the phyla Proteobacteria and Bacteroidetes enriched commonly in the rhizosphere of most plant species, while Acidobacteria, Gemmatimonadete, Nitrospirae, and Planctomycetes were depleted contrarily by plant rhizosphere effects. Notably, agricultural practices might make up the plant-associated microbial communities. Tillage can lead to shifts in microbial communities as anaerobic microorganisms are exposed to oxygen ( Coleman-Derr et al., 2016 ; Dawson et al., 2017 ). Reduced or no-till farming can preserve anaerobic niches and maintain a different microbial community structure. Synthetic fertilizers often provide easily accessible nutrients, which can favor certain microbial taxa, while organic fertilizers release nutrients slowly, supporting a more diverse microbial community ( Yang et al., 2017 ). Crop rotation and the diversity of crops planted in a field can provide different root exudates and organic matter, altering the nutrient availability and microbial community. This practice promotes a more diverse and dynamic microbial community ( Visioli et al., 2018 ; Wang et al., 2020 ). Moreover, the responses of the phyla Actinobacteria, Firmicutes, Chloroflexi, and Verrucomicrobia to plant rhizosphere were highly dependent on plant species ( \n Figures 6 \n , \n 7 \n ). The phyla Actinobacteria was significantly depleted in the rhizosphere of rice, herbaceous, woody, and other crops, while enriched in that of vegetables. For example, it has been found that the phylum Actinobacteria dominated the wild beet rhizosphere ( Zachow et al., 2014 ) and lettuce rhizosphere ( Blau et al., 2019 ). Additionally, the phylum Actinobacteria has been shown to dominate in the pak choi rhizosphere compared with the bulk soil with or without Se application ( Cai et al., 2019 ). In addition, we showed that the phylum Chloroflexi significantly depleted in the rhizosphere of maize, rice, vegetables, and woody, while enriched in that of herbaceous plants ( \n Figure 6 \n ). This is in agreement with a previous study reporting that the relative abundance of Chloroflexi increased from 2.7% to 8.0% in the rhizosphere compared to the bulk soil across 19 herbaceous plants ( Dawson et al., 2017 ). We found that the phyla Firmicutes significantly enriched in the rhizosphere of maize and rice, while depleted in those of herbaceous, woody plants, and other crops. This is in line with previous studies observing that the phylum Firmicutes significantly increased in the rhizosphere compared with the bulk soil in maize fields at different rice growth stages ( de Araujo et al., 2019 ; Li et al., 2019 ). Similarly, the abundance of Verrucomicrobia revealed opposite trends between the rhizosphere of maize and herbaceous plants ( \n Figure 7 \n ), which was greatly observed in previous studies ( Coleman-Derr et al., 2016 ; Dawson et al., 2017 ; Yang et al., 2017 ; Visioli et al., 2018 ; Wang et al., 2020 ). Additionally, the phyla Ascomycota and Basidiomycota were the dominant fungal communities having distinct responses to rhizosphere depending on plant species ( \n Figure 8 \n ), indicating that plant species differentiate their root microbiota in a species-specific manner ( Berg and Smalla, 2009 ; Aira et al., 2010 ; Dawson et al., 2017 ). Such as, Ascomycota had a higher relative abundance in the rhizosphere of maize. In contrast, bulk soils had a higher abundance of Basidiomycota ( Philippot et al., 2013 ). Commonly, plant species determine the structure of the rhizosphere soil microbial community as follows: firstly, the soil layer surrounding the roots promotes the growth of organotrophic microorganisms and initiates a shift in the soil microbiome through rhizodeposits and root cell wall features ( Bulgarelli et al., 2013 ); secondly, the selection process that depends on the host genotype occurs close to the root surface ( Reinhold-Hurek et al., 2015 ), fine-tuning the community profiles that thrive on the rhizoplane. Overall, the phyla Proteobacteria and Bacteroidetes are considered r-strategists that enriched in rhizosphere across all plant species, while Acidobacteria, Gemmatimonadete, Nitrospirae, and Planctomycetes are considered as K-strategists that depleted in rhizosphere across all plant species. Especially, Actinobacteria, Firmicutes, Chloroflexi, and Verrucomicrobia were selected in a species-specific manner from various plant species, thus revealing divergent abundance among different plants."
} | 5,456 |
37484356 | PMC10360604 | pmc | 8,060 | {
"abstract": "Most worldwide policy frameworks, including the United Nations Sustainable Development Goals, highlight soil as a key non-renewable natural resource which should be rigorously preserved to achieve long-term global sustainability. Although some soil is naturally enriched with heavy metals (HMs), a series of anthropogenic activities are known to contribute to their redistribution, which may entail potentially harmful environmental and/or human health effects if certain concentrations are exceeded. If this occurs, the implementation of rehabilitation strategies is highly recommended. Although there are many publications dealing with the elimination of HMs using different methodologies, most of those works have been done in laboratories and there are not many comprehensive reviews about the results obtained under field conditions. Throughout this review, we examine the different methodologies that have been used in real scenarios and, based on representative case studies, we present the evolution and outcomes of the remediation strategies applied in real soil-contamination events where legacies of past metal mining activities or mine spills have posed a serious threat for soil conservation. So far, the best efficiencies at field-scale have been reported when using combined strategies such as physical containment and assisted-phytoremediation. We have also introduced the emerging problem of the heavy metal contamination of agricultural soils and the different strategies implemented to tackle this problem. Although remediation techniques used in real scenarios have not changed much in the last decades, there are also encouraging facts for the advances in this field. Thus, a growing number of mining companies publicise in their webpages their soil remediation strategies and efforts; moreover, the number of scientific publications about innovative highly-efficient and environmental-friendly methods is also increasing. In any case, better cooperation between scientists and other soil-related stakeholders is still required to improve remediation performance.",
"conclusion": "6 Conclusions Despite the current trend to develop sustainable mining and agricultural practices, HM contamination of soils is still a huge problem affecting soil health. Although ecosystems are known to have great resilience to external alterations, the natural attenuation processes are usually very slow [ 273 ]; therefore, implementing environmentally sustainable remediation strategies for soil affected with high concentrations of HMs is still a necessity. All the examples summarized here reveal the complexity of using standard protocols for the remediation of soils contaminated with HMs. In highly contaminated environments, usually related to mining sites, and if economic constraints allow it, physical containment in combination with assisted-phytoremediation have been demonstrated to be the best approach for environmental restoration. Difficulties associated with the topography of these mining areas, the vast area to be remediated, economic constraints, and, sometimes, the need to take urgent decisions (i.e. after spills), have made difficult the field application of some of the innovative remedial techniques that have shown good results in the laboratory after huge research efforts. In agricultural soils, the problem of HM contamination has been only recently acknowledged, and thus, the optimal management and remedial strategies are still being investigated. So far, several approaches have been tested and discussed. In the case that agricultural exploitation must be preserved during remediation actions, an approach combining different management and treatment possibilities is expected to reduce risks for a safe use of polluted agricultural lands. Nevertheless, in all cases, a constant eco-toxicological monitoring programme is essential, and cultivation should not be allowed unless intensive and periodic toxicity tests demonstrate the safety of the crops for consumption. Further research is clearly necessary to optimize the existing remedial approaches by reducing their duration and enhancing their applicability, as well as implementing new efficient and cost-effective treatments such as promising nanotechnology-based methods. These promising innovative approaches, successfully tested at laboratory level, need to be validated in the field to make them effectively applicable (from a technical and economical point of view) in the medium and long term. Phytomining or the use of biomass from phytoremediated areas for bio-energy production could help to support the costs of the remediation, however, none of these options have so far been extensively used or developed by industry.",
"introduction": "1 Introduction Soil is a non-renewable natural resource which can be considered as the most essential component of terrestrial ecosystems. Unfortunately, soil is also a major sink for pollutants of different nature like heavy metals (HMs), which are persistent contaminants since they can neither be degraded nor destroyed. These elements occur naturally in the Earth's crust in various forms of the solid phase of soils and sediments and also dissolved in water. Low concentrations of several HMs, i.e. iron (Fe), copper (Cu), cobalt (Co), zinc (Zn), nickel (Ni), manganese (Mn), selenium (Se) and molybdenum (Mo) are necessary for metabolic activity, whilst high concentrations are toxic for humans, plants and microorganisms. Other HMs, such as silver (Ag), arsenic (As), cadmium (Cd), lead (Pb), mercury (Hg) and chromium (Cr (VI) ) do not have a known biological function and may provoke serious toxic and carcinogenic effects, even at low concentrations, and thus, they are amongst the priority metals for public health concern [ 1 ]. The most common hazards for humans related to soil contaminated with HMs include direct inhalation of particulate matter, dust or aerosols, and ingestion of contaminated water or vegetables [ 2 , 3 , 4 ]. The toxicity of HMs in soil does not only depend on their total concentration, but also on the bioavailable fraction. This bioavailability depends on numerous factors such as soil pH, organic matter content, temperature, etc. [ 5 ]. With all these considerations, it is not surprising that threshold values for HM concentrations in soil are difficult to evaluate [ 6 ]. As an example, in the mainland of China, the limit for Pb in agricultural soil is ≤ 250 mg kg −1 (pH < 6.5), ≤300 mg kg −1 (pH 6.5–7.5) and ≤350 mg kg −1 (pH > 7.5). In many cases, the authorities establish different thresholds for HM depending on the soil use, with more restrictive levels in the case of agricultural soil [ 7 ]. Regulatory concentrations of toxic metals in agricultural soil differ amongst countries; e.g., the limit for Pb is ≤ 300 mg kg −1 in Australia, ≤70 mg kg −1 in Canada, or ≤200 mg kg −1 in the European Union. Some soils are naturally enriched in HMs; however, certain anthropogenic activities contribute to the redistribution of HMs, generating relevant environmental and/or human health risks when exceeding certain concentration levels [ 8 , 9 , 10 , 11 , 12 , 1 ]. Mining activities and mineral processing are sources of large volumes of metal-rich waste materials which generate large extensions of mine tailings and huge volume sludge dams ( Fig. 1 ). Atmospheric deposition of dust emitted during mining exploitation, industrial production, and motor vehicle usage, as well as abandoned contaminated bare soils are other important sources of contaminants [ 13 , 14 ]. Although, lately, mining industry tends to enhance its production rates by using safer and more efficient production methods for reconciling the increase in metal demand (as a result of both a growing world population and potential higher per-capita requirements) with safety [ 15 , 16 ], contamination episodes are inevitable. Another significant anthropogenic source of HMs in agricultural soil is related with certain agronomic practices such as the long-term application of pesticides, fertilizers or irrigation with wastewaters, among others ( Fig. 1 ). Plants acquire metals from soil for their normal development, however, because of the lack of specificity of the uptake mechanisms, when growing in contaminated substrates, they may incorporate toxic concentrations of essential and non-essential HMs [ 17 ]. Contamination can also reach plant aerial tissues when the HMs are deposited directly on above ground biomass. As plants are the first compartment of the terrestrial food chain, HM content in plants should be monitored and minimized as soon as possible [ 18 , 7 ]. Fig. 1 Schematic representation of the main sources of anthropogenic HM contamination; mining activities generate residues that are in many occasions accumulated in ponds. During these mining activities, in abandoned mines or because of accidents, these HM can be spread by water or air, affecting the nearby areas. Agricultural processes, such as mechanical management, and use of chemical fertilizers, animal manure, or contaminated wastewaters, are also sources of contamination. The main remedial actions that have been demonstrated their utility at large scale are indicated in the lower part of the figure. Fig. 1 There are more than 10 million sites with polluted soil reported worldwide, with more than 50% of them contaminated with HMs and/or metalloids. In Europe, there are 2.8 million sites potentially contaminated with HMs; in China, 19% of the agricultural soil contains harmful pollutants and in India, 80% of the contaminated soil has anthropogenic origins in the states of Maharashtra, Gujarat, and Telangana [ 19 , 20 , 21 ]. The economic impact of HM pollution worldwide has been estimated at more than US $10 billion per year [ 13 ]. The cost and duration of soil remediation are technique-dependent and site-specific, but it has been estimated to be up to $500 ton −1 soil and 15 years [ 6 ]. Given the global increase in human population, and thus, the need to maintain soil potential and a high quality food and fiber production in the long term [ 22 ], the application of occasional or continuous remedial actions are clearly recommended. In general, the treatments applied to HM contaminated soil aim to reduce the metal fractions of the soil (total and/or available) and to diminish its transfer rate to edible plant parts, as well as to improve soil structural stability to reduce erosion [ 23 , 24 , 25 ] . Amongst the remediation techniques available, those based on biological methods are generating great interest as demonstrated by the high number of scientific publications in the area [ 26 ]. However, bioremediation practices in real scenarios have not generally been well documented from the scientific point of view. Fortunately, industries, politicians and citizens are increasingly aware of the environmental risks and implementation of safety practices are commonly reported on the web pages of many industrial companies. This review covers information on remediation strategies of HM-contaminated soil in real scenarios, based on representative case studies that, at least to some degree, have been scientifically reported. We have also reviewed few cases of remediation on agricultural fields, although, as HM contamination of agricultural areas is an emerging problem, not many open-field experiences have been reported in scientific literature so far. Finally, we present several perspectives for this field in a sustainable development context."
} | 2,877 |
24463066 | null | s2 | 8,061 | {
"abstract": "Many biomaterials constructed today are complex chemical structures that incorporate biologically active components derived from nature, but the field can still be said to be in its infancy. The need for materials that bring sophisticated properties of structure, dynamics and function to medical and non-medical applications will only grow. Increasing appreciation of the functionality of biological systems has caused biomaterials researchers to consider nature for design inspiration, and many examples exist of the use of biomolecular motifs. Yet evolution, nature's only engine for the creation of new designs, has been largely ignored by the biomaterials community. Molecular evolution is an emerging tool that enables one to apply nature's engineering principles to non-natural situations using variation and selection. The purpose of this review is to highlight the most recent advances in the use of molecular evolution in synthetic biology applications for biomaterial engineering, and to discuss some of the areas in which this approach may be successfully applied in the future."
} | 272 |
23630537 | PMC3633777 | pmc | 8,062 | {
"abstract": "Ectomycorrhizas (EcM) are important for soil exploration and thereby may shape belowground interactions of roots. We investigated the composition and spatial structures of EcM assemblages in relation to host genotype in an old-growth, monospecific beech ( Fagus sylvatica ) forest. We hypothesized that neighboring roots of different beech individuals are colonized by similar EcM assemblages if host genotype had no influence on the fungal colonization and that the similarity would decrease with increasing distance of the sampling points. The alternative was that the EcM species showed preferences for distinct beech genotypes resulting in intraspecific variation of EcM-host assemblages. EcM species identities, abundance and exploration type as well as the genotypes of the colonized roots were determined in each sampling unit of a 1 L soil core ( r = 0.04 m, depth 0.2 m). The Morisita-Horn similarity indices (MHSI) based on EcM species abundance and multiple community comparisons were calculated. No pronounced variation of MHSI with increasing distances of the sampling points within a plot was found, but variations between plots. Very high similarities and no between plot variation were found for MHSI based on EcM exploration types suggesting homogenous soil foraging in this ecosystem. The EcM community on different root genotypes in the same soil core exhibited high similarity, whereas the EcM communities on the root of the same tree genotype in different soil cores were significantly dissimilar. This finding suggests that spatial structuring of EcM assemblages occurs within the root system of an individual. This may constitute a novel, yet unknown mechanism ensuring colonization by a diverse EcM community of the roots of a given host individual.",
"introduction": "Introduction In Central Europe, beech ( Fagus sylvatica ) is a dominant, ecologically, and economically important tree species (Ellenberg and Strutt, 2009 ). In mono- and hetero-specific forests roots compete for limited resources of water and nutrients (Bobowski et al., 1999 ; Jackson et al., 1999 ; Linder et al., 2000 ; Brunner et al., 2001 ; Hölscher et al., 2002 ; Meinen et al., 2009a , b ). In mixtures beech roots were often the superior competitor compared with other tree species (Schmid and Kazda, 2002 ; Bolte and Villanueva, 2006 ; Rewald and Leuschner, 2009 ). With the advent of molecular techniques, genotyping of tree individuals of the same species became possible and was applied to study the intraspecific patterns of root soil occupation (Brunner et al., 2004 ; Lang et al., 2010 ). Genotyping of beech roots revealed no evidence for competition of tree individuals for soil exploration (Lang et al., 2010 ). However, nutrient uptake by beech roots is primarily achieved by ectomycorrhizal (EcM) fungi, which colonize the root tip and form a new compound organ, the EcM. EcM enwrap the root tip by a mantle-like structure from which hyphae emanate into the soil. Thereby, EcM enlarge the surface for soil exploration and can overcome nutrient depletion zones (Cairney, 2011 ). Beech trees form EcM with a large number of different fungal species (Buée et al., 2005 ; Pena et al., 2010 ; Lang et al., 2011 ). Functional traits for nutrient acquisition vary among different EcM species including biochemical and morphological features such as exudation of organic acids for nutrient solubilization, exudation of hydrolytic and oxidative enzymes as well as different hyphal lengths which enable different EcM to forage in different soil volumes (Courty et al., 2010 ; McGuire et al., 2010 ; Plassard et al., 2011 ; Pritsch and Garbaye, 2011 ; Agerer et al., 2012 ; Weigt et al., 2012 ; Pena et al., 2013 ). If different EcM species provided different benefits, we expect that neutral behavior for resource competition in mono-specific beech forests is mediated by mixed EM fungal assemblages with no preference for individual trees. However, there is now evidence that the ability for mycorrhization with distinct fungal species is under genetic control of the host (Peterson and Bradbury, 1998 ). For example, greenhouse studies with Scots pines from different seed sources and with different Norway spruces clones showed strong intraspecific host differences in colonization and EcM species composition (Leski et al., 2010 ; Velmala et al., 2012 ). Mycorrhizal colonization of poplar hybrids and their parents varied strongly and affected EcM enzymatic activities suggesting a genetic basis for plant-EcM interactions (Tagu et al., 2001 ; Courty et al., 2011 ). Furthermore, in a poplar plantation differences in EcM community composition were found among different transgenic poplars modified in lignification enzymes and also among different P . x euramericana clones (Danielsen et al., 2013 ). Because of the significance of EcM for plant nutrition and ecosystem functioning, it is important to understand the links between inter- and intraspecific plant and mycorrhizal diversity. The aim of our study was to investigate the relationship between EcM fungal assemblages and the roots of individual beech trees. Since beech propagates typically by seedlings, each tree is usually a distinct genotype. In mono-specific forests roots of a given individual are strongly intermingled with those of the neighboring trees, even close to the stem the individual (Lang et al., 2010 ). Therefore, analyses of the relationship between roots of distinct trees and their mycorrhizal assemblage require root genotyping and fungal species identification of that specific root. We used this strategy to test our working hypothesis that the EcM species composition of different neighboring root genotypes is more similar than that of the same genotype sampled at different positions. The alternative was that the EcM species showed preferences for distinct beech genotypes resulting in intraspecific variation of host fungal assemblages. For the purpose of this study we defined the roots in our sampling unit of a 1L-soil core ( r = 0.04 m, depth 0.2 m) as neighboring roots (small spatial scale) compared with roots in different soil cores collected at distances of 1–9 m within a plot and those collected in different plots at distances of about 40 m. We analyzed the EcM species abundances and identities on all root tips in each soil core and determined the genotypes of colonized roots. We used these analyses to describe the spatial pattern of EcM diversity and to investigate the similarities of EcM assemblages on roots of different beech genotypes at small and larger spatial scales.",
"discussion": "Discussion In recent years considerable efforts have been made to describe and interpret the ecological significance of spatial patterns of EcM (O’Hanlon, 2012 ). A key challenge is to find out whether predictable relationships exist between inter- and intraspecific plant and mycorrhizal fungal diversity, which may be key factors in understanding ecosystem functioning (Johnson et al., 2012 ). The present study contributes to this question by linking EcM species patterns to beech genotypes with a spatial resolution of about 0.04–9 m. The fungal community composition on the beech roots of our study and their general structures with few dominant and many scarce species are typical for Fagaceae forests (Buée et al., 2005 ; Courty et al., 2005 ; Lang and Polle, 2011 ; Lang et al., 2011 ). Because we found almost complete colonization of vital root tips with EcM, all nutrients taken up by a beech tree must have passed the EcM. Therefore, EcM are expected to play an important role in the distribution of nutrients between conspecific neighbor trees and may lead to asymmetric competition, if the EcM species differed in functions and preferences for distinct genotypes. Data regarding functional classifications of EcM are still incomplete. EcM fungi exude different exoenzymes to mobilize nutrient resources (Cairney, 2011 ; Plassard et al., 2011 ; Pritsch and Garbaye, 2011 ; Hobbie and Högberg, 2012 ; Habib et al., 2013 ), but groupings for these traits are still lacking because of strong variations of the enzyme activities with their biotic and abiotic environment (Courty et al., 2008 ). Currently, the most frequently used classification system assigns EcM fungi according to their hyphal morphology such as lengths, densities, and surface properties to different soil exploration types, which reflect spatial differences for nutrient absorption (Agerer, 2001 ). In our study the abundant EcM include contact ( R. chloroides, T. sublilacina ), short distance ( C. geophilum, Genea hispidula ) and medium distance ( C. christata, L. subdulcis, C. anomalus ) soil exploration types, with a potential reach of up to 16 cm per cm EcM length (Agerer, 2001 ; Agerer et al., 2012 ; Weigt et al., 2012 ). Thus, the majority of EcM species can forage for nutrients beyond the dimensions of the soil core. A yet larger outreach is achieved by long distance rhizomorph-forming fungi with an exploration potential >400 cm per cm of EcM length (Agerer et al., 2012 ), which colonized, however, only a small fraction of the root tips in our study (about 1%, X. pruinatus ). In other forest communities the abundance of rhizomorphic exploration types was found to be very high (Heinonsalo et al., 2007 ). Here, the similarity of EcM species among the plots used in our study was only moderate, but the similarity based on exploration types was very high. This finding suggests that there were no major differences between the plots with respect to soil foraging by EcM. Previous studies in a pine forest have shown that EcM communities were highly similar at scales <3.4 m (Pickles et al., 2012 ). In our study we also found high similarities of EcM communities within the plots, but no significant differences between adjacent (ca. 1 m) and more distant (ca. 9 m) sampling points. Fine scale analyses of EcM at the cm-scale showed that some fungi, e.g., Clavulina sp. and Cortinarius sp., which were also present in our study, can form mycelial and EcM patches, whereas this was not the case for C. geophilium (Genney et al., 2006 ; Pickles et al., 2010 ). Clusters for Cortinarius and other fungal species ( Tomentella, Piloderma ) were also detected on oak (Gebhardt et al., 2009 ). The formation of clusters indicates non-random spatial structuring of the EcM communities. It has been suggested that interspecific competition or priority effects could lead to spatial partitioning of fungal species on the root system (Pickles et al., 2012 ). Another possibility, which was addressed in our study, is that intraspecific host diversity may lead to structuring of the fungal assemblages. Since strong host preferences of EcM species have been found in mixtures of beech with other deciduous tree species (Lang et al., 2011 ) and effects of the host genotype were reported under experimental conditions (Tagu et al., 2001 ; Leski et al., 2010 ; Courty et al., 2011 ; Danielsen et al., 2013 ), it is clear that links exist between the fungal assemblage and the host genotype. However, in the present investigation we found no evidence for discernible EcM communities on distinct beech genotypes. One reason may be that the genetic structure of the genotypes studied in this old-growth unmanaged stand might have been relatively similar because the trees were established by natural regeneration and significant family structures were found in the plot (Rajendra, 2011 ). To further address the question of interactions between host genotype and fungal assemblages, field studies with different beech ecotypes/populations will be required. The most striking finding of our study was that the similarity of EcM communities of different beech genotypes within a soil core was almost twice higher than for same genotype in different soil cores. Because the dimensions of the soil core were smaller than the radius of most fungal hyphae, it is possible that the same fungal genotype colonized neighboring roots of different host trees in the same soil core. Although we have not determined fungal genets, this assumption is not unreasonable because others have shown that fungal genets connect hetero- as well as conspecific neighbors (Curlevski et al., 2009 ; Beiler et al., 2010 ). The connectivity was especially strong for old, dominant individuals, where one individual was connected with as many as more than 40 other conspecific trees and could cover distances of up to 20 m (Beiler et al., 2010 ). Mycorrhizal networks may facilitate resource transfer within the fungal web and between, thereby, foster the establishment of seedlings with access to the common mycorrhizal network (Teste and Simard, 2008 ). In our study the high dissimilarity of fungal assemblages at roots of the same genotypes at spatial distances of some meters was unexpected because the overall similarities of fungal communities in the soil cores of plot were not significantly different. This is an exciting finding because it suggests that spatial structuring occurs within the root system of an individual. Spatial segregation of different EcM species – mediated by unknown host mechanisms – can ensure colonization by a diverse EcM community on the roots of a given host genotype. Thereby, asymmetric competition between conspecific neighbors can be avoided. We are aware that this suggestion is preliminary because our study includes only few individuals. However, it opens a new avenue to look at spatial structuring of EcM communities."
} | 3,391 |
25584120 | null | s2 | 8,063 | {
"abstract": "In this paper we describe an FPGA-based platform for high-performance and low-power simulation of neural microcircuits composed from integrate-and-fire (IAF) neurons. Based on high-level synthesis, our platform uses design templates to map hierarchies of neuron model to logic fabrics. This approach bypasses high design complexity and enables easy optimization and design space exploration. We demonstrate the benefits of our platform by simulating a variety of neural microcircuits that perform "
} | 124 |
20028097 | null | s2 | 8,065 | {
"abstract": "Self-assembly represents a robust and powerful paradigm for the bottom-up construction of nanostructures. Templated condensation of silica precursors on self-assembled nanoscale peptide fibrils with various surface functionalities can be used to mimic biosilicification. This template-defined approach toward biomineralization was utilized for the controlled fabrication of 3D hybrid nanostructures. The peptides MAX1 and MAX8 used herein form networks consisting of interconnected, self-assembled beta-sheet fibrils. We report a study on the structure--property relationship of self-assembled peptide hydrogels where mineralization of individual fibrils through sol--gel chemistry was achieved. The nanostructure and consequent mechanical characteristics of these hybrid networks can be modulated by changing the stoichiometric parameters of the sol--gel process. The physical characterization of the hybrid networks via electron microscopy and small-angle scattering is detailed and correlated with changes in the network mechanical behavior. The resultant high fidelity templating process suggests that the peptide substrate can be used to template the coating of other functional inorganic materials."
} | 301 |
27739484 | PMC5064364 | pmc | 8,066 | {
"abstract": "Here, we report a stable and predictable aero-elastic motion in the flow-driven energy harvester, which is different from flapping and vortex-induced-vibration (VIV). A unified theoretical frame work that describes the flutter phenomenon observed in both “stiff” and “flexible” materials for flow driven energy harvester was presented in this work. We prove flutter in both types of materials is the results of the coupled effects of torsional and bending modes. Compared to “stiff” materials, which has a flow velocity-independent flutter frequency, flexible material presents a flutter frequency that almost linearly scales with the flow velocity. Specific to “flexible” materials, pre-stress modulates the frequency range in which flutter occurs. It is experimentally observed that a double-clamped “flexible” piezoelectric P(VDF-TrFE) thin belt, when driven into the flutter state, yields a 1,000 times increase in the output voltage compared to that of the non-fluttered state. At a fixed flow velocity, increase in pre-stress level of the P(VDF-TrFE) thin belt up-shifts the flutter frequency. In addition, this work allows the rational design of flexible piezoelectric devices, including flow-driven energy harvester, triboelectric energy harvester, and self-powered wireless flow speed sensor.",
"conclusion": "Conclusion A unified theoretical frame work that describes the flutter of both “stiff” and “flexible” materials are established and experimentally validated in this study. A steep rise in vibration amplitude of double-clamped belt characterizes the flutter phenomenon observed in both materials, due to the coupled effects of the bending and torsional modes of the belt. The observation that higher incoming air velocity induces higher vibration amplitude for both materials also agrees well with the unified analytical model. The flutter frequency of “stiff” materials is found independent of the air flow velocity. Catastrophic failures were observed for “stiff” materials when air flow exceeds the rate at which flutter first occurs. In comparison, no such failure is observed for “flexible” material in the flutter regime, allows full utilization of the maximum displacement associated with flutter. Flutter frequency scales near linearly with flow velocity for the “flexible” material. The frequency range over which flutter occurs can be modulated by pre-stress. “Flexible” piezoelectric vibrating belt employing flutter phenomenon can be rationally designed as a sensing element to detect and monitor the pneumatic flow velocity in a flow field. Tuning the frequency through pre-stress of the “flexible” piezoelectric belt also allows fitting the energy harvester to the power management IC for maximum energy harvesting efficiency.",
"discussion": "Discussion To further illustrate the occurrence of fluttering and its characteristics, theory was developed and employed to predict the onset velocity and fluttering frequency at different flow rate in the next section. The distinct behaviors for belts based on different materials, which is associated to the correlation between flutter frequency and the deformation amplitude, is also discussed in depth herein. As known, flutter is a complex combination of bending and torsional vibration modes which cross-feed each other, resulting in divergent vibration amplitude 11 . It is characterized by an onset air flow velocity U onset , below which flutter does not occur. In addition, flutter normally occurs when natural torsion frequency f α 0 is higher than natural bending frequency f h 0 , and the flutter frequency f F is slightly lower than the natural torsion frequency 11 12 13 14 (see §2 of Supplementary Information ). For natural vibration of “stiff” belts which is governed by stiffness, the theoretical model has already been established well 15 16 ; and the theoretical model for bending vibration of pre-stressed “flexible” belts/string is also widely used under conditions with small amplitude 17 18 and large amplitude 19 20 21 22 23 . However, there is a lack of model for torsional motion of “flexible” belts with pre-stress and finite vibration amplitude are missing. So, it is important to establish an unified model for the bending and torsional vibrations for “stiff” and “flexible” belts with pre-stress and finite vibration amplitude which is possibly observed in the real world applications (see §2 of Supplementary Information ): where x is along the flow direction, z is along the axis of beam or belt, y is the normal direction of the belt surface, and t is time. v is the deformation of the belt along the y direction, and φ is the torsional angle of each element of the belt. The following are the belt materials properties. I x is the second axial moment of area about the x-direction. E and G are the Young’s and shear modules, T is the axial internal force, and m is the mass per unit length, J is the torsional constant (stiffness), K m is the radius of gyration, A is the cross section area (see §2 of Supplementary Information ). Accordingly, the natural bending and torsion frequency for belts with different material under different vibrating situation can be analyzed as following. Especially, for the double clamped belts of “stiff” material, the axial internal force T 0 and the vibration amplitude C v are small due to its high stiffness, leading to a result that the second term and the third (nonlinear) term in Eqs (1 ) and ( 2 ) are relatively small. On the other hand, for the double clamped belts of “flexible” material, the stiffness of the material is much smaller than the effect of axial internal force T 0 , thus the first terms in Eqs (1 ) and ( 2 ) are ignorable, while the third terms (nonlinear) are un-neglectable when bending amplitude C v is large. So theoretically, it can be summarized that the natural frequency of “stiff” material is almost constant, while the frequency of “flexible” material increases with increasing bending amplitude, which is presented in Table 1 (see Eqs S1.1 and S1.2 of Supplementary Information ). To verify the above theory about flutter phenomena for long and thin belt (length ≫ width ≫ thickness) in air flow, the experimental results are studied in details and depth. First, the linear flutter theory is validated by examining the motion of “Stiff” material belt which is easy to surpass the material mechanical limit (fracture strength) at high air flow velocity due to the ultra-low toughness and stress concentration at the belt’s ends. It is found in the experiment that the maximum bending deformation of AlN/Si belt is around 0.015 mm (see §3 of Supplementary Information ) before it cracks, corresponding to 1–2 degrees of maximum torsion (see Eq. S1.26 of Supplementary Information ). Within such small bending deformation magnitude (≈0.01 mm, see §3 of Supplementary Information ), the natural vibration frequencies for “stiff” belt almost remain as constants when bending deformation is increasing (see §4 of Supplementary Information ). Thus, the linear Euler-Bernoulli theory for bending and St. Venant theory for torsion 15 16 . are valid for fluttering “stiff” material micro belts. Based on Selberg and Theodorsen’s theories that flutter occurs when bending and torsional modes are “self-feeding”, pairs of bending and torsional modes are analyzed theoretically to investigated the possibility of flutter (see §2 of Supplementary Information ). It is theoretically revealed in Fig. 6(a) that flutter with 3rd order bending (10.128 kHz, based on the finite element method simulation results by ABAQUS software) with 1st order torsional (13.410 kHz) modes becomes onset when air velocity is larger than 75 m/s, which is defined as U onset . The experimental measurement of highly sensitive Laser-Doppler technique (MSA-500 Micro System Analyzer) shows very obvious existence of such two vibration modes for fluttering thin belt in inflow air, which is presented together with the finite element method simulation results in Fig. 6(b) . Figure 7(a) shows the theoretically predicted dynamic behavior together with the measured phenomenon for the double-clamped “stiff” material AlN/Si based micro-belt, which is investigated through monitoring the piezoelectric voltage output of the belt. Experimentally, low air flow velocity does not initiate efficient vibration of the double-clamped “stiff” AlN/Si micro-belt (voltage output is extremely low), but this vibration becomes suddenly periodical and stable when the air flow velocity exceeds a critical value 64 m/s, which agrees very well with the theoretical prediction of flutter onset velocity as 75 m/s. Considering the minor difference of each individual micro belt, the observation that the dominant frequencies of the vibration is almost independent on air velocity as 11.12 kHz quantitatively aligns well to the predicted flutter frequency which remains relatively constant as the air flow velocity increases above U onset . In contrast of “stiff” material AlN/Si, the “flexible” material has relatively low stiffness but its high toughness ensures it to bend and twist with large deformation. So the deformation can increase up with the air velocity until the angle of attack roughly reaches the stall angle (normally 30–45 degrees for thin film plate 8 24 ) due to the lack of aerodynamic lift and torque. As seen from the governing equations of vibration for belts (see Eqs 1 and 2 ), the bending deformation has nonlinear effects on the natural vibration frequency when the deformation amplitude C v is large where linear theories 15 16 are invalid. In contrast of “stiff” material, the vibration of “flexible” material is dominated by the internal axial stress within the belt. As known, the higher the internal axial pre-stretching force T 0 is, the higher the vibration frequency (see Table 1 ) will be; which can be found in adjustment of strings of piano and violin. Similarly, in the current study, large bending deformation elongates the axial length of the belt by an extra strain , which increases the total axial force up to . Thus, it can be implied that the increase in both pre-stress and bending deformation amplitude C v rises the equivalent effective internal axial force , then resulting in a raise in the natural vibration frequency. Finally, the increase in natural vibration frequency induces higher flutter frequency, which is almost determined by the torsional frequency. A detailed numerical simulation (see §4 of Supplementary Information ) was conducted to quantitatively evaluate this nonlinear effect on flutter frequency of “flexible” P(VDF-TrFE) micro belt in the current experiment with the bending deformation amplitude ranging within 0–0.4 mm (estimated based on voltage output, see §3 of Supplementary Information ). The theoretically predicted flutter frequency of P(VDF-TrFE) micro belt is presented in Fig. 7(b) together with experimental measurement against the incoming air velocity and bending deformation amplitude C v at two different axial pre-stretching force T 0 = constant ≈ 0.07 N and 0.21 N. Such bending deformation (up to 0.4 mm) is magnified compared to that of “stiff” material as 0.015 mm (see §3 of Supplementary Information ). The theoretical prediction shows that the flutter frequency increases from 3300 Hz to 3800 Hz and 5050 Hz to 5375 Hz with the increasing bending deformation amplitude (incoming air velocity) for less and more pre-stressed “flexible” micro belt, which agrees well with the experimental finding. Furthermore, the increasing pre-stress makes the flutter frequency of “flexible” belt to become higher at the same air velocity, which is also the modulation effect predicted by the theory. Thus, it can be concluded that the flutter frequency of “flexible” material is sensitive to the air velocity, and the pre-stress can be utilized to modulate the flutter frequency."
} | 2,985 |
24348093 | PMC3852633 | pmc | 8,068 | {
"abstract": "The Archaea represent the so-called Third Domain of life, which has evolved in parallel with the Bacteria and which is implicated to have played a pivotal role in the emergence of the eukaryotic domain of life. Recent progress in genomic sequencing technologies and cultivation-independent methods has started to unearth a plethora of data of novel, uncultivated archaeal lineages. Here, we review how the availability of such genomic data has revealed several important insights into the diversity, ecological relevance, metabolic capacity, and the origin and evolution of the archaeal domain of life.",
"introduction": "1. Introduction The description of the three (cellular) domains of life—Eukarya, Bacteria, and Archaea—by Carl Woese and George Fox [ 1 ] represents a milestone in the modern era of microbiology. In particular, using phylogenetic reconstructions of the small-subunit (16S or 18S) ribosomal RNA gene, Woese discovered that microscopically indistinguishable prokaryotes are not a homogeneous assemblage but are comprised of two fundamentally different groups of organisms: Eubacteria (later Bacteria) on one side and an additional life form referred to as Archaebacteria (later Archaea) on the other side [ 1 ]. Though not immediately accepted by the scientific community, this finding was early on supported by Wolfram Zillig through his studies on DNA-dependent RNA polymerases, as well as by Otto Kandler investigating “bacterial” cell walls [ 2 ]. Indeed, a subset of prokaryotic organisms subsequently assigned to Archaea was found to harbor DNA-dependent RNA polymerases that bore more similarity to those of eukaryotes, and to contain proteinaceous cell walls that lack peptidoglycan as well as cell membranes composed of L-glycerol ether lipids with isoprenoid chains instead of D-glycerol ester lipids with fatty acid chains [ 3 – 6 ]. Since then, further investigation of cellular characteristics of archaea has revealed that this domain of life contains eukaryotic-like information-processing machineries [ 7 – 14 ]. These findings were later supported by genome sequences and comparative analyses of genes coding for replication, transcription, and translation machineries as well as by protein crystal structures [ 15 – 21 ]. Additionally, some archaeal lineages were shown to contain homologs of eukaryotic cell division and cytoskeleton genes as well as histones and seem to express a chromatin architecture similar to eukaryotes [ 22 – 28 ]. In contrast to information-processing and cell division genes, archaeal operational systems (energy metabolism, biosynthesis pathways, and regulation) often appear to be more closely related to bacteria [ 29 ]. Based on phylogenetic reconstructions of the evolutionary history of 16S rRNA genes, the domain Archaea was originally divided into two major phyla: the Euryarchaeota and Crenarchaeota [ 30 ], which were separated by a deep split and thought to comprise only extremophilic (thermophilic, halophilic, and acidophilic) as well as methanogenic organisms. However, novel culture-independent and high-throughput sequencing techniques have recently uncovered a huge diversity of so far uncharacterized microorganisms on Earth as well as the ubiquitous occurrence of archaeal species [ 31 – 33 ]. Many of these novel archaeal groups are responsible for important ecological processes and are only distantly related to established lineages within Cren- and Euryarchaeota [ 31 , 32 , 34 – 39 ]. For example, the acquisition of genome sequences from novel archaeal representatives has led to the proposal of several additional archaeal phyla (including Nanoarchaeota, Korarchaeota, Thaumarchaeota, Aigarchaeota, and Geoarchaeota) [ 40 – 46 ] and the investigation of uncultivated archaea using single cell genomics has already started to add new insights into the phylogenetic diversity of the Third Domain of life and necessitates the definition of additional lineages of high taxonomic rank including novel potential phyla and superphyla [ 33 , 39 ] (see also below). Furthermore, the investigation of the metabolic potential of these novel organisms has provided fundamentally new insights into major biogeochemical nutrient cycles. Indeed, archaea are now recognized as key players in various biogeochemical processes [ 47 ]. For example, the perception of the global nitrogen cycle has been deeply altered by discovering that the ability to gain energy solely from ammonia was not limited to a few bacteria but also included the ammonia-oxidizing Thaumarchaeota [ 48 , 49 ]. Archaea also appear to play a significant role in the carbon cycle, since, in addition to all known methanogenic organisms on Earth, they also encompass anaerobic methane oxidizing archaea (ANME lineages 1–3) [ 50 ]. The study of archaeal genomes and diversity is also of considerable importance for a better understanding of eukaryotic evolution. Indeed, the discovery of eukaryotic features in archaea [ 10 ] has initiated a new basis for addressing the origin of eukaryotes [ 51 – 54 ]. Interestingly, recent phylogenetic analyses of universal proteins have suggested that eukaryotes might have evolved from a bona fide archaeal lineage that forms a sister-lineage of or a lineage emerging from within the TACK-superphylum comprised of Thaum-, Aig-, Cren-, and Korarchaeota [ 55 – 58 ]. Below we give a contemporary overview of how recent developments in archaeal genomic research have contributed to revealing new insights into the diversity, ecological relevance, metabolic capacity, and the origin and evolution of the archaeal domain of life."
} | 1,398 |
26647299 | PMC4672918 | pmc | 8,070 | {
"abstract": "Bacteria have diverse mechanisms for competition that include biosynthesis of extracellular enzymes and antibiotic metabolites, as well as changes in community physiology, such as biofilm formation or motility. Considered collectively, networks of competitive functions for any organism determine success or failure in competition. How bacteria integrate different mechanisms to optimize competitive fitness is not well studied. Here we study a model competitive interaction between two soil bacteria: Bacillus subtilis and Streptomyces sp. Mg1 ( S . Mg1). On an agar surface, colonies of B . subtilis suffer cellular lysis and progressive degradation caused by S . Mg1 cultured at a distance. We identify the lytic and degradative activity (LDA) as linearmycins, which are produced by S . Mg1 and are sufficient to cause lysis of B . subtilis . We obtained B . subtilis mutants spontaneously resistant to LDA (LDA R ) that have visibly distinctive morphology and spread across the agar surface. Every LDA R mutant identified had a missense mutation in yfiJK , which encodes a previously uncharacterized two-component signaling system. We confirmed that gain-of-function alleles in yfiJK cause a combination of LDA R , changes in colony morphology, and motility. Downstream of yfiJK are the yfiLMN genes, which encode an ATP-binding cassette transporter. We show that yfiLMN genes are necessary for LDA resistance. The developmental phenotypes of LDA R mutants are genetically separable from LDA resistance, suggesting that the two competitive functions are distinct, but regulated by a single two-component system. Our findings suggest that a subpopulation of B . subtilis activate an array of defensive responses to counter lytic stress imposed by competition. Coordinated regulation of development and antibiotic resistance is a streamlined mechanism to promote competitive fitness of bacteria.",
"introduction": "Introduction Bacteria are communal organisms. As such, bacteria have mechanisms to interact with other species that range from cooperative to antagonistic. Antibiotics are a classic example of molecules produced by bacteria that probably function in shaping microbial communities due to their bioactive function, including growth inhibitory and stimulatory activities [ 1 – 4 ]. The study of antibiotics has revealed a great deal about the cellular functions they target, mechanisms of resistance, and uses in treating disease. The traditional approach to discovery of antibiotics typically begins with extraction of metabolites from culture media, followed by direct screening of culture extracts to identify growth inhibitory agents [ 5 ]. While this approach has had tremendous success for antibiotic discovery, it has left great gaps in our understanding of competitive dynamics between bacteria. Approaches to bacterial competition that rely on culture of two or more organisms together are emerging as a powerful tool to discover new bioactive molecules and reimagine mechanisms of competition between diverse species of bacteria [ 6 , 7 ]. For instance, microbial competitive functions include secreted enzymes, type VI secretion systems, and specialized metabolism, including developmental signals and antibiotics [ 1 , 4 , 8 ]. In addition, changes in community functions such as biofilm formation or motility are recognized increasingly as important competitive strategies for bacteria [ 9 , 10 ]. Specialized metabolism and developmental functions are common features among soil bacteria, including the actinomycetes, bacilli, and myxobacteria [ 11 – 17 ]. In these bacteria, antibiotic production and cellular development are often intertwined and co-regulated processes, which is thought to provide fitness benefits to the organisms [ 18 – 20 ]. For example, during typical development Streptomyces species differentiate and develop spores [ 14 ]. During Streptomyces sporulation the substrate mycelium is cannibalized, which is thought to provide the cells with necessary nutrients to complete sporulation [ 21 , 22 ]. Cannibalization of the substrate mycelium is concurrent with production of many antibiotics, which are thought to protect the nutrient resources from opportunistic competitors [ 23 ]. Use of simple, tractable assays of two or more competing bacteria is one approach to identify new specialized metabolites, enzymes, and bacterial functions that determine the outcomes of competitive interactions. Indeed, interaction assays reveal not only growth inhibitory metabolites, but also changes in development and colony morphology that expose abundant and poorly understood survival mechanisms for bacteria. Dynamic patterns of interaction based on models of competition are producing new insights into bacterial competitive mechanisms [ 9 , 18 , 24 – 28 ]. As a model for competitive interactions, we use different species of Bacillus and Streptomyces . This competition model has led to identification of new functions for known molecules, including bacillaene and surfactin [ 18 , 24 ]. In the case of surfactin, a secreted hydrolase was identified from Streptomyces sp. Mg1 ( S . Mg1) and shown to be a resistance mechanism that specifically degrades surfactin and plipastatin produced by Bacillus subtilis [ 25 ]. The current study stems from observing colonies of S . Mg1 and B . subtilis placed side by side on agar media. In this format, cellular lysis occurs along with progressive degradation of the B . subtilis colony [ 29 ]. Previously, imaging mass spectrometry revealed the loss of the polyglutamate component of colony extracellular matrix in the area of lysis, indicating degradation of both cellular and extracellular materials [ 30 , 31 ]. Streptomyces sp. Mg1 encodes production of many specialized metabolites with potential to participate in lysis and degradation [ 32 ]. One gene cluster encodes the biosynthetic enzymes for chalcomycin A, which inhibits the growth of B . subtilis but does not cause lysis and colony degradation [ 29 ]. Here we report both the identification of a lytic degradative activity (LDA) from S . Mg1, as well as a mechanism of resistance to LDA for B . subtilis . We show that resistant mutants of B . subtilis have a complex phenotype, which includes LDA resistance and visible changes in colony morphology and motility. We show the LDA resistance and the changes in colony morphology and motility are genetically separable functions, all regulated by a two-component system of previously unknown function. Our results indicate that a subpopulation of B subtilis cells in a colony trigger a complex mechanism for competitive fitness when challenged by the streptomycete.",
"discussion": "Discussion In this study, we used a two-species culture model of bacterial competition to identify functions that contribute to bacterial competitive fitness. The present study stemmed from an earlier observation of lysis and degradation of B . subtilis colonies when cultured adjacent to S . Mg1 [ 29 ]. Here, we first identified linearmycins, produced by S . Mg1, as the primary cause of progressive lysis and colony degradation. The culture format used for competition revealed small B . subtilis colonies spontaneously resistant to lysis. When isolated, the resistant colonies showed a biofilm-like appearance with increased wrinkled colony morphology and aberrant motility. We sequenced whole genomes of the resistant colonies and identified mutations that confer resistance. Genomic analysis revealed alleles of the yfiJK operon, which encodes a two-component system of previously unknown function. Based on our observations, we define yfiJK as a regulator of yfiLMN , encoding an ABC transporter, and possibly other target genes that govern modes of colony growth and motility ( Fig 9 ). 10.1371/journal.pgen.1005722.g009 Fig 9 Model for YfiJK-LMN functions in LDA resistance and development. LDA is sensed either directly by the ABC transporter YfiLMN, similarly to the ABC transporter BceAB and peptide antibiotics, or indirectly as membrane damage. This signal is transferred to the histidine kinase YfiJ, which then activates YfiK via phosphorylation. YfiK~P then activates the transcription of yfiLMN and likely represses des and yvfRS , leading to LDA resistance, biofilm formation, and motility through an unknown mechanism. These functions promote survival of B . subtilis under competitive stress. The YfiJK system differs structurally and functionally from other TCS that control either antibiotic resistance, such as the BceRS-AB system, or development, such as the DegSU system. Interactions between HKs and ABC transporters are shown with double-headed arrows. Hypothesized interactions of molecules with ABC transporters or membranes are shown with dashed arrows. We show that the LDA resistance is not dependent upon known biofilm-specific functions, suggesting that colony morphology and LDA R are separable processes, unified under YfiJK regulation. Two-component systems are well established as regulators for cellular responses to environmental stresses, including antibiotics [ 74 , 75 ]. The significance of the current work is the use of model interspecies competition to reveal both the agent of aggression, linearmycins, and a multifaceted survival response from genes with no prior functional assignment, yfiJKLMN . Only gain-of-function mutations in yfiJK were identified in this study to cause LDA resistance. The resistance alleles of yfiJK were due to missense mutations causing changes to four regions of YfiJK: (i) the third TM helix in YfiJ, (ii) the cytoplasmic linker between the fifth TM helix and the dimerization and histidine phosphotransfer (DHp) domain in YfiJ, (iii) the C-terminal end of the DHp, and (iv) the regulator domain in YfiK. We hypothesize that each of these amino acid substitutions are responsible for conformational changes in YfiJK, leading to a constitutively active state. A previous study described a similar phenotype caused by point mutations of pmrAB in Pseudomonas aeruginosa . Gain-of-function alleles in pmrB lead to polymyxin B resistance via increased signaling through the histidine kinase [ 76 ]. We also considered an alternative mechanism, wherein point mutations in yfiJK could lead to non-cognate interactions of YfiJ or YfiK and aberrant signal transduction [ 77 ]. However, we view this mechanism as unlikely because only one of the affected residues (L254) lies in the DHp domain, which is predicted to be involved in specificity [ 78 ], and LDA resistance required the presence of the phosphoacceptor residue in the cognate partner. Thus, we conclude that gain-of-function alleles cause LDA resistance and changes in both colony morphology and motility, and that the signaling is specific to YfiJK. Although the specific defects caused by each allele will require further investigation, we note that many of the mutations we observed are responsible for amino acid changes in the cytoplasmic linker of YfiJ. The cytoplasmic linker domain of HKs has been best characterized in periplasmic-sensing histidine kinases. In these kinases, the linker may contain conserved PAS or HAMP domains that are necessary for signal transduction from the sensory machinery to the kinase domains [ 46 , 79 – 81 ]. YfiJ has neither of these conserved domains, suggesting that the short linker in this protein is the sole signal-transducing domain. The mutations in the yfiJ linker, through fixing the protein in activated state, may be very informative for determining the mechanism of signal transduction via the YfiJ intramembrane histidine kinase. Two-component systems are commonly involved in sensing antibiotic and environmental stress [ 74 , 75 ]. Among Firmicutes, a conserved mechanism for resistance to peptide antibiotics pairs genes for two-component systems and ABC transporters [ 56 , 82 , 83 ]. The identification of mutations in yfiJK suggests the cell envelope is the linearmycin target, based on comparison to other TCS-ABC transporter pairs in B . subtilis [ 56 ]. Immediately downstream of yfiJK are three genes, yfiLMN , that are predicted to encode an ABC transporter. We found that when B . subtilis was unable to produce YfiLMN, the colonies were LDA sensitive and failed to develop altered colony morphology, regardless of the presence of a LDA R allele of yfiJK . Furthermore, expression of yfiLMN under a constitutive promoter resulted in LDA resistance, even in the absence of yfiJK . Thus, the YfiLMN transporter is necessary and sufficient for LDA resistance. We hypothesize that YfiLMN may act as an exporter either for linearmycin or for cell envelope remodeling factors that lead to LDA resistance. We used RNA-seq to identify genes that may be regulated by YfiJK. As expected we identified that yfiLMN expression was increased in a LDA R mutant. We also identified yvfRS , encoding an ABC transporter of unknown function, and des as genes downregulated by YfiJK. The des gene encodes a fatty acid desaturase that is responsible for altering membrane fluidity in response to cold shock [ 69 , 70 ]. Intriguingly, B . subtilis strains with des deletions are more susceptible to daptomycin-treatment, potentially due to their altered membrane fluidity [ 84 ]. Antifungal polyenes structurally related to linearmycins target ergosterol in fungal membranes [ 39 – 42 ]. The decreased expression of des in LDA R mutants may contribute to resistance by affecting interactions between linearmycins and the cell membrane. Characterization of the cell envelopes of LDA sensitive and LDA R strains may provide insight into the mechanism of linearmycin-induced lysis. Mutants with LDA R alleles of yfiJK grow as rugose colonies that resemble some aspects of biofilm development on rich media, which does not support traditional biofilm development. We demonstrated that we could functionally divorce this colony morphology phenotype and LDA resistance by expressing yfiLMN constitutively and by introducing deletions of genes specifically required for biofilm development ( epsH , sinR , degU ). In so doing, we found that changes to the biofilm extracellular matrix are not responsible for resistance. LDA resistance may be modulated by specific matrix or cell envelope modifications activated by YfiJK-LMN, but such modifications remain to be identified. Although we found no obvious candidates in our RNA-seq data to explain colony morphological changes, the decreased expression of des or yvfRS may contribute to alterations in colony development. We also observed that LDA R mutants respond to S . Mg1 by inducing motility, whereas wild type B . subtilis colonies are lysed. The pleiotropic phenotypes of yfiJK LDA R alleles differentiate this coupled TCS-ABC transporter system from the BceRS-AB, PsdRS-AB, YxdJK-LM systems in B . subtilis , which appear to be dedicated antibiotic resistance systems [ 56 , 85 – 88 ]. To our knowledge, there are no phenotypes associated with development that have been attributed to these TCS-ABC transporter pairs, suggesting that YfiJK holds a specialized role in providing specific LDA resistance and in activating biofilm development and motility, both of which are known to increase resistance to antimicrobials [ 10 , 60 ]. We propose that activation of YfiJK-LMN promotes competitive fitness of B . subtilis by coupling a specific resistance mechanism (LDA R ) with generalized-resistance that occurs as a consequence of altered development and motility. A recent study using strains of Pseudomonas aeruginosa demonstrates that biofilm formation is stimulated in response to competition, as opposed to a cooperative function of different strains or cell types [ 9 ]. The identification of YfiJK as a regulator of biofilm and motility functions is consistent with a model wherein competition with S . Mg1 induces developmental responses, including biofilm and colony spreading, among a subpopulation of resistant cells of B . subtilis . Using microbial competition we assigned resistance and developmental functions to a previously uncharacterized TCS in B . subtilis . Without imposing the conditions of competition on B . subtilis , these TCS functions may be difficult to identify, because the yfiJ , yfiK , and yfiJK deletion mutants have no phenotype when compared to wild type. The B . subtilis genome encodes 36 histidine kinases and 34 response regulators [ 89 ]. The functions of at least 11 of these TCS are currently unknown. Bacteria use these systems to sense and respond to their environment, which include stresses and nutrient conditions, but also include other bacteria and their antagonistic enzymes and specialized metabolites. Many TCS of unknown function may have a role in the context of microbial competition, despite having no distinct phenotype under laboratory conditions. Thus, microbial competition studies provide an effective approach to identify functions for TCS and other genes that promote competitive fitness of bacteria. By expanding our knowledge of individual competitive functions, a more comprehensive view of bacterial competitive fitness will emerge."
} | 4,312 |
28587290 | PMC5484115 | pmc | 8,071 | {
"abstract": "Genome mining has become an increasingly powerful, scalable, and economically accessible tool for the study of natural product biosynthesis and drug discovery. However, there remain important biological and practical problems that can complicate or obscure biosynthetic analysis in genomic and metagenomic sequencing projects. Here, we focus on limitations of available technology as well as computational and experimental strategies to overcome them. We review the unique challenges and approaches in the study of symbiotic and uncultured systems, as well as those associated with biosynthetic gene cluster (BGC) assembly and product prediction. Finally, to explore sequencing parameters that affect the recovery and contiguity of large and repetitive BGCs assembled de novo , we simulate Illumina and PacBio sequencing of the Salinispora tropica genome focusing on assembly of the salinilactam ( slm ) BGC.",
"conclusion": "5. Conclusions Current sequencing, assembly, and binning methods used to investigate BGCs have a number of notable strengths and weaknesses. Although these methods are powerful, allowing the investigation of BGCs even from uncultured sources, it should be apparent from this article that potential complications need to be taken into account and are context dependent. Consequently, there are no bioinformatic panaceas for BGC assembly and analysis. Researchers should therefore treat the output of bioinformatic applications with healthy skepticism, just as they should question and independently verify the results of instrumental measurements (e.g., complementing NMR with mass spectrometry analysis). There are a number of problems that do not yet have completely generalizable solutions in BGC analysis and metagenomics. A fundamental problem is that total structure prediction from cluster sequence is not yet possible; this clearly complicates the task of genome mining. Efforts have been made to collate and standardize the annotation of BGCs [ 180 ], which could aid future efforts to improve structure prediction. Another problem is that metagenomic binning is still difficult, often requiring much manual data processing and effort, a significant barrier for entry for groups interested in shotgun metagenomic sequencing. On the experimental side, there are two roadblocks contributing to the supply problem for any natural product made by an uncultured organism. The first of these entails the difficulty in culturing the majority of environmental microbes. It may well be possible to culture more environmental microbes than previously thought [ 44 , 46 ], but finding appropriate culturing conditions that are both selective and specific is a significant challenge. A potential solution to this challenge may lie in improved automatic annotation and metabolic modeling [ 181 , 182 ] of genomes obtained through metagenomics to predict growth rates and conditions. The other major problem is that heterologous expression is challenging, especially for large pathways, such as PKS and NRPS systems, and for pathways originating from uncultured organisms. Such pathways will likely not be suited to heterologous hosts, requiring de novo synthesis and refactoring [ 74 ] to provide optimal codon usage and compatible promoters, respectively. Advances in synthetic biology may ultimately alleviate this challenge but rational methods to identify and correct expression problems will still be needed. Ultimately, much has been achieved in developing tools to accurately correlate genomic information to structural information when it comes to natural products biosynthesis. However, this area of study continues to be heavily investigated and promises to provide challenging and rewarding work for years to come.",
"introduction": "1. Introduction As sequencing costs continue to decrease [ 1 ], it is now more feasible than ever to sequence the genome of natural product producing organisms. For isolated strains, the use of long-read PacBio sequencing combined with short-read Illumina data is now the gold standard, frequently yielding completely assembled microbial genomes using off the shelf assemblers [ 1 , 2 , 3 ]. Such technology provides access to genomic information that can be readily mined for new biosynthetic pathways, be they active or silent. However, there are situations when sequencing and assembly are not as readily accomplished. For instance, it may be difficult to extract large enough quantities of high-quality DNA from some systems (e.g., the variable cellular rigidities and doubling times of many Actinobacteria [ 4 ]); this limitation particularly impacts applications of culture-independent sequencing (metagenomics). In this review, we outline biological and practical issues to consider when embarking on a sequencing project to yield small molecule biosynthetic pathways. We also investigate the factors that contribute to successful assembly of repeat-laden biosynthetic pathways. Natural product chemists often desire to sequence biosynthetic pathways for a number of interconnected reasons. The most basic motivation is perhaps the gleaning of structural information from sequence data. In particular, absolute stereo-configuration can be predicted from the sequence of modular pathways such as polyketide synthase (PKS) and nonribosomal peptide synthetase (NRPS) systems [ 5 ]. Such analyses can be used to assign probable configurations when they are recalcitrant to spectroscopic and chemical analyses; this is especially the case with polyketides. The genomic context of a pathway may also give clues as to the molecular target or mechanism of action of a compound, since genes involved in resistance mechanisms are often clustered with natural product biosynthetic genes [ 6 , 7 ]. Another motivation for sequencing pathways is to establish a renewable supply of the compound of interest, either through engineering of the producing organism [ 8 , 9 ], or by heterologous expression [ 10 ]. Depending on the structural complexity of the natural product and/or the biosynthetic machinery driving its synthesis, this approach to production may be more practical than total organic synthesis. Notably, shotgun (random) sequencing campaigns generally associated with cluster identification often unearth much more data besides the sequence of a single pathway. These data can include the entire genome of the producing organism. In the case of metagenomics projects, the genomes of other co-localized species often complicate or obscure the specific pathway of interest. Nevertheless, this information can tie primary [ 11 ] and secondary metabolic pathways [ 12 , 13 ] to a specific organism allowing one to investigate the producing organism’s ecology and/or evolutionary history [ 14 ]. For instance, the degree of genome reduction in microbial symbionts [ 15 , 16 , 17 ] can suggest approximate evolutionary age and dependency of the symbiosis, along with the natural products made by the symbiont. One can also carry out comparative studies to investigate the function and evolution of natural products in the environment [ 18 ], distribution of pathways through horizontal transfer [ 19 ], and the dynamics of pathway expression in the environment [ 20 , 21 ]. Sequencing, therefore, can be used to study many aspects of chemical ecology, which is often of great interest to natural product chemists since the evolved target may be related to therapeutically relevant activities [ 22 ]. For these and other reasons, there is currently a great deal of interest in the application of “omics” technologies in the natural products field. Rather than exhaustively covering all “omics” work related to natural products, we concentrate herein on the limitations of current methods and the caveats in data analysis that researchers embarking on sequencing projects need to be aware of when designing experiments and analyzing acquired sequence data. We also discuss some biological, evolutionary, and ecological factors warranting consideration throughout the course of sequencing projects."
} | 2,006 |
30961056 | PMC6403572 | pmc | 8,072 | {
"abstract": "For the design of the next generation of microelectronic packages, thermal management is one of the key aspects and must be met by the development of polymers with enhanced thermal conductivity. While all polymer classes show a very low thermal conductivity, this shortcoming can be compensated for by the addition of fillers, yielding polymer-based composite materials with high thermal conductivity. The inorganic fillers, however, are often available only in submicron- and micron-scaled dimensions and, consequently, can sediment during the curing reaction of the polymer matrix. In this study, an epoxy/amine resin was filled with nano- and submicron-scaled alumina particles, yielding a gradient composite. It was found that the thermal conductivity according to laser flash analysis of a sliced specimen ranged from 0.25 to 0.45 W·m −1 ·K −1 at room temperature. If the thermal conductivity of an uncut specimen was measured with a guarded heat flow meter, the ‘averaged’ thermal conductivity was measured to be only 0.25 W·m −1 ·K −1 . Finite element analysis revealed that the heat dissipation through a gradient composite was of intermediate speed in comparison with homogeneous composites exhibiting a non-gradient thermal conductivity of 0.25 and 0.45 W·m −1 ·K −1 .",
"introduction": "1. Introduction Thermal management is one of the key aspects in the design of reliable microelectronic packages [ 1 , 2 ] as well as high-voltage machinery [ 3 , 4 ]. Geometry and materials have to be defined in a way that the packages, insulations, multi-layer assemblies, etc. can withstand the application-specific external or internal temperature loads. In microelectronics, the most critical load often originates from an internally generated heat by active components such as a power metal-oxide-semiconductor field-effect transistor (MOSFET) [ 5 , 6 , 7 , 8 ]. This type of silicon chip can produce high temperatures in short times, which results in pronounced temperature gradients and high thermo-mechanical strains [ 9 ]. Due to the ongoing demand for integrated functions and miniaturization, geometric changes of the design are subject to limitations, which add additional importance to increasing the thermal conductivity of the materials used [ 10 ]. Polymers are commonly used materials in power packages. Despite their broad versatility in material properties and functionality, all polymer classes show one common physico-chemical characteristic, namely, a very low thermal conductivity commonly in the range of 0.1 to 0.2 W·m −1 ·K −1 [ 4 ]. Very few polymers with dedicated structural motifs show a higher thermal conductivity of 0.3 W·m −1 ·K −1 [ 11 ]. This characteristic can be overcome by the addition of fillers with high thermal conductivity [ 4 , 12 , 13 , 14 ]. Due to the low heights of films in power packages or insulation layers down to the μm range, such (inorganic) fillers are preferentially used in nano- and/or submicron-scaled sizes. Aiming at high thermal conductivity of a composite material, highly priced fillers with high thermal conductivity such as nanodiamonds (λ = 2200 W·m −1 ·K −1 ) [ 15 ], hexagonal boron nitride (λ = 390 W·m −1 ·K −1 ) [ 16 ], and/or aluminum nitride (λ = 300 W·m −1 ·K −1 ) [ 17 ] may be added; reasonably priced alternatives are comprised of silica (λ = 0.7 W·m −1 ·K −1 ) and alumina (λ = 23 W·m −1 ·K −1 ) [ 18 ]. In cases of some inorganic fillers, nano-scaled particles are not available in quantities relevant for industrial production and/or at reasonable prices; this is particularly true for nanodiamonds and hexagonal boron nitride due to, among other things, their hardness. It must be taken into account that particles with diameters above the nano-scale may sediment in a composite material during the curing reaction, yielding a gradient composite with varying composition along the height scale (e.g., increasing content of inorganic fillers from top to bottom) and, consequently, an analogously varying thermal conductivity. The phenomenon of sedimentation eventually occurs to even higher extent due to the agglomeration of (non-functionalized) particles, despite their initial homogeneous dispersion in a polymer matrix [ 14 ]. Correspondingly, this study aimed at investigating the effect of particle sedimentation in an epoxy/amine resin and the consequences on the thermal conductivity of and the thermal dissipation through such a composite gradient. In order to trigger sedimentation of the particles, a mixture of nano- and submicron-scaled alumina particles was used. The thermal conductivity was comparatively quantified by laser flash analysis and a guarded heat flow meter. The experimental study was complemented by modelling efforts and finite element analysis in order to detail the thermal properties of gradient composites. With the help of numerical simulations based on thermal finite element models, the thermal properties of various types of materials, including the gradient composites detailed in this study, can be calculated in straightforward fashion, as this type of simulation models predominantly considers the thermal flux through the material. As such, it inherently provides the opportunity to calculate the temperature field without consideration of stresses, deformations, or electrical fields.",
"discussion": "4. Summary, Discussion and Conclusions An epoxy/amine-based gradient composite was prepared by the addition of nano- and submicron-scaled alumina particles by expanding the curing time of the polymer matrix to the range of a few hours. The thermal conductivity within this gradient composite ranged from 0.25 to 0.45 W·m −1 ·K −1 at r.t., hence by a factor of almost 2. The range of thermal conductivities could be measured within this study only by performing laser flash analysis on individual layers of a dedicatedly cut specimen. If the thermal conductivity of an uncut specimen was measured with a guarded heat flow meter, the ‘averaged’ thermal conductivity was measured to be 0.25 W·m −1 ·K −1 , reproducing in good approximation the lowest value of thermal conductivity according to laser flash analysis. The fact that these two types of measurement techniques revealed pronouncedly different findings will be subject of further studies. Complementary finite element analysis of a multi-layer assembly comprising layers of copper, silicon, and the epoxy/amine/alumina composite revealed that the heat dissipation through a gradient composite was of intermediate speed in comparison with materials exhibiting a non-gradient thermal conductivity of 0.25 and 0.45 W·m −1 ·K −1 , respectively, if the layers with the highest thermal conductivities were adjacent to the heat source. These findings of the finite element analysis supported the experimental data of the laser flash analysis. It may be concluded from this study that gradient composites are formed (autonomously) within the range of a few hours if non-nanoscaled fillers are added to a polymer matrix, e.g., for the enhancement of the thermal conductivity. This phenomenon must be taken into account in particular if only submicron or micron-scaled fillers are (commercially) available. Correspondingly, the thermal conductivity varies along (at least) one dimension of such a gradient composite. Such gradient composites nonetheless enable faster heat dissipation compared to a homogeneous composite material with a uniform thermal conductivity identical to the lowest one of the gradient composite, despite eventually identical thermal conductivity according to guarded heat flow Meter measurements."
} | 1,890 |
34711833 | PMC8553950 | pmc | 8,073 | {
"abstract": "Quorum sensing (QS) can function to shape the microbial community interactions, composition, and function. In wastewater treatment systems, acylated homoserine lactone (AHL)-based QS has been correlated with the conversion of floccular biomass into microbial granules, as well as EPS production and the nitrogen removal process. However, the role of QS in such complex communities is still not fully understood, including the QS-proficient taxa and the functional QS genes involved. To address these questions, we performed a metagenomic screen for AHL genes in an activated sludge microbial community from the Ulu Pandan wastewater treatment plant (WWTP) in Singapore followed by functional validation of luxI activity using AHL biosensors and LC–MSMS profiling. We identified 13 luxI and 30 luxR homologs from the activated sludge metagenome. Of those genes, two represented a cognate pair of luxIR genes belonging to a Nitrospira spp. and those genes were demonstrated to be functionally active. The LuxI homolog synthesized AHLs that were consistent with the dominant AHLs in the activated sludge system. Furthermore, the LuxR homolog was shown to bind to and induce expression of the luxI promoter, suggesting this represents an autoinduction feedback system, characteristic of QS circuits. Additionally, a second, active promoter was upstream of a gene encoding a protein with a GGDEF/EAL domain, commonly associated with modulating the intracellular concentration of the secondary messenger, c-di-GMP. Thus, the metagenomic approach used here was demonstrated to effectively identify functional QS genes and suggests that Nitrospira spp. maybe QS is active in the activated sludge community.",
"introduction": "Introduction Quorum sensing (QS) is a bacterial communication system that involves production, secretion, and response to signal molecules known as autoinducers and QS has been shown to regulate many bacterial behaviors 1 – 3 . QS has been extensively studied in a number of model microorganisms under axenic conditions 3 – 6 . However, most bacteria predominantly exist as a complex community in their natural habitat 7 , 8 where interspecies crosstalk may be common and where signaling process potentially play an important role in community function 9 , 10 . In wastewater treatment systems, interaction via QS signaling has been shown to serve important functions at the community level. For example, an increased AHL concentration was associated with changes in community composition and was linked to enhanced EPS production and biofilm formation in an activated sludge community 11 , 12 . In our previous studies, the formation of activated sludge granules was correlated with an increased in AHL concentration 13 and was accompanied by a shift in microbial community species composition. In particular, this change in community members was associated with a reduction in the organisms encoding quorum quenching functions to be dominated by those that encoded QS systems 14 . In terms of wastewater treatment performance, the ammonia removal efficiency was positively correlated with C4-HSL concentration, while C6- and C8-HSL were positively correlated with nitrite removal efficiency 11 , 15 . Activated sludge communities are highly diverse, commonly comprised of members from Proteobacteria, Bacteriodetes, and Chloroflexi 16 and often, many of those taxa are uncultivable or outgrown by faster-growing heterotrophs 17 , 18 . Because of these challenges, it is often difficult to directly couple QS organisms with their putative functions within the community. Traditional approaches for environmental samples have used metagenomic clone libraries to identify QS genes and reporter strains to identify the signals and the approximate concentrations of those signals 19 – 21 . However, this approach has limitations due to the need to construct and screen the entire metagenomic clone library as well as issues with gene expression in a heterologous host 22 , 23 . Typically, such screens have identified one to three AHL QS genes from the entire community 19 – 21 . Metagenome sequencing represents a potentially powerful approach to improve the identification of functional genes in complex communities and to assign those genes to specific taxa. For example, a total of 569 luxI sequences were found from the analysis of 68 metagenome samples collected from the Global Ocean Sampling 24 , while another in-silico study identified 31 luxI sequences from 14 environmental metagenomes 25 . These results highlight the power of metagenomic approaches in the search for AHL QS genes in complex communities. However, these in-silico analyses were not supported with experimental data to demonstrate that the QS genes identified were indeed functional. In this study, we performed metagenomic sequencing to examine the QS community in the activated sludge from the Ulu Pandan (UP) Wastewater treatment Plant (WWTP) in Singapore. We aimed to: (i) identify and functionally verify the genes involved in AHL QS signaling and (ii) to resolve the taxonomic origins of the putative luxI and luxR genes to explore the bacterial groups that may communicate via AHL QS in the activated sludge community. We found a cognate luxIR pair belonging to Nitrospira spp., a widespread genus of nitrite-oxidizing bacteria (NOB) 26 . We found that the Nitrospira LuxR (designated as NspR1) regulates the expression of its cognate luxI (designated as nspI ) gene, a hypothetical GGDEF/EAL-domain containing protein and a hypothetical transcription factor protein. We also demonstrated the binding of NspR1 to the promoter region of nspI gene in vitro and show that the DNA-binding activity requires the presence of RNA polymerase.",
"discussion": "Discussion The role of QS signaling in complex communities has been challenging to study, in part due to the difficulties in identifying individual QS producers and responders. This has typically been approached by either culturing individual species and testing them as pure cultures or through shotgun cloning 19 – 21 . However, these methods were limited by the fact that many organisms are difficult to culture, and shotgun cloning may result in genes not being expressed due to their position in vector or a lack of required regulatory proteins (e.g. native sigma factors, RNA polymerase, etc.). As a result, these approaches often identify low numbers of QS genes. In contrast, metagenomic sequencing studies have revealed a larger number of QS genes, although they may not capture and verify that the genes are functional 24 , 25 , 33 . In this study, we identified 13 putative luxI and 30 putative luxR homolog genes (representing 0.0012% and 0.0028% of total ORFs) in a complex sludge community from the UP WWTP. For comparison, it was found that AHL QS genes represent 0.0015% and 0.046% in the metagenome extracted from activated sludge and biofilm from membrane bioreactor, respectively 34 , while another study reported no QS genes were found in the microbial community from terephthalate-degrading wastewater bioreactor 25 . In addition, we functionally verified the putative luxI genes using AHL biosensor strains and LC–MS/MS, while for luxR , using conserved domain analysis. Except for US16, all of the luxI genes activated at least one of the AHL biosensors, demonstrating they are functional and most luxI produced intermediate chain (C6 and C8) AHL. In our previous study, the concentration of intermediate-chain AHLs, e.g. 3OC6-HSL, C6-HSL, C8-HSL, and 3OC8-HSL correlated with the transition of floccular sludge into granular sludge as well as EPS production 13 . Interestingly, many of the luxI homologs identified in this study were able to produce three out of the four key AHLs, suggesting their potential role in stimulating the granulation process of the sludge community. One luxI and three luxR homologs found in this study were linked to Nitrospira , which is recognized as the key NOB in both natural and engineered habitats 35 , 36 . AHL QS genes in Nitrospira were first described in 2012 21 and to date, relatively few studies have been reported for Nitrospira AHL QS 26 , 31 , 34 , 37 . The AHL QS in Nitrospira was reported in N. defluvii from Nitrospira lineage I as well as N. moscoviensis , N. japonica , N. inopinata , and N. nitrifican from lineage II which includes the comammox group that is capable of complete ammonia oxidation 21 , 31 . Because we were unable to recover full-length 16S rRNA genes or achieve sufficient genome coverage, we are unable to resolve the lineage of the Nitrospira harboring the AHL QS genes identified in this study. Based on the BLAST search, the majority of the ORFs found on the Nitrospira contigs were mostly related to N. defluvii from lineage I. In addition, we also did not detect the amoA gene in the contigs assigned to the Nitrospira contigs. This would suggest that the species identified here is not a Comammox organism. A hybrid Illumina and Nanopore long-read sequencing approach could be performed in the future to improve the genome recovery in order to resolve the lineage of the Nitrospira identified in this study. Based on sequence comparison, all of the Nitrospira QS genes were closely related regardless of lineage suggesting that it is likely that they were inherited from ancient common ancestors with Proteobacteria rather than acquired through horizontal gene transfer event 21 . Whether QS regulates nitrification and the survival fitness in this bacterium remained unclear. Given its important role in the nitrogen removal process in WWTP and scarce knowledge on the QS system in Nitrospira , we decided to further study the cognate pair of Nitrospira AHL QS gene US13 and UR43, which were later designated as nspI and nspR1 , respectively. NspI was most closely linked to N. defluvii and produced C8-HSL as the dominant AHL species. The AHL species reported in other Nitrospira include C8-HSL ( N. moscoviensis ) and C12-HSL ( N. japonica and a metagenomic clone of N. defluvii ) 21 , 31 , 37 . NspR1, on the other hand, was found to regulate the expression of its cognate AHL synthase NspI and a GGDEF/EAL domain-containing hypothetical protein in a GFP-reporter assay when C8-HSL was added. The upregulation of nspI gene by its own cognate LuxR suggests that the AHL QS in this Nitrospira spp. is also subjected to the autoinduction feedback system, which is commonly observed in many other QS-proficient bacteria 2 , 38 . GGDEF/EAL-domain-containing proteins are known to regulate a diverse set of cellular functions including biofilm formation and bacterial virulence 39 via modulating the concentration of intracellular cyclic-di-GMP in response to environmental cues such as oxygen and nitric oxide 40 , 41 . Hence, it is possible that the AHL QS in Nitrospira spp. may indirectly regulate multiple downstream genes via the cyclic-di-GMP pathway or fine-tuning the gene expression by integrating of QS signal and local environmental cues. The two genes are oppositely oriented and shared a common lux box sequence (ACCTGGCGGTTCCGCCAGGT) in their promoter sequence, indicating that the transcriptional regulatory effect of NspR1 is bi-directional. The results of the GFP-reporter assay are further supported by the EMSA result which demonstrates the binding of NspR1 to the Nsp104 probe which carries the common lux -box sequence, confirming that this lux box is truly regulated by the NspR1. All of the other putative lux boxes had at least two nucleotide differences and thus may suggest that the lux box described above is the true recognition sequence for NspR1. Interestingly, the NspR1 only bound the lux box in the presence of RNA polymerase (Fig. 5 ). Although RNA polymerase has been reported to interact with Proteobacterial LuxR homologs, such as LasR, LuxR, and TraR to facilitate the expression of target genes 42 , 43 , the DNA binding does not require the presence of RNA polymerase 44 – 47 . Hence, the requirement of RNA polymerase for DNA binding might be unique to the Nitrospira LuxR. Co-expression of the native host’s sigma factor has been shown to facilitate the recognition of the foreign promoter in the screening host 22 . With the co-expression of one of the rpoD genes ( rpoD2 ), we identified an additional Nspbox (Nspbox23) under the regulation of AHL QS. Nspbox23 contains a palindromic lux box-like sequence (CACTGGACGAGTGTACAGTT) and is located 187 bp upstream to a gene encoding putative helix-turn-helix domain-containing protein, suggesting its potential role as a transcription regulator. Sigma factors RpoS and RpoN were reported to co-regulate the QS regulon in Pseudomonas aeruginosa and Burkholderia pseudomallei 48 – 51 . However, in this study, we did not identify any additional Nspbox induced with the co-expression of the Nitrospira rpoS and rpoN gene. Instead, the co-expression of Nitrospira sigma factors affect the AHL QS induction of Nspbox1 and Nspbox2 at varying degree. In particular, Nspbox2 which regulates the expression of the AHL synthase nspI was completely suppressed by co-expression of the Nitrospira rpoN gene. RpoN has been shown to regulate gene expression under nitrogen-limiting conditions and also to regulate diverse functions such as virulence and motility 52 – 54 . Given that nitrogen serves as the major energy source for NOB, it is possible that QS in Nitrospira is repressed under nitrogen-limiting conditions. These findings suggest that C8-HSL QS may play a role in regulating the nitrification process to acquire energy more efficiently and to compete for the nitrogen resources in a mixed community. Indeed, it was reported previously that C8-HSL could accelerate ammonium oxidation rate by the anaerobic ammonium oxidation (ANAMMOX) communities dominated by Candidatus Brocadia fulgida 55 or Candidatus Jettenia caeni 56 and modulate nitrogen oxide fluxes in N. winogradskyi 57 .” This study shows that a combination of bioinformatics and in vitro functionality tests can be applied to study AHL-mediated QS in a complex community such as an activated sludge system. Our results show that there are many novel luxI and luxR homolog genes found in the activated sludge and we expect that the same will also be observed in other complex ecosystems. We demonstrated the functionality of both the luxI and luxR gene from a QS-proficient Nitrospira that is present in the sludge metagenome and describe an unusual DNA-binding behavior that was not observed for other LuxR receptors. This provides valuable insight into the molecular mechanism of AHL QS in Nitrospira . Further work would include investigating the downstream regulatory outcomes of QS in this organism, such as the implications for AHLs to regulate the expression of c-di-GMP modifying enzymes and the associated genes and phenotypes."
} | 3,738 |
36936196 | PMC10022739 | pmc | 8,074 | {
"abstract": "Woodlands are pivotal to carbon stocks, but the process of cycling C is slow and may be most effective in the biodiverse root zone. How the root zone impacts plants has been widely examined over the past few decades, but the role of the root zone in decomposition is understudied. Here, we examined how mycorrhizal association and macroinvertebrate activity influences wood decomposition across diverse tree species. Within the root zone of six predominantly arbuscular mycorrhizal (AM) ( Acer negundo, Acer saccharum, Prunus serotina, Juglans nigra, Sassafras albidum, and Liriodendron tulipfera ) and seven predominantly ectomycorrhizal (EM) tree species ( Carya glabra, Quercus alba, Quercus rubra, Betula alleghaniensis, Picea rubens, Pinus virginiana, and Pinus strobus ), woody litter was buried for 13 months. Macroinvertebrate access to woody substrate was either prevented or not using 0.22 mm mesh in a common garden site in central Pennsylvania. Decomposition was assessed as proportionate mass loss, as explained by root diameter, phylogenetic signal, mycorrhizal type, canopy tree trait, or macroinvertebrate exclusion. Macroinvertebrate exclusion significantly increased wood decomposition by 5.9%, while mycorrhizal type did not affect wood decomposition, nor did canopy traits (i.e., broad leaves versus pine needles). Interestingly, there was a phylogenetic signal for wood decomposition. Local indicators for phylogenetic associations (LIPA) determined high values of sensitivity value in Pinus and Picea genera, while Carya, Juglans, Betula, and Prunus yielded low values of sensitivity. Phylogenetic signals went undetected for tree root morphology. Despite this, roots greater than 0.35 mm significantly increased woody litter decomposition by 8%. In conclusion, the findings of this study suggest trees with larger root diameters can accelerate C cycling, as can trees associated with certain phylogenetic clades. In addition, root zone macroinvertebrates can potentially limit woody C cycling, while mycorrhizal type does not play a significant role.",
"conclusion": "5. Conclusions Unraveling ways in which biodiverse trees can influence ecosystem processes may provide additional insight into C and nutrient cycling. With respect to the root zone, a phylogenetic signal was observed for decomposition. Pinus and Picea species were most sensitive to decomposition–phylogenetic distance autocorrelations. The presence of macroinvertebrates lessened recalcitrant litter decomposition, perhaps suggesting an antagonistic effect of macroinvertebrates on saprotrophs. Additionally, the finding that mycorrhizal type did not affect wood decomposition suggests neutral outcomes for forest demography shifts, specifically those that affect predominant mycorrhizal type (i.e., AM versus EM). Additionally, results of this study support the premise that woodlands overrepresented by trees of a large root diameter can potentially accelerate the cycling of recalcitrant C.",
"introduction": "1. Introduction Woody plants are quintessential to carbon storage and net primary productivity [ 1 , 2 ]. These rigid organisms inhabit 30% of Earth’s landmass and contain 50% of the carbon that makes up the aboveground terrestrial biosphere [ 3 , 4 ]. In addition to their impact on C flux, woody plants can shape the pedosphere [ 5 ] through root recruitment of mycorrhizal fungi, recycling of organic material, and litter deposition [ 6 , 7 ]. Particularly, plant material can be fragmented by natural events (e.g., freeze–thaw events, windstorms, and animal activity), as well as deposited into soil communities from plant standing mass. Coarse and fine wood debris can make up anywhere from 1 to 25% of the forest floor [ 8 - 10 ], as the brown food web is supplemented by rotten logs, snags and stumps, which can provide resources for seed germination [ 11 ], as well as habitats for invertebrates and microbes. Select soil microbes have a primary role in wood degradation and are key components of SOM formation and decomposition [ 12 ]. Yet, soil macroinvertebrates (>2 mm) may have an equally important role as microbial decomposers [ 13 ], but macroinvertebrate function is often context dependent and can at times be disruptive (e.g., burrowing, predation, and ecosystem engineering) to microbial function. Determining ways in which diverse root zones may impact soil fauna is essential to understanding brown food web processes. Many organisms are involved in mineralizing wood: ~20–30 percent of forest arthropods, including insects, are either wood dependent (i.e., saproxylic) or opportunistically utilize wood [ 14 , 15 ]. Wood can be broken down through modes of tunneling and nesting [ 16 ], while some invertebrates rely on hindgut microbes to metabolize wood [ 17 , 18 ]. Lumbricida (i.e., earthworms) and collembola (i.e., springtails) harbor Bacillus spp. in their intestinal systems, which plays a role in the degradation of chitin and lignocellulose [ 17 ]. Radiolabeling studies have found invertebrates to consume both mycorrhizae and saprotrophic fungi [ 19 ], perhaps suggesting that macroinvertebrates can harness microorganisms involved in C exchange and cycling. Invertebrate activity, including the communition of wood debris and burrowing activity, can increase wood surface area, potentially leading to increased decomposition through mycelium contact with wood surfaces. Invertebrates may also slow down decomposition, as collembola (i.e., Folsomia Candida ) activity has been reported to sever and disrupt mycelial cords from connecting with wood substrate [ 20 ], which can slow C cycling. This may be pertinent to recent studies that suggest hyphal extension to be an important predictor of wood decomposition [ 21 ]. Wood is decomposed by a limited number of invertebrate and fungal classes [ 15 , 22 , 23 ]. Decomposer efficacy may also be influenced by foliar litter input [ 24 - 26 ], as minerals can differentially accumulate in foliar tissue prior to being introduced into soils [ 27 ]. Differences in pine versus broad leaf tissue may differentially alter soil chemistry (i.e., pH) [ 28 ], as aging pine needles can lead to an increase in Mn 2+ oxidation state (i.e., Mn 3+ and Mn 4+ ), which negatively corresponds with C: N [ 29 ]. Such changes in litter chemistry may directly affect decomposers [ 30 ], as white, brown, and soft rot presence in sapwood corresponds to wood pH [ 31 ]. White and brown rot fungi can decompose wood through enzymatic activity or Fenton redox chemistry [ 32 - 35 ]. Aside from free-living decomposers, root-associated fungi may also play a role in decomposition, especially in the context of the root zone. Some root-partnering fungi, termed ectomycorrhizal (EM) fungi, have been reported to degrade cellulose through Fenton redox chemistry and hydroxyl radical attacks [ 36 , 37 ]. This suggests that the life history of EM fungi spans a biotroph–saprotroph continuum [ 38 ], but this characterization may depend on life history, evolutionary divergence, and the retention/expression of lignocellulolytic genes that are localized in mycelial networks [ 39 ]. In contrast, arbuscular mycorrhizal (AM) fungi are not known for lignocellulolytic capabilities, but still, AM fungi can increase water-stable aggregates [ 40 , 41 ] and make the soil environment conducive toward decomposers. Interestingly, fine roots can reduce soil moisture (i.e., drying effect), which may be antagonistic toward decomposers [ 42 ]. Thus, root morphology, or variation in root diameter, may help shape root zone decomposition, as previous studies found correlations with root diameter and soil organic matter respiration [ 43 , 44 ]. Moreover, root-zone-mediated decomposition may also be autocorrelated with phylogenetic signals or links between phylogeny and continuous trait values [ 45 ]. For example, decomposition in hardwood tree soils (e.g., black cherry) may differ from softwoods (e.g., pines), but in a manner that is not to be confused with phylogenetic conservatism [ 46 ]. To date, a myriad of studies has increased our understanding of wood decomposition [ 47 - 51 ], but the effect of the soil-mediated root zone is unclear. In addition to that, it is unclear how macroinvertebrates are differentially influenced by the root zone of EM-versus AM-associated trees, as well as trees of varying root diameter and phylogenetic distance. In this study, we sought to unravel how soils conditioned by diverse tree species can affect the decomposition of woody litter. Here, mycorrhizal type, phylogenetic distance, root diameter, litter quality (canopy trait), and macroinvertebrates were assessed. To address this knowledge gap, we sought to determine how mycorrhizal type interacts with macroinvertebrates to influence decomposition. To limit the influence of environmental heterogeneity, we made use of a common garden forest by manipulating the presence (+) or absence (−) of macroinvertebrates > 0.22 mm on added woody material in the root zone of six AM and seven EM trees. Under these conditions, wood was allowed to decompose for 13 months in the root zone of 13 tree species. We hypothesized that: (1) the exclusion of macroinvertebrates (>0.22-mm) would enhance decomposition due to less negative interactions on microbes; (2) root diameter would be a good predictor of decomposition, and there might be a phylogenetic signal for this trait. Additionally, (3) differences in mycorrhizal association would lead to differences in wood decomposition rates.",
"discussion": "4. Discussion Wood decay provides a sink for N 2 O and a source for CO 2 and CH 4 [ 73 ], as well as a source for soil phosphorus [ 65 ]. In addition, it is widely accepted that wood decomposes faster in soil communities than in suspension [ 65 , 73 ]. The novelty of the present study is the interactive role of root morphology, mycorrhizal type, and macroinvertebrates on wood degradation in rhizosphere-adjacent soils. Soils are differentially influenced by plantspecific traits (i.e., rhizodeposition and foliage), which in turn helps structure belowground communities [ 74 ]. To our knowledge, this is the first study to show an association between phylogenetic distance and wood decomposition. Species that were more closely related to pines had highly sensitive values for local positive auto correlations. Tree mycorrhizal type also has the potential to impact root zone dynamics. Past studies have predicted differences in AM and EM trees in biogeochemical cycles [ 63 , 75 , 76 ], which may be pertinent to shifts in forest demography [ 77 ], which can impact predominant mycorrhizal type [ 78 ]. As it relates to this study, mycorrhizal type did not impact wood decomposition ( Table 2 ), which suggests a mixed effect of mycorrhizal type on C cycling that may depend on the species of fungi colonizing the host tree species. To our knowledge, we are the first to examine wood decomposition in root zones of contrasting mycorrhizal association and root morphology. Mild interaction was observed between mycorrhizal type and root diameter ( Table 2 ). Irrespective of mycorrhizal type, root diameter was positively correlated with wood decomposition at a marginal level of significance ( Figure 5 ), as coarse roots significantly increased decomposition ( Figure 6A ). While coarse roots promoted decomposition, a phylogenetic signal was not detected for this trait. Interestingly, excluding macroinvertebrates from the soil environment led to increased wood degradation ( Figure 6C ), which corroborates the findings of Wood, Tordoff [ 20 ], which suggested that macroinvertebrates can disrupt microbial decomposer involvement in wood decomposition. Taken together, these findings provide insight into wood decomposition as influenced by biodiverse root zones. 4.1. Foliar Trait Legacy and Wood Decomposition Phylogenetic signals were observed in tree-specific soils ( Figure 2 ). These signals were likely due to root exudates and litter input from the canopy trees. Litter inputs can fuel soil food webs through rhizodeposits, foliage, and surface accumulation [ 79 ]. Specifically, plant identity can structure communities of arachnida, nematoda, collembola, enchytraeidae, and mycorrhizae [ 74 ]. Together, these communities may help facilitate the outcome of wood decomposition. Lignin is an important component of wood and makes up 20–32% of lignocellulosic biomass and is dramatically resistant to chemical degradation [ 33 , 80 ]. According to our ANOVA model, the decomposition rate beneath pine versus broad leaf canopies was insignificant ( Table 2 ), but these differences may be gradual and amplified over phylogenetic distance ( Figures 2A and 3A ). This may also explain why local positive autocorrelation was detected on opposite ends of the phylogenetic spectrum ( Figure 4A ). Sensitivity values waned in species that were phylogenetically distant from Pinus and Picea species, including Carya and Juglans spp. Ironically, Carya glabra and Juglans nigra were previously shown to differ from Pinus strobus and Pinus virginiana in stem wood density [ 81 ] by about 45 percent. The tree species used in this study have been structuring the soil community for over 20 years at this particular site, yielding notable changes in some soil characteristics [ 61 ]. The effect of tree litter deposits may amplify with an increase in stand age [ 82 ], as tree-specific litter has been reported to impact invertebrate richness, diversity, and assemblage [ 24 ]. The phylogenetic signal observed in the present study suggests tree species can condition the soil environment in way that may be predictable across species of closely related genera. 4.2. Macroinvertebrate Exclusion Improved Wood Decomposition Macroinvertebrate exclusion increased wood decomposition ( Table 2 ). This may suggest that macroinvertebrates can disrupt saprotroph mycelial cords and reduce C cycling. On the contrary, there may be a specific context in which macroinvertebrates and fungal decomposers can have an additive effect on wood decomposition, and this may depend on the abundance of macroinvertebrates that specialize in wood (i.e., termites, carpenter ants, etc.). For example, +macroinvertebrate communities that are overrepresented with termites and carpenter ants are likely to increase wood decomposition, as this select class of arthropods can specialize in recalcitrant forms of carbon. However, this experiment was conducted in the root zone, which is rich in labile carbon (i.e., active photosynthates, soluble C, etc.) and root-derived C [ 83 ], thereby providing resources to a broad array of organisms. Macroinvertebrate exclusion improved subsurface wood decomposition ( Figure 6C ), and similar effects have been found for surface wood decomposition, as macroinvertebrate exclusion was reported to alter saprotroph communities [ 16 ]. In subtropical forests, wood contact with soil surface, combined with invertebrates, was found to be optimal for wood decomposition [ 84 ]. The role of macroinvertebrates may also depend on canopy tree cover (i.e., shading); an increase in ambient radiation has been shown to decrease invertebrate density [ 47 ]. 4.3. Mycorrhizal Type and Wood Decomposition Mycorrhizal type has important implications on ecosystem processes, including soil structure, C storage, and N and P cycling [ 85 - 87 ]. As it relates to global change biology, predictable demographic shifts in eastern USA deciduous forests [ 77 ] can directly lead to shifts in the dominant mycorrhizal type. Mycorrhizal fungi can increase the uptake of soluble nutrients, and in some cases, the mycorrhizal type (e.g., EM fungi) can even lead to the decomposition of organic matter [ 37 ]. However, this may depend on the forest system (i.e., boreal versus temperate forest), as EM’s lignocellulolytic enzyme capabilities may not necessarily apply to recalcitrant woody litter, although EM fungi have been found to modify SOM [ 88 , 89 ]. Mycorrhizal type did not influence wood decomposition in this study ( Table 2 ), perhaps suggesting that models predicting the role of mycorrhizae in C and nutrient cycling may not apply to wood-derived C in temperate forests. 4.4. Moderate Correlation between Decomposition and Root Diameter Our findings suggest wood decomposition may not be impacted by tree demographic shifts affecting mycorrhizal type, but instead, by tree-species shifts affecting absorptive root diameter. Across the root zone of 13 diverse tree species, we found a positive correlation between root diameter and wood decomposition ( Figure 5 ), with most points falling within the 95% CI ( Figure A5 ). Wood decomposition in coarse root zone soils was increased by ~8% ( p < 0.001; Figure 6A ). Perhaps this may be explained by the “drying effect hypothesis” [ 42 ], where fine roots are better able to remove soil residual moisture from soil and suppress decomposer activity. In grasses, root diameter was found to be positively correlated with decomposition and soil organic carbon respiration [ 43 ]. Interestingly, a similar trend was found among woody plants [ 44 ], perhaps suggesting that increased root diameter facilitates increased C and N cycling. Collectively, these findings show an additive effect of root diameter on decomposition. In addition, we did not observe interaction of root diameter with the macroinvertebrate exclusion barrier (0.22 mm mesh). This suggests that while the barrier may have inhibited a certain amount of root growth around the wood substrate, it did not limit the growth of coarse-root species more than fine-root species. To our knowledge, this is the first study to show a correlation of root diameter with the decomposition of wood debris."
} | 4,436 |
26484735 | PMC5029217 | pmc | 8,077 | {
"abstract": "Microorganisms in the terrestrial deep biosphere host up to 20% of the earth's biomass and are suggested to be sustained by the gases hydrogen and carbon dioxide. A metagenome analysis of three deep subsurface water types of contrasting age (from <20 to several thousand years) and depth (171 to 448 m) revealed phylogenetically distinct microbial community subsets that either passed or were retained by a 0.22 μm filter. Such cells of <0.22 μm would have been overlooked in previous studies relying on membrane capture. Metagenomes from the three water types were used for reconstruction of 69 distinct microbial genomes, each with >86% coverage. The populations were dominated by Proteobacteria , Candidate divisions, unclassified archaea and unclassified bacteria. The estimated genome sizes of the <0.22 μm populations were generally smaller than their phylogenetically closest relatives, suggesting that small dimensions along with a reduced genome size may be adaptations to oligotrophy. Shallow ‘modern marine' water showed community members with a predominantly heterotrophic lifestyle. In contrast, the deeper, ‘old saline' water adhered more closely to the current paradigm of a hydrogen-driven deep biosphere. The data were finally used to create a combined metabolic model of the deep terrestrial biosphere microbial community.",
"conclusion": "Conclusions One striking feature for all three water types was the potential ability of the major populations to use a plethora of metabolic processes to sustain their energy and nutrient requirements. For example, several populations were suggested to be able to grow mixotrophically including the modern marine group I ( Figure 3 ) that potentially ferments organic carbon, couples inorganic sulfur compound oxidation to nitrate reduction and fixes carbon dioxide via the CBB cycle. An exception to this was several poorly understood microbial taxa associated with candidate division populations that were suggested to grow via fermentation of simple organic carbon compounds or amino acids. These candidate division populations show a greater dependency on heterotrophy in these waters than previously reported. The metabolic model of the dominant populations in the microbiome at 171 m below the surface of the earth at the Äspö HRL has a greater dependency on organic carbon than the paradigm of an autotrophic, hydrogen-driven environment. This organic carbon could potentially be provided from the surface waters of the Baltic Sea. In contrast, the dominant microbial community in the deeper and more anciently formed saline waters appears to be more extensively maintained by chemolithoautotrophic processes. The ability to reduce sulfate (or sulfur) by known pathways was primarily found in the deepest, old saline waters but was less widespread in the modern marine water compared with previous models of the Fennoscandian deep biosphere based upon growth experiments and 16S rRNA gene-based methods ( Itavaara et al. , 2011 ; Pedersen 2012 , 2013 ). Furthermore, the dominant populations have no genomic signal for ferric or manganese reduction or methanogenesis, despite that these microorganisms have been cultured from the Äspö HRL ( Hallbeck and Pedersen, 2008 ) and that key genes in methanogenesis have been amplified from the Outokumpu deep borehole waters ( Purkamo et al. , 2015 ). Finally, the Äspö HRL microbial communities included cells with a small cell size that also had a tendency to have smaller genomes than their closest sequenced relatives. This may be a physiological adaptation to life in highly oligotrophic deep biosphere groundwaters. A consequence of their small size makes these cells likely to have been overlooked in earlier studies relying on membrane capture.",
"introduction": "Introduction The existence of a deep biosphere was postulated ∼20 years ago ( Gold, 1992 ) and it is now known that the presence of microorganisms extends for several km below the surface ( Lin et al. , 2006 ). As a result of its recent discovery and the inherent difficulties in accessing samples from these systems, the deep biosphere is one of the least understood ecosystems on earth. In recent studies it has been estimated that 4.1 × 10 15 g C reside in the deep marine biosphere ( Kallmeyer et al. , 2012 ) whereas the deep continental subsurface is estimated to contain from 10 16 to 10 17 g C ( McMahon and Parnell, 2014 ). At depths below those influenced by organic carbon from the surface, the environment is suggested to be highly oligotrophic ( Hoehler and Jorgensen, 2013 ) and deep life has been described as proceeding ‘in extreme slow motion' with generation times ranging from hundreds to thousands of years ( Jorgensen, 2011 ; Onstott et al. , 2014 ). Despite living under extreme energy limitation, deep subsurface microorganisms are suggested to be predominantly viable and active ( Hoehler and Jorgensen, 2013 ). Several lines of evidence support this idea including gene expression in marine subseafloor metatranscriptomes implying metabolically active, dividing cells from all three domains of life ( Orsi et al. , 2013 ). Whereas information on the diversity of these deep-dwelling microorganisms is scarce, it was recently shown that microorganisms in more shallow groundwater aquifers are diverse and include representatives from many uncultivated or poorly characterized lineages ( Luef et al. , 2015 ). Many of the cells in these aquifers were also characterized by small physical size and streamlined genomes ( Luef et al. , 2015 ). The SKB (Swedish Nuclear Fuel and Waste Management Co.)-run Äspö HRL (Hard Rock Laboratory) is located in Proterozoic crystalline bedrock of the Fennoscandian shield and consists of a 3.6-km long tunnel extending to 460 m below the ground. Microbiological studies of the Äspö HRL have thus far relied on a mixture of culture-dependent methods, adenosine triphosphate assays and 16S rRNA gene approaches. It is suggested that the bedrock waters represent an anaerobic and oligotrophic environment colonized by nitrate-, ferric-, sulfate- and manganese-reducing microorganisms along with acetogens and methanogens ( Hallbeck and Pedersen, 2012 ; Pedersen, 2013 ; Ionescu et al. , 2015b ). A preliminary model of energy and carbon acquisition being driven by the ‘geogases' hydrogen and carbon dioxide ( Pedersen, 1999 ) is supported by the presence of the hydrogenotrophic sulfate-reducing bacterium, Desulfovibrio aespoeensis ( Pedersen et al. , 2014 ). However, other potential energy sources that may be exploited by microorganisms in the deep biosphere should also be evaluated. These include anaerobic oxidation of inorganic sulfur compounds ( Osorio et al. , 2013 ) and exudation of organic carbon by chemolithoautotrophic microorganisms that may be subsequently utilized by heterotrophs ( Nancucheo and Johnson, 2010 ). Potential chemolithotrophic metabolisms of deep biosphere microorganisms have traditionally been evaluated based upon standard conditions rather than in situ conditions and reactant concentrations. Using in situ values suggests that energy can be harvested from the transformation of sulfur, iron, nitrogen, methane and manganese compounds, and this is in good alignment with microbial metabolic capabilities inferred from previous 16S rRNA gene inventories ( Osburn et al. , 2014 ). Metagenomics is the sequencing of environmental DNA from the entire microbial community without introducing biases from culturing or PCR amplification. This technique has been applied to the deep subsurface such as the Outokumpu drill hole where homoacetogenic, methylotrophic and methanogenic processes are present ( Nyyssonen et al. , 2014 ). However, in the referenced study, the metabolic functionality was not partitioned to different taxa. A deep terrestrial biosphere metagenome has also been used to reconstruct the complete genome of Candidatus Desulforudis audaxviator that comprises >99.9% of the microorganisms in a fracture within a 2.8-km deep South African gold mine ( Chivian, 2008 ). A third study identified the dominating microorganism to be Halomonas sulfidaeris in a 1.8-km deep subsurface Cambrian Sandstone reservoir ( Dong et al. , 2014 ). The latter environments are characterized by low species diversity in contrast to more diverse communities in the Outokumpu drill hole ( Nyyssonen et al. , 2014 ) and have very different geological conditions to the Fennoscandian Shield. The present study investigates the genetic potential in microbial metagenomes from three water types at the Äspö HRL. To advance our understanding of metabolic interactions within the indigenous microbial community, the sequencing data were partitioned and assembled into amalgamated genomes from phylogenetically distinct populations. Subsequently, a metabolic reconstruction of the dominant community members and an insight into their potential dependencies and other community-level interactions in the deep terrestrial biosphere were inferred.",
"discussion": "Results and discussion Geochemical characteristics of the borehole fracture waters All three fracture groundwaters were neutral (pH 7–8), carried iron entirely as Fe 2+ , contained dissolved sulfide (HS − ), had temporally stable chemistry and δ 18 O, and based upon the presence of Fe 2+ and HS − the redox potential was low and dissolved oxygen would have been absent ( Table 1 ). However, they differed in terms of several chemical constituents. Based on their major element chemistry and δ 18 O values, the groundwaters could be characterized with regard to origin and age ( Laaksoharju et al. , 2008 ). SA1229A had high magnesium and potassium concentrations, which are tracers of marine waters in these settings ( Gimeno et al. , 2014 ), and also had similar values for the conservative variables chloride and δ 18 O as modern Baltic Sea water ( Mathurin et al. , 2012 ). This groundwater was thus composed of infiltrated brackish marine (Baltic Sea) water and was termed ‘modern marine' (metagenome bins defined as ‘MM'). The precise infiltration age of the groundwater was not known, but was estimated to be <20 years and is probably even more recent ( Mathurin et al. , 2014b ). The origin and age of the KA3105A:4 groundwater cannot be defined in detail. It had relatively low chloride concentrations and thus was strongly influenced by fresh waters, such as glacial meltwater and/or modern meteoric water. It may also contain appreciable amounts of Baltic Sea water or Littorina Sea water. However, it also likely contained older waters as it was sampled at 415.19 m below ground surface. It was concluded that the KA3105A:4 groundwater was composed of a mixture of several different water types and was termed an ‘undefined mixed' (metagenome bins defined as ‘UM'). KA3385A:1 had high chloride and calcium concentrations and relatively low δ 18 O values. These features are typical for saline groundwater with a residence time in the order of thousands of years or more ( Louvat et al. , 1999 ). However, the chloride concentration of this groundwater was considerably lower than for pure old saline water at the site ( Mathurin et al. , 2012 ). Therefore, this groundwater had been diluted by waters with lower salinity including glacial meltwater from the retreat of the last Pleistocene continental ice sheet and marine water intruded during the Littorina Sea stage a few thousands of years ago ( Mathurin et al. , 2012 ). This groundwater was termed ‘old saline' (metagenome bins defined as ‘OS'). A principal component analysis ( Figure 1 ) of chemical characteristics for the three water types showed that dissolved organic carbon was associated with both the modern marine and undefined mixed water types. This organic carbon is regarded to be dominated by reduced humic substances, consisting of humic and fulvic acids in variable proportions ( Mathurin et al. , 2014a ) that may be a source of electron donors for heterotrophic species. The higher amounts of dissolved organic carbon in the modern marine water was supported by cell counts showing lower cell numbers in the undefined mixed and old saline waters (127 cells per ml in the modern marine water compared with 37 and 100 cells per ml in the undefined mixed and old saline waters, respectively). These microorganisms may have been growing by nitrate reduction to nitrite and/or ammonia in both water types, as indicated by the elevated levels of nitrite in both waters and ammonium in the modern marine water. The source of oxidized nitrogen is unknown but based upon community mRNA transcript sequencing it has been hypothesized to be formed in a subseafloor sediment as a by-product of anaerobic ammonium oxidation ( Orsi et al. , 2013 ). In addition, previous studies at the Äspö HRL have identified nitrate/nitrite-reducing species ( Nielsen et al. , 2006 ; Pedersen 2013 ; Ionescu et al. , 2015a , 2015b ). Elevated levels of hydrogen sulfide suggested that microbial sulfate reduction might be a more dominant form of respiration in the undefined mixed water compared with the modern marine water. In contrast, increased levels of ferrous iron in the modern marine water suggested anaerobic ferric iron reduction may be a growth strategy in this water mass. However, homologs may not have been identified as the gene(s) encoding for ferric reductase has only been identified in a few species, such as from the Geobacter and Shewanella genus ( Bird et al. , 2011 ), or because soluble redox mediators were used. The lack of chemical ions associated with microbial metabolism in the old saline water probably reflected a lower biomass, as supported by the lower amounts of DNA recovered from this water ( Supplementary File 2 ). DNA extraction and metagenome sequencing data The volume of the different water types filtered, amount of DNA extracted and details of metagenome sequencing are provided in Supplementary File 2 . Details of each approved phylogenetic bin are given in Supplementary File 4 . Many of the cells in the tested Äspö HRL water types passed a 0.22 μm filter and electron microscopy confirmed their small cell size ( Supplementary File 5 ). There was little taxonomic overlap between these small cells (<0.22 μm metagenome; metagenome bins defined as ‘S') and those that were retained (>0.22 μm metagenome; metagenome bins defined as ‘L') ( Supplementary File 6 ). For duplicate metagenomes, there was general agreement between the relative percentages of the mapped reads assigned to phylogenetically closely related species ( Supplementary Files 4 and 6 ). For instance, MMS_A4 and MMS_B4 constituted 24.1% and 22.8% of the mapped reads in their respective metagenomes. Microbial community from metagenome binning The deep biosphere is suggested to have cell turnover rates ranging from hundreds to thousands of years ( Hoehler and Jorgensen, 2013 ) and as a consequence it is extremely difficult to describe processes by direct measurements. With culture-independent molecular methods, these limitations can be at least partly overcome, but only very recently have there been attempts to use such information to generate hypotheses regarding the potential metabolic capacity of individual populations within complex communities ( Wrighton et al. , 2012 ). To understand how populations interact and collectively perform ecosystem processes, such information is critical. Here we partition community metagenomes into individual populations ( Figure 2 ) to provide hypotheses on the biology and metabolic strategies ( Figure 3 ) as well as potential interactions between populations ( Figure 4 ) within three water types in the terrestrial deep subsurface. The phylogeny of the dominant microbial community members from the three water types was reconstructed from nearly complete assembled population genomes ( Figure 2 and Supplementary File 7 ). Proteobacteria were retrieved in all three water types, and for both size fractions but at higher taxonomic resolution, clearly partitioned communities were observed. At the class level, α- and γ- Proteobacteria were exclusively found in the <0.22 μm cell size, whereas δ- Proteobacteria were only detected in the >0.22 μm size fraction. This division in cell sizes between the water types at the class level was also generally supported by the 16S rRNA gene tag sequencing (data not shown). The microbial communities were also partitioned by water type, where Actinobacteria were only identified from the <0.22 μm cell size old saline water. Finally, archaea were recovered from the >0.22 μm size fraction old saline metagenome, but were only distantly related to any genome in the NCBI or PATRIC database. Despite the populations in this study being from pH-neutral groundwaters, the closest match was to Archaeal Richmond Mine acidophilic nanoorganisms Candidatus Micrarchaeum acidiphilum ARMAN-2 previously identified from an extremely acidic sulfide mineral mine ( Dick et al. , 2009 ) ( Supplementary File 7 ). The metagenomes from the three water types were partitioned into draft genome bins using CONCOCT ( Alneberg et al. , 2014 ) that utilizes 36 single copy housekeeping genes to estimate the genome coverage. The presence of ≥31 of the single copy genes (suggesting a statistical average of ≥86% coverage of the genome) and no more than two duplicates of the same gene were considered a near-complete genome bin. The near-complete genome bins, representing populations, were searched for genes coding for metabolic pathways involved in electron donor utilization, electron acceptors, ability to fix carbon dioxide and nitrogen and uptake of nutrients ( Table 2 and Supplementary File 8 ). These data were then used to identify the different suggested potential growth strategies and putative population interactions within communities from the three deep biosphere water types. Metabolism in modern marine water The >0.22 μm metagenome had the highest relative percentage of reads that mapped to the bin MML_A2 that was related to Chlorobi/Ignavibacteriae (5.4% all quoted values in the sections below refer to the percentage of mapped reads from the respective metagenome). This population aligned most closely to the fermentative species Ignavibacterium album and potentially grew via fermentation or anaerobic hydrogen and ethanol oxidation coupled to electron transport via the ferredoxin:NAD + oxidoreductase Rnf complex. The recently discovered Rnf complex ( Schuchmann and Muller, 2014 ) appears to be used in many anaerobic microorganisms to couple the oxidation of organic carbon or hydrogen to NAD + (via ferredoxin) for adenosine triphosphate production at redox potentials below −320 mV. A second phylogenetic population was represented by MML_B2 (most related to Candidatus Endomicrobium sp.) that also encoded genes assigned to anaerobic hydrogen oxidation and the electron transport Rnf complex. Both of these populations have a reversible type III anaerobic, NADP-dependent hydrogenase that we suggest functions for hydrogen oxidation as the populations also contain the Rnf complex. An example of potential metabolic interactions ( Figure 4 ) is hydrogen produced as a fermentation product that can subsequently be utilized by a hydrogen oxidizing population, thus creating a cryptic hydrogen pathway, whereby any produced hydrogen would likely be immediately consumed. MML_A1 and MML_B1 (2.2% and 1.3%, respectively) from the replicate metagenomes both grouped with Candidate division OD1. Based on the number of identified single copy genes, these genome bins were estimated to have >86% genome coverage ( Supplementary File 4 ). Despite the high estimated genome coverage, only genes coding for fermentation of simple organic carbon compounds could be identified (for example, the cells appeared to lack tricarboxylic acid cycle or electron transport components). Neither carbon dioxide nor nitrogen fixation could be identified from the >0.22 μm metagenome bins. The <0.22 μm metagenome for the same water type generated 13 bins (totaling 41.5% and 41.3% in the replicate metagenomes) representing populations that were predicted to ferment pyruvate to ethanol, propionate, lactate or hydrogen. Further possible electron donors included ethanol that could be degraded to acetyl-CoA (via pathways I to IV) that was present in the majority of the reconstructed genomes. Methane is also a potential electron donor via anaerobic oxidation coupled to nitrate reduction ( Haroon et al. , 2013 ; Orcutt et al. , 2013 ) and the phylogenetically similar MMS_A3 and MMS_B3 (both related to Mesorhizobium alhagi ) that contains genes assigned as the respiratory nitrate reductase napAB (2.0% and 1.4%, respectively) and conversion of methane to methanol. However, the encoded proteins may also mediate reversed methanogenesis. The final step in conversion of one carbon (C 1 ) compounds to carbon dioxide is catalyzed by formate dehydrogenase and homologs were identified in 13 populations (45.5% and 41.0%), suggesting these species were able to grow utilizing C 1 compounds. A potential respiratory electron acceptor was nitrate that was converted to nitrite (seven bins totaling 18.9% and 17.2%), ammonia (four bins totaling 25.2% and 23.8%) or nitrogen gas (24.1% and 22.8%) as the end products. This was in agreement with the chemical signature of the marine water mass, where ammonia and nitrite concentrations were elevated ( Figure 1 ). Furthermore, five bins (16.9% and 15.8%) were suggested to fix carbon dioxide via the Calvin–Benson–Bassham (CBB) cycle and two bins (24.1% and 24.1%) to fix nitrogen. No evidence was identified in any of the water types for other carbon dioxide fixation pathways than the energetically expensive CBB cycle, suggesting alternative autotrophic processes were not dominant in the communities. Surprisingly, this included the Wood–Ljungdahl pathway that operates in conjunction with the Rnf complex in acetogenic microorganisms for autotrophic growth in thermodynamically limited environments ( Schuchmann and Muller, 2014 ). It was also surprising that genes supporting the presence of the reductive tricarboxylic acid cycle and reductive acetyl CoA pathway were not identified as these methods of carbon dioxide fixation are more prevalent in anaerobic microorganisms ( Hugler et al. , 2003 ). The Rnf complex has additional roles such as during anaerobic nitrogen fixation that may be occurring in some populations, such as MMS_A7, or to create an ion motive force for transport across the membrane ( Schuchmann and Muller, 2014 ). Finally, the presence of gene homologs in several populations to oxidize thiosulfate and reduce nitrate along with CBB genes for carbon dioxide fixation (for example, MMS_B2) suggested the potential to grow chemoautotrophically. The current paradigm for life in the deep terrestrial biosphere points toward an autotrophic system fueled mainly by hydrogen of geological origin ( Hallbeck and Pedersen, 2008 ). Our data partially support this model but also point to an important role of heterotrophic growth via organic carbon potentially recharged from the Baltic Sea over years to decades. This results in many abundant community members that seem to rely exclusively on fermentation. Metabolism in undefined mixed water Three near-complete genome bins were reconstructed from the undefined mixed water >0.22 μm metagenome. Two of these bins were phylogenetically most related to Candidate division OD1 (UML_A1) and unclassified bacteria (UML_B2). However, these bins only represented a minor portion of the community as they contributed 1.4% and 0.3% of the mapped reads, respectively. These populations also had a reduced genome size and we suggest they have a similar, simple fermentative growth strategy as described for MML_A1 and MML_B1 from the modern marine water. The third bin, UML_B1 has the suggested metabolic strategy of fermenting pyruvate to propionate, anaerobically oxidizing hydrogen, and oxidizing formate to carbon dioxide. Bin UML_B1 was also suggested to utilize nitrate reduction to nitrite and sulfate to sulfide during anaerobic respiration and fix nitrogen for cellular growth. The ability to reduce nitrate was supported by an elevated concentration of nitrite in this water type, analogous to the modern marine water. Hydrogen sulfide was strongly elevated in the undefined mixed water, despite that only a single phylogenetic bin was identified containing genes coding for the dissimilatory sulfite reductase. This may be explained by either a disproportionately high sulfate reduction activity of this population compared with sulfate reducers in the other waters (that novel, unidentified sulfate-reducing mechanisms were present) or that genomes from less abundant sulfate-reducing populations could not be assembled. A total of 15 near-complete bins were constructed from the undefined mixed <0.22 μm metagenome with a relatively uniform abundance distribution and altogether contributing 9.1% and 12.8% of the mapped reads. Of the 15 reconstructed bins, 9 were suggested to be able to ferment pyruvate to ethanol (3 bins; 3.2% and 2.6%), propionate (5 bins; 2.0% and 5.5%), lactate (6 bins; 7.4% and 4.8%) or hydrogen (2 bins; 0% and 4.2%). Eight bins had genes assigned to mediate ethanol degradation to acetyl-CoA (6.6% and 9.8%) and a further three bins were suggested to be able to further ferment the acetyl-CoA to butyrate (2.6% and 3.3%). Four of the undefined mixed populations were suggested to utilize formate. None of the bins were suggested to reduce sulfate or sulfur, but five bins were suggested to reduce nitrate to either nitrite (0.6% and 1.9%) or ammonia (3.4% and 3.6%). The phylogenetically similar UMS_A3 and UMS_B3 (2.6% and 2.6%) were most similar to Marinomonas sp. and were suggested to generate an ion motive force via the Rnf complex during heterotrophic growth. Only two populations contained genes assigned to the CBB cycle for carbon dioxide fixation (UMS_A2 and UMS_B2 related to Limnobacter sp.; both 0.6%), suggesting these species may have been sufficiently active to support the community or that novel carbon dioxide pathways were not identified. The ability to oxidize the inorganic sulfur compound thiosulfate might also allow the nitrate-reducing populations to grow chemoautotrophically. Metabolism in old saline water A total of 17 bins were identified from the old saline water >0.22 μm metagenome (totaling 23.8% and 64.3%). One of the >0.22 μm replicate metagenomes was dominated by population OSL_B1 that was most similar to Dechloromonas aromatica and contributed 57.7% of the mapped reads. For the replicate metagenome, the phylogenetically related population (OSL_A1) merely contributed 4.9% of the mapped reads. Gene homologs in these bins implied a capacity to utilize several organic carbon sources including pyruvate, acetyl-CoA, ethanol, formate and methane. A potential anaerobic terminal electron sink was nitrate reduction to ammonia or nitrogen gas coupled to generation of an ion motive force via the Rnf complex. These two populations were also suggested to fix nitrogen and carbon dioxide. The other bins in the >0.22 μm metagenome also contained populations suggested to ferment pyruvate and acetyl-CoA, degrade ethanol, oxidize formate and convert methane into methanol. In addition to the two bins most similar to D. aromatica , a further eight populations were suggested to utilize nitrate and/or sulfate as terminal electron acceptor. Despite the presence of potential sulfate-reducing bacteria, the principal component analysis suggested the old saline water was enriched with sulfate. This may be because of insufficient energy supply (electron donor inputs) to effectively drive sulfate reduction. Alternatively, the bacterial (OSL_A10 and OSL_A11) and archaeal (OSL_A2, OSL_A5, and OSL_A9) populations reduced the sulfur (but not sulfate) to sulfide. Three populations (4.9% and 60.5%) were suggested to be able to denitrify to the level of nitrous oxide or nitrogen gas that could also fix nitrogen. Eight of the old saline >0.22 μm metagenome bins contained homologs for hydrogen oxidation (13.5% and 3.0%), whereas 6 populations contained homologs for carbon dioxide fixation via the CBB cycle (6.9% and 60.5%), potentially suggesting a greater dependence on the gases hydrogen and carbon dioxide from geological origin to support growth in the deeper and older fracture waters. Finally, a population most similar to Candidate division OP11 was identified that, similar to the other detected candidate divisions, had a fermentative metabolism while lacking the tricarboxylic acid cycle and ability to respire. The <0.22 μm old saline metagenome contained 16 populations totaling 11.9% and 16.3% of the mapped reads. Of these 16 populations, 13 were suggested to ferment pyruvate to various final electron acceptors (9.5% and 14.1%); 11 had the potential to degrade ethanol (10.8% and 13.7); 7 could possibly perform formate oxidation (3.8% and 7.5%); and 1 population was suggested to be able to oxidize methane to methanol. The potential final electron acceptor was nitrate that was reduced to nitrite, ammoni, or nitrous oxide by, for example, OSS_A4 and OSS_B4 or sulfur reduction to sulfate by OSS_A6 and OSS_B6. In addition, three bins (all γ- Proteobacteria ; 0.7% to 1.9%) were suggested to be able to generate an ion motive force via the Rnf complex. In contrast to the modern marine water, the deep old saline water more closely adheres to the present metabolic model with populations growing via chemolithotrophic processes. These putative autotrophs also include unclassified and poorly understood archaeal groups, in agreement with the tendency for archaea to become more prevalent as the depth below the surface increases ( Hoehler and Jorgensen, 2013 ). Fermentative populations from candidate divisions constituted 3.5% of the mapped reads in the modern marine water compared with 0.8% in the old saline water, further pointing to the importance of heterotrophy in the younger water versus autotrophy in the old saline water. The old saline water populations were also suggested to have a greater tendency to sulfate/sulfur reduction than the shallower water types. Potential adaptations to extreme oligotrophy One feature of the communities was the apparent existence of extremely small microbes that passed the 0.22 μm membrane filter, and electron microscope observations indeed supported the presence of very small cells ( Supplementary File 5 ). These small cells included genome bins assigned to the α-, β- and γ- Proteobacteria ( Figure 2 ). The cell sizes of all the phylogenetically closest published type species related to the populations in the <0.22 μm metagenomic bins were >0.3 × 1.0 μm. Because of the small cell size, low cell density and consequent challenges in microscopic analyses, the portion of small cells (<0.22 μm) were estimated with a PCR and sequencing approach. The abundance of operational taxonomic units that were retained by a 0.22 μm filter (designated as large cells) and those that were retained by a 0.1 μm filter but not present in the large cells (designated as small cells) was quantitatively compared ( Supplementary Files 1 and 9 ). These data suggested a median percentage of 47%, 54% and 50% of the modern marine, undefined mixed and old saline communities were made up of cells that were unique to the fraction that passed the 0.22 μm filter. Because of the 0.1 μm filter size being used to select for the small cells (as compared with iron chloride precipitation), the estimated percentage of small cells may be conservative. Although these PCR-based estimates are associated with some uncertainty, the values of ∼50% small cells in the three water types warrants further investigation of their role in the deep terrestrial biosphere. An abundance of microorganisms with small cell sizes have recently been described for microbes in shallow aquifers ( Luef et al. , 2015 ), but these are the first data pointing to their existence in the terrestrial deep biosphere. Another potential adaptation to oligotrophy is reduced genome size ( Swan et al. , 2013 ; Giovannoni et al. , 2014 ). Although most of the reconstructed genomes were >1.3 Mb, a few streamlined genomes were identified. These included bins assigned to Candidate division OD1 found in the modern marine and undefined mixed waters along with Candidate division OP3 found in the undefined mixed water ( Figure 2 ). Comparing the estimated size of the reconstructed genomes to the closest matching reference genomes in the databases revealed that overall 63% of the genomes in the <0.22 μm fraction were reduced in comparison with the reference genomes in the NCBI database. One example was for the replicate populations OSS_A5 and OSS_B5 that both had genomes 37% smaller than the Microbacterium barkeri reference genome. However, there did not appear to be a trend of smaller genome sizes with depth. As a reference, the sizes of reconstructed genomes in the >0.22 μm metagenomes were on average larger than the closest matching reference genomes in the NCBI database. Assessment of potential sample contamination Many potential sources of contamination in groundwater communities are associated with drilling and deep biosphere sampling. The Äspö HRL circumvents the majority of these issues because: (1) the Äspö HRL tunnel was constructed decades ago and the studied fissures are reached by boreholes from the tunnel wall and are thus far away from an oxidizing environment and (2) the water from the boreholes flow into the tunnel, where the sampling is carried out, by gravity and therefore water-pumping activities that can induce a variety of contamination and sampling errors are avoided. However, the addition of materials to boreholes in order to enclose the targeted fissure (called ‘sections') can be a source of electron donors for the microbes ( Drake et al. , 2015 ). For this reason, three to five section water volumes were drained from the borehole to allow pristine groundwater to flow. Recently, Salter et al. (2014) presented an analysis of the impact of contamination of DNA derived from laboratory chemicals in sequence-based community analyses. This should not be a major issue in the present study as the recovered amount of DNA was high (0.17 to 2.10 μg). Nevertheless, an evaluation of potential contamination was performed, showing no evidence of reagent contamination ( Supplementary Files 10 and 11 ). In addition, in a different project with samples prepared with the same protocol, laboratory chemicals and in the same laboratory as the <0.22 μm fraction for the data reported here, none of the taxa assigned to the bins in this study were detected among contigs longer than 100 kb (data not shown). This was consistent with sample preparation or reagents used not significantly contributing to the recovered DNA from the boreholes."
} | 8,754 |
33193187 | PMC7644778 | pmc | 8,078 | {
"abstract": "The Galápagos Archipelago is located at the intersection of several major oceanographic features that produce diverse environmental conditions around the islands, and thus has the potential to serve as a natural laboratory for discerning the underlying environmental factors that structure marine microbial communities. Here we used quantitative metagenomics to characterize microbial communities in relation to archipelago marine habitats, and how those populations shift due to substantial environmental changes brought on by El Niño. Environmental conditions such as temperature, salinity, inorganic dissolved nutrients, and dissolved organic carbon (DOC) concentrations varied throughout the archipelago, revealing a diversity of potential microbial niches arising from upwelling, oligotrophic to eutrophic gradients, physical isolation, and potential island mass effects. The volumetric abundances of microbial community members shifted with these environmental changes and revealed several taxonomic indicators of different water masses. This included a transition from a Synechococcus dominated system in the west to an even mix of Synechococcus and Prochlorococcus in the east, mirroring the archipelago’s mesotrophic to oligotrophic and productivity gradients. Several flavobacteria groups displayed characteristic habitat distributions, including enrichment of Polaribacter and Tenacibaculum clades in the relatively nutrient rich western waters, Leeuwenhoekiella spp. that were enriched in the more nutrient-deplete central and eastern sites, and the streamlined MS024-2A group found to be abundant across all sites. During the 2015/16 El Niño event, both environmental conditions and microbial community composition were substantially altered, primarily on the western side of the archipelago due to the reduction of upwelling from the Equatorial Undercurrent. When the upwelling resumed, concentrations of inorganic nutrients and DOC at the western surface sites were more typical of mesopelagic depths. Correspondingly, Synechococcus abundances decreased by an order of magnitude, while groups associated with deeper water masses were enriched, including streamlined roseobacters HTCC2255 and HIMB11, Thioglobacaceae , methylotrophs ( Methylophilaceae ), archaea ( Nitrosopumilaceae ), and distinct subpopulations of Pelagibaceriales (SAR11 clade). These results provide a quantitative framework to connect community-wide microbial volumetric abundances to their environmental drivers, and thus incorporation into biogeochemical and ecological models.",
"conclusion": "Conclusion Studies of the Galápagos revolutionized our understanding of evolution and ecology by examining biological heterogeneity among terrestrial islands ecosystems. Here we show the marine waters surrounding the islands also have physical and chemical gradients that promote distinct microbial habitats within relatively close proximity. The Galápagos Archipelago thus serves as a natural laboratory for the bottom-up factors that structure marine microbial communities and lead to niche diversification, as well as the potential for certain microbial taxa to be indicators of water mass types. This work also connected volumetric abundances of microbial taxa to environmental niches, working toward a quantitative framework for incorporating microbes into ecosystem and biogeochemical models. Finally, the substantial physical, chemical, and biological shifts the archipelago experienced during El Niño serves as a model for microbial responses to a warming ocean due to climate change.",
"introduction": "Introduction Microbes mediate the flux of energy and materials through the ocean ( Moran, 2015 ), yet how environmental conditions structure marine microbial communities, and therefore the suite of biogeochemical and ecological activities they carry out, is only partially understood ( Fuhrman et al., 2015 ; Mende et al., 2017 ). The Galápagos Islands have long served as a natural laboratory to examine how environmental variation shapes community and population structure. Darwin’s observations of differences in the Galápagos terrestrial habitats and their associated fauna were critical to development of the theory of speciation through natural selection. In contrast to these terrestrial ecosystems, identifying the factors structuring marine microbial communities is less obvious given marine environments are well mixed with low barriers to nutrient and organism exchange. Yet the Galápagos Archipelago is located in a unique oceanographic setting in which several major oceanographic features intersect to create diverse marine habitats with gradients in temperature, inorganic dissolved nutrients, primary production, organic matter composition and concentration, and plankton groups in a relatively close proximity ( Jimenez, 1981 ; Liu et al., 2014 ; Campoverde et al., 2018 ) that might make it well suited for identifying marine microbial niche diversification. The archipelago consists of 18 major islands lying on the equator approximately 900 km from Ecuador ( Figures 1A,B ). Current flows across the islands are complex and include influences from the South Equatorial Current (SEC), the North Equatorial Countercurrent, and Peru current ( Schaeffer et al., 2008 ; Liu et al., 2014 ). The Equatorial Undercurrent (EUC) flows eastward along the equator and directly intercepts the Galápagos platform, generating upwelling of nutrient rich water on the western side of the archipelago. As a result, the archipelago has substantially higher rates of primary production than the surrounding oligotrophic waters of the East Equatorial Pacific ( Figure 1C ). FIGURE 1 The Galápagos Archipelago lies at the intersection of several ocean currents which create a diversity of marine habitats around the islands. (A) Map of the Galápagos platform with sampling locations marked in red and probable current flows of the South Equatorial Current (SEC, yellow arrows) and Equatorial Under Current (EUC, white arrows). (B) Location of the Galápagos Archipelago in the Pacific Ocean. (C) Chlorophyll a concentration from satellite observations (Aqua/MODIS). (D) Genovesa Island and sampling Site 14 within the partially collapsed caldera that is now Darwin bay. (E) Mixed layer temperate, salinity, inorganic nutrient, size-fractionated chl a , and primary productivity (determined by DIC uptake) data, and microbial abundances at sampled stations in 2015 and 2016. Sample site IDs are shown on the left, corresponding with IDs in (A) and divided into four main geographical regions. Microbial abundances are based on single-copy gene ( recA ) recovery from the metagenomes normalized to internal standard recovery. These oceanographic features, together with a variety of geological features ( Karl et al., 1980 ; Campoverde et al., 2018 ), are ripe for creating diverse niches that have unique microbial community compositions and functions. In a study of three Western Galápagos sites in 2014, Campoverde et al. (2018) found pronounced differences in water column properties, organic carbon pools, and microbial community composition, suggesting that there is high spatial diversity in these factors across the archipelago. Further, the islands can experience major shifts in these variables due to seasonal shifts in currents and ENSO events. During El Niño periods, warm equatorial surface water migrates east toward the islands and the EUC upwelling that supports the islands high productivity is reduced, resulting in substantial perturbation of the archipelago ecosystem ( Schaeffer et al., 2008 ). To understand how patterns in physical, chemical, and biological characteristics shape microbial community composition, we conducted a quantitative metagenomic survey of the Galápagos Archipelago microbiome. We specifically examined, (1) what microbes comprise the community, (2) how the absolute abundances of those microbes are shaped by the diverse physical and chemical setting of the archipelago, and (3) how temporal variability in physical-microbial coupling alters microbial composition. Surface samples were collected across the archipelago over a 2-year period that included the 2015/16 El Niño event. Our results indicate the strong environmental gradients across the archipelago lead to distinct microbial communities, that certain taxa can be used as indicators of water mass history and characteristics, and these communities undergo substantial shifts during El Niño events.",
"discussion": "Results and Discussion Environmental Variability Across the Archipelago Surface waters (5–10 m) spanning the Galápagos Archipelago were sampled in October 2015 and 2016 ( Figure 1A ), encompassing a range of environmental conditions ( Figure 1E ). Western stations had the coldest and most nutrient rich surface waters, owing to the upwelling of the Equatorial Undercurrent (EUC) as it collides with the archipelago platform ( Liu et al., 2014 ). Correspondingly, the western stations had high primary productivity and phytoplankton standing stocks ( Figure 1E ). By contrast, the eastern stations are relatively isolated from EUC upwelling and are more oligotrophic. Central archipelago sampling stations most often represented a middle state, although several Sites (14, 16, and 18) were notable for their high primary productivity and phytoplankton standing stocks ( Figure 1E ). Based on our hydrographic and nutrient data and the major oceanographic currents in the system, we divided the archipelago into five regions: west, north, central, caldera, and east ( Figure 1E ). Between the 2 years sampled there was substantial variability in hydrographic conditions and microbial composition ( Figure 1E ). The year of 2015 was classified as an El Niño year based on NOAA’s El Niño 1/2 index of sea surface temperature anomalies in the region that encompasses our Galápagos sites ( Reynolds et al., 2002 ; Santoso et al., 2017 ). Correspondingly, water temperatures across our sites were on average 2–4°C warmer during the 2015 El Niño than in 2016 ( Figure 1E ), with some western stations warmed by more than 7°C. Mixed layer inorganic nutrient concentrations were reduced during the 2015 El Niño, with western EUC influenced sites in particular having a 75% NO 3 and 30% PO 4 reduction ( Figure 1E ). As the system returned to a neutral, cooler state in 2016, the western site temperatures decreased and had higher salinities, both indications that EUC upwelling had returned to delivering nutrient-rich midwater to the surface ( Figure 1E ). Dissolved organic carbon concentrations were measured across the archipelago in both years ( Figure 2 ). During the 2015 El Niño, western EUC-influenced site DOC concentrations were ∼80 μM, slightly above the average of the rest archipelago, and DOC concentrations were reduced eastward and at a minimum in the north. In 2016, after the system returned to a more neutral state, the DOC paradigm was altered. DOC concentrations in the west decreased to 40–60 μM, a third less than 2015 at the same locations, while mid-island and eastern sites stayed approximately the same. FIGURE 2 Dissolved organic carbon (DOC) concentrations at stations across the archipelago collected in 2015 (gray) and 2016 (black). In general, vertical ocean DOC profiles are highly reproducible across basins and time, with surface DOC concentrations approaching 70–80 μM and decreasing rapidly to ∼40 μM in the mesopelagic ( Hansell et al., 2009 ; Medeiros et al., 2015 ). Our results in the Galápagos show much of the archipelago has typical surface-like DOC concentrations, except at the western stations where deeper water is likely being upwelled so quickly that surface primary production has yet to increase DOC standing stocks. During an El Niño year, such as observed during our 2015 sampling, reduced EUC upwelling resulted in western stations having a DOC profile more typical of open ocean surface waters. Together, the hydrographic, nutrient, and DOC data indicate that (1) there is substantial spatial variability in environmental conditions across the archipelago, and (2) El Niño had an extensive environmental effect on many of these sites, most prominently a reduction in the upwelling of nutrient rich waters at the western stations that is the main driver of primary production in this region. Below we explore how the microbial communities inhabiting these waters reflect both the spatial heterogeneity in environmental conditions and temporal dynamics likely driven by the El Niño. The Galápagos Marine Microbiome Stations across the archipelago were selected for metagenomic analysis of the free-living bacterioplankton community (0.22–3 μm size fraction; Supplementary Table 2 ). A total of 47 metagenomes were sequenced, with 23 metagenomes sequenced in 2015 (with replicates for Sites 1, 2, and 16) and 24 metagenomes in 2016 (replicated sites: 1, 4, 7, 11, 14, 16, 18, 24, and 26; see Supplementary Table 2 for complete details on read quantities and sample information). Bacterial abundances were estimated using single-copy recA read counts normalized to internal standard genome recoveries ( Supplementary Table 2 ). Individually, the three genomic standards were recovered at similar ratios within a sample ( Figure 3A ), having an average coefficient of variation of 15% ( Figure 3B ). Volumetric abundances were calculated separately for each of three internal standards for three bacterial families that are representative of abundant, minor, and rare groups and exhibited a range of abundances across the archipelago are shown in Figures 3C–E . These abundances demonstrate that variation arising from the different internal standards is minimal compared to variation between samples. Summed recA -based abundances of all bacterial and archaeal taxa produced estimates of 1.5 and 3.1 billion cells L –1 in 2015 and 2016, respectively; corresponding well with direct cell counts (1.6 and 2.2 × 10 9 cells L –1 in 2015 and 2016, respectively; Supplementary Table 1 ) and were typical of surface pelagic bacterial abundances. We then quantified bacterial community composition by binning genome equivalents at the family level ( Supplementary Table 3 ) and placing them into four categories: dominant (>10 8 cells L –1 ), abundant (>10 7 cells L –1 ), minor (>10 6 cells L –1 ), and rare (<10 6 cells L –1 ; Figure 4A ). FIGURE 3 Recovery and variation of the three internal standards and the effect on taxa volumetric abundances. (A) Recovery ratio derived from Blautia producta (red), Deinococcus radiodurans , (gold), and Thermus thermophilus (blue) internal genomic standards for the 47 metagenomes. (B) Percent coefficient of variation (%CV = standard deviation/mean × 100) of the three standards. Red dashed line shows the mean %CV of the 47s metagenomes. Volumetric abundances of three families, (C) \n Synechococcaceae , (D) \n Puniceispirillaceae (SAR116 clade), and (E) \n Thioglobaceae derived from each internal standard. Error bars denote the 95% confidence intervals (t distribution) determined from the three internal standards for each metagenome. FIGURE 4 Galápagos marine microbiome composition across the archipelago based on recA recovery and binned at the family level. (A) Volumetric abundances of all bacterial families. The top 5 families are colored as follows Pelagibacteracea , blue; Flavobacteriaceae , purple; cyanobacteria, green; Rhodobacteraceae , red. The remaining 477 families are plotted as semitransparent blue circles. The distribution of families was categorized into four groups based on their volumetric abundances: dominant, abundant, minor, and rare, and these bins are outlined by the gray and white shading. (B) Relative abundances (percent of total site recA sequences) of all bacterial families across the sampling stations. At this broad taxonomic level, the Galápagos microbiome has a typical surface-ocean community composition ( Sunagawa et al., 2015 ; Mende et al., 2017 ). Two families were consistently in the dominant bin: Pelagibacteraceae (SAR11 clade) and Flavobacteriaceae ( Figure 4 ). The abundant bin consisted primarily of Synechococcaceae , Rhodobacteraceae , Prochloraceae , and to some extent the Halieaceae , Rhodospirillaceae , Puniceispirillaceae (SAR116 clade), and Cellvibrionaceae . These top 9 families in the dominant and abundant bins contained on average 71% of total cell abundances. The minor bin contained a quarter of the 482 families identified, including diverse taxa that are consistently found at each station across both years. The rare bin contained the greatest number of families (424), but their cumulative abundances averaged <0.1% of total genome equivalents and they were often found only sporadically across time and space. The spotty detection of rare organisms is due in part to the limit of detection, which is directly related to sequence depth. In previous quantitative omics studies, the detection limit ranged from 10 5 to 10 7 genes or transcripts L –1 ( Gifford et al., 2011 ; Satinsky et al., 2014 ; Wilson et al., 2017 ), and 10 3 to 10 5 rRNA copies L –1 in quantitative amplicon studies [internal standard normalized ( Wang et al., 2018 ; Lin et al., 2019 ; Tang et al., 2019 ); flow cytometry normalized ( Wang et al., 2019 )]. In this study, an average abundance of >480,000 cells L –1 was needed to detect a recA representative in our sequence libraries ( Figures 3A , 4A orange dotted line). Variation in Community Composition Across the Archipelago and With Time A Principle Component Analysis (PCA) shows bacterial community composition substantially differed across the sites and years, correlating with several environmental conditions ( Figure 5 ). The first two PCA axes explained 41% of total variance and were strongly correlated with site location, environmental parameters, and sampling year. Axis 1 (PC1) reflected the west to east productivity gradient, with the most negative PC1 scores for eastern stations, correlating positively with temperature and negatively with salinity. PC axis 2 shows the samples clearly divided between those collected in 2015 and 2016. A PERMANOVA analysis confirmed community composition differed significantly ( p < 0.001) between the 2 years, revealing a strong temporal shift in microbial community composition likely due in part to El Niño conditions. The western sites were substantially separated from other sites in the PC analysis and western community composition was significantly different than those in other regions by the PERMANOVA analysis ( p < 0.05). The PCA analysis thus showed (1) substantial variations in community composition, (2) several taxonomic indicators of a site’s location within the Archipelago, and (3) a substantial response to El Niño served as major shift in composition between these 2 years. Below, we explore specific families that served as taxonomic indicators of a site and how their abundances changed during the 2015 El Niño. FIGURE 5 Differences in community composition across the Galápagos Archipelago. Principal components analysis (PCA) based on the recA abundances of the top 100 families in the metagenomes. Percent variance explained by each axis is shown in parentheses. Samples are colored based on year collected (2015, gold circle; 2016, blue triangle) with the site number next to the sample symbol. The bacterial family loadings are plotted with left justification. Inset: the same PCA as shown in the main plot, but with samples color-coded according to the geographic region of their collection in the archipelago. Cyanobacteria Synechococcus and Prochlorococcus made up the majority of cyanobacteria (97% of cyanobacteria genome equivalents) and have a distinct spatial distribution across the archipelago, going from a Synechococcus dominated system in the west to an even mix of Prochlorococcus and Synechococcus in the southeast ( Figure 6 ). Notably, this relative evening results from Prochlorococcus absolute abundances increasing eastward, while Synechococcus cell densities remain consistently high. These cyanobacterial populations are likely major contributors to primary production in the archipelago, given that the <5 μm size-fraction constituted a large fraction of total primary production, especially in the non-western stations and during El Niño ( Figure 1E ). FIGURE 6 Abundances and composition across the archipelago of select taxa within (top) the cyanobacteria, (middle) the Roseobacter clade, and (bottom) Flavobacteriaceae genera in 2015 (left) and 2016 (right) . The color bar at the bottom of the graph denotes a station’s geographic region as shown in Figure 1E . High abundances of Synechococcus were detected at two separate sites in 2015. Site 14 is located on Genovesa Island within Darwin Bay, a partially collapsed caldera with a sill that restricts interactions with the surrounding ocean ( Figure 1D ). Synechococcus reached 9 × 10 8 cells L –1 in the caldera, becoming the most abundant bacterioplankton in the community. Supporting these molecular observations, high chlorophyll a concentrations were measured here, the majority of which was in the small size fraction (<5 μm; Figure 1E ). While Synechococcus abundances in Darwin Bay were slightly reduced in 2016 compared to 2015 (4 × 10 8 cells L –1 ), the site still had some of the highest Synechococcus densities measured in 2016 ( Figure 6 ). The western sites experienced order of magnitude shifts in Synechococcus abundances between the 2 years. In 2015, Synechococcus were dominant community members in the west, second in abundance only to SAR11 clade members. The highest 2015 Synechococcus abundances were detected at Site 2 (10 9 cells L –1 ; Figure 6 ). In 2016, when EUC upwelling was restored, cyanobacteria densities decreased substantially at western stations, with Synechococcus decreasing to 0.3 × 10 7 cells L –1 and Prochlorococcus to 0.05 × 10 7 cells L –1 at Site 7, a three order of magnitude drop relative to Site 1 and the largest abundance change between years observed in our dataset ( Figure 6 ). SAR11 As is common for marine systems, SAR11 clade members were dominant components of the archipelago community ( Giovannoni, 2017 ). Pelagibacteraceae was consistently the most abundant family, averaging 14% of genome equivalents and average densities of 2–5 × 10 8 cells L –1 ( Figure 4 ). The only instance Pelagibacteraceae was not a dominant community member was in 2016 at western Sites 5 and 7 during normal upwelling conditions. While SAR11 was consistently abundant across the sites, we detected distinct populations across the archipelago. We examined the distribution of metagenomic read recruitment to the 20 SAR11 reference bins available in the RefSeq database ( Figure 7 ). The Pelagibacter ubique bin was always the dominate reference bin, recruiting an average of 70% of all Pelagibacteraceae metagenome reads, followed by strains RS39 and HIMB59 making up ca. 6% each, and then by a series of SAR11 genomes whose proportion of read recruitment is highly stable across the archipelago. However, in 2016, at the western upwelling stations (Sites 3, 4, 5, 7) and Site 24, there is a distinct shift in the rank order recruitment driven by increased recruitment of several single cell amplified genomes originally obtained from oxygen minimum zones ( Tsementzi et al., 2016 ). This suggests that at actively upwelling sites, the SAR11 community contains unique populations harboring functional genetic potential for dealing with relatively low oxygen and deep-water nutrient conditions. FIGURE 7 Differential metagenome read recruitment to SAR11 clade reference bins across the archipelago. For each sampling station, the rank order of 20 SAR11 clade reference bins available in NCBI RefSeq v84 is shown in each column and colored from top recruiting (blue) to lowest recruiting (red). Grayed columns indicate no metagenomes were acquired at the site that year. Roseobacters Members of the Rhodobacteraceae family primarily belonging to the Roseobacter clade were highly abundant across sites (∼10 8 cells L –1 ; Figure 4 ) and binned to diverse taxa (479 reference genomes belonging to >100 genera). Roseobacter abundances substantially increased at EUC upwelling sites in 2016 to become dominant members of the community. These increases were primarily driven by three populations: HTCC2255, HIMB11, and SB2 ( Figure 6 ), which accounted for 40–60% of all Rhodobacteraceae genome equivalents in the west. Rhodobacteraceae HIMB11 and SB2 are closely related [termed the CHAB-1-5 strains by Billerbeck et al. (2016) ], while Rhodobacteraceae HTCC2255 lies on the distant evolutionary branches of the roseobacters in the NAC11-7 clade ( Suzuki et al., 2004 ; Newton et al., 2010 ; Zhang et al., 2016 ). A comparative genomic study grouped these three strains together with several other Roseobacters prominent in open ocean environments and termed them the Pelagic Roseobacter Cluster [PRC, ( Billerbeck et al., 2016 )]. CHAB 1–5 strains HIMB11 and SB2 were prominent members of the Roseobacter community across all sites in both years, with typical cell abundances >10 6 L –1 . By contrast, HTCC2255 was most often a rare community member. In 2015, HTCC2255 was below our detection limit for 17 out of 23 samples (<3 × 10 5 L –1 , Figure 6 ). However, in 2016, HTCC2255 cell abundances increased from undetectable at Site 1 to >10 8 cell L –1 at EUC upwelling Sites 4, 5, and 7; this was 100-fold higher than at the central archipelago stations it was also detected at in 2016. In addition to our observations, HTCC2255 is prominent at several sites around the world that have similar steep topographies and upwelling. Phylogenomic analysis by the Genome Taxonomy DataBase ( Parks et al., 2018 ) places HTCC2255 into the Amylibacter genus, whose type strain, Amylibacter marinus , was isolated from surface waters experiencing strong upwelling with a steep topography off the coast of Muroto, Japan ( Teramoto and Nishijima, 2014 ). HTCC2255 has also consistently been found to be enriched in surface waters of Monterey Bay, CA, United States ( Ottesen et al., 2011 ; Varaljay et al., 2015 ) that has a similar steep topography and periods of intense upwelling. Together, these findings suggest that HTCC2255 may have a niche for recently upwelled deep waters, potentially thriving on a combination of increased inorganic nutrients and solar radiation availability. HTCC2255 is notable for its phylogenetic placement at the base of the Roseobacter phylogeny and its streamlined lifestyle ( Luo and Moran, 2014 ). While most roseobacters have large genomes with diverse metabolic and regulatory capabilities, HTCC2255 has a relatively small genome (half the size and number of genes typical of roseobacters), and a relatively restricted set of metabolic capabilities and transcriptional regulators ( Newton et al., 2010 ; Luo and Moran, 2014 ) suggestive of a more specialist, oligotrophic lifestyle ( Giovannoni et al., 2014 ; Billerbeck et al., 2016 ). While most Roseobacter genomes lack photo-driven supplemental energy conservation or use aerobic anoxygenic phototrophy, HTCC2255 is one of the only Roseobacter genomes to contain a proteorhodopsin ( Newton et al., 2010 ; Sun et al., 2017 ). Flavobacteria The other consistently dominant family in the Galápagos microbiome was the Flavobacteriaceae . Like Roseobacters, Flavobacteriaceae reads binned to a diversity of genomes (578 reference genomes belonging to >80 genera). Cosmopolitan and abundant flavobacteria included the Flavobacteria sp. MS024-2A (notable for its streamlined lifestyle), as well Nonlabens and Arenibacter genera. EUC upwelling-enriched genera found in 2016 but not 2015, include Formosa species and substantial enrichment (>100-fold increase) of Tenacibaculum and Polaribacter spp. ( Figure 6 ). Notably, while Tenacibaculum and Polaribacter were consistently found at all sites and times, the specific reference genomes recruiting reads at the EUC sites were hardly detectable at other sites, indicating these particular populations have functional capabilities adapted to deepwater or recently upwelled, nutrient rich environments. Ottesen et al. (2011) also found Polaribacter species were substantially enriched in the upwelled waters of Monterey Canyon. Interestingly, we also detected flavobacteria taxa that were distinctly enriched in the eastern stations, most prominently Leeuwenhoekiella which was one of the few good heterotrophic indicators of Galápagos oligotrophic habitats ( Figure 6 ). While enrichment of Leeuwenhoekiella sp. was spatially segregated from Polaribacter and Tenacibaculum in the Galápagos along the east-west mesotropic-oligotrophic gradient, this does not likely reflect a streamlined lifestyle given that Leeuwenhoekiella , Polaribacter , and Tenacibaculum reference genomes are relatively large and have metabolic capabilities typical of a generalist lifestyle; future work is therefore needed to identify the specific genome characteristics that lead to the clear niche differentiation among these flavobacteria. Several other groups were substantially enriched at the upwelling sites in 2016 and relatively deplete at oligotrophic eastern sites ( Figures 5 , 8 ). Notably, these families could be divided into two groups, one enriched primarily at EUC upwelling Sites 3 and 4 south of Fernandina Island, and the other at EUC Sites 5 and 7 north of Fernandina ( Figure 5 ). Thioglobaceae and Methylophilacea ( Spietz et al., 2019 ) were a minor component of the community in 2015, but in 2016 increased by greater than 10-fold at sites of strong upwelling (Sites 3, 4, 5) and eastern Sites 18 and 24, while reduced by almost 100-fold again at the far eastern stations. Archaea were relatively rare in our metagenomes, as expected given samples were collected in the upper 5–10 m of the water column and archaea are primarily abundant below the euphotic zone ( Karner et al., 2001 ; Santoro et al., 2019 ). The most abundant Archaeal family in our data set was the Nitrosopumilaceae , which was undetectable in all but four 2015 samples, but become enriched in 2016 at sites 3, 4, 18, and 24 ( Figure 8 ). Taken together, the Thioglobaceae , Methlophilaceae , and Nitrosopumilaceae served as good markers of deep-water intrusion to the surface layer. FIGURE 8 Abundances of Thioglobaceae , Methlophilacea , and Nitrosopumilaceae across the Galápagos Archipelago. The color bar at the bottom of the graph denotes a station’s geographic region as shown in Figure 1E . Synthesis Environmental conditions such as dissolved inorganic nutrients, DOC concentrations, and other hydrographic parameters differed substantially throughout the archipelago, and quantitative metagenomics revealed shifts in the absolute abundances of the microbial communities that correlated with these changes, producing key taxonomic indicators of the archipelago habitats. From these results we can assemble a model of microbial niche diversification across the Galápagos. During a neutral, non-El Niño year, surface microbial communities on the western edge of the archipelago are strongly influenced by EUC upwelling. Our initial expectation was that nutrient rich upwelled EUC water would drive high primary production and stimulate growth of bacterioplankton typically associated with phytoplankton blooms ( Teeling et al., 2012 ). However, our data suggests intense EUC upwelling rates result in the surface waters immediately bordering the western islands where we sampled to have deep-water characteristics, including high inorganic nutrient and low DOC concentrations typical of the mesopelagic. Correspondingly, the bacterioplankton community at these sites are enriched in deeper water taxa, including archaea and Thioglobus , as well as several other Roseobacter and Flavobacteria taxa previously associated with deep water upwelling ( Ottesen et al., 2011 ; Varaljay et al., 2015 ). Roseobacter HTCC2255 was a particularly strong indicator of deep-water injection, an observation that fits with a potentially distinct niche for this group for rapidly upwelled waters. Even within the cosmopolitan SAR11 clade, western upwelling stations were enriched in deep-water, oxygen minimum zone SAR11 genome-types. Together, this indicates that the western archipelago bacterioplankton communities have not had the surface exposure time needed to develop compositions typically of the upper euphotic zone. Fine-Scale Habitat Diversity The combination of surface exposure time and complexity of upwelled EUC flow around the archipelago creates fine scale heterogeneity in microbial composition at the western stations. Even western sites in close proximity can have different conditions and community compositions, as exemplified by sites south and north of Fernandina Island. South Fernandina sites (Sites 3, 4) had the coldest temperatures, highest salinities and inorganic nutrient concentrations, and lowest DOC concentrations, and were enriched in deep-water like populations such as Thioglobus , archaea, and SAR11 strains. However, north of Fernandina Island (Sites 5, 7), DOC concentrations increased while cyanobacteria and SAR11 populations declined substantially. This area had distinct bacterial communities enriched in roseobacters, flavobacteria, and gammaproteobacteria bacteria, many previously associated with phytoplankton blooms ( Teeling et al., 2012 ). Correspondingly, north of Fernandina Island large cell phytoplankton biomass and DOC concentrations are slightly higher than south, and inorganic nutrient concentrations are drawn down within the mixed layer ( Figure 1E ). Together these data suggest that the northwestern sites are receiving waters that have been exposed to the surface longer, and thus may have higher abundances of eukaryotic phytoplankton and their associated microbial communities sustained on a more abundant and labile DOC pool. In a 2014 study at three western archipelago sites in proximity to ours, Campoverde et al. (2018) observed relatively high DOC concentrations (∼92 μM) when temperatures in the west were elevated above typical conditions. This fits with our 2015 observations that warmer western waters had elevated DOC concentrations more typical of surface ocean concentrations. Notably, while our 2015 western sites were significantly warmer than the 2014 observation, the DOC concentrations did not reach the mean 92 μM observed by Campoverde et al. (2018) supporting the authors hypothesis that while temperatures were elevated in 2014, there was still upwelling influence resulting in enhanced phytoplankton production and associated DOC production. Together, both this study and Campoverde et al. (2018) suggest that DOC concentrations are highly heterogenous at the western sites and emphasize the need to better understand the lability of those DOC pools particularly in relation to water mass history. Further emphasizing the complex fate of EUC upwelled waters is Site 1, just south of Isabela Island, which had different DOC and microbial characteristics than all other western sites, suggesting that EUC flow hadn’t reached this site or is deflected by westerly flowing surface currents. Future work is needed to better understand the fate of EUC waters and their microbial communities as they are advected across the archipelago. What is clear though, is that the environmental conditions and microbial community composition of the western archipelago are substantially altered by El Niño, including warmer waters, a reduction in deep-water nutrient injection, DOC concentrations more typical of the epipelagic, and increased prevalence of taxa typically associated with surface ocean oligotrophic communities. At the other end of the archipelago, waters surrounding the eastern islands act as oligotrophic endmembers, characterized by lower nutrient concentrations, surface like DOC profiles, and microbial community compositions typical of open ocean ecosystems. Most cells at eastern sites belonged to the SAR11 clade and cyanobacteria. In contrast to the western sites, Prochlorococcus is the dominant cyanobacteria in the east, although Synechococcus abundance remains high. While roseobacters and flavobacteria were prevalent in the east, they were composed largely of cosmopolitan, oligotrophic ecotypes, such as CHAD-1 and MS024-2A members. Notably, our work showed flavobacteria Leeuwenhoekiella seems to occupy a distinctly eastern niche, of interest due to the large genome and copiotrophic lifestyle often associated with this group. The eastern sites were seemingly less affected by El Niño, at least in comparison to the major hydrographic and microbial shifts observed in western sites. Within the broader archipelago patterns, we observed fine scale habitat diversity, a good example being Darwin Bay located in Genovese Island’s partially collapsed caldera (Site 14; Figure 1D ). A ∼10 m deep sill at the mouth of the bay reduces mixing of caldera water with the surrounding ocean, trapping nutrients and microbial biomass, resulting in some of the highest primary production and phytoplankton biomass measurements we observed ( Figure 1E ). Correspondingly, nitrogen and phosphate concentrations are relatively reduced in the caldera, with moderate DOC concentrations, and Synechococcus reaching some of the highest abundances we observed. Interestingly, the caldera did not have a highly distinct bacterioplankton community. High primary production and reduction in horizontal advection by the sill may lead to hypoxic or anoxic conditions in the caldera’s deep water. Future work characterizing the chemistry and biology of Darwin Bay’s deep waters is needed to determine the fate of its organic matter and microbial community. A Potential Island Mass Effect Several central and eastern archipelago stations were anomalous in their nutrient and microbial characteristics in comparison to nearby sites in the same region ( Figure 1E ). In 2016, Site 18 located northwest of Santa Cruz Island was enriched in Roseobacters (particularly HTCC2255), Thioglobus , and Methylophilacea . Similarly, Site 24 located northwest of Española Island, was also enriched in Thioglobus , Methlophilacea , deep-water SAR11 genome-types, and a notable increase in Thaumarchaeota . Site 24’s microbial community clustered more with the northwestern stations in our PCA analysis and had decreased DOC concentrations (63 μM). These taxa and environmental conditions are more characteristic of western sites receiving deep-water injection from EUC upwelling. Island wake-induced primary production may explain these stations’ anomalies. In the season we sampled, there are consistent winds coming from the southeast, which likely sets up island wakes on the leeward sides of the islands. Islands wakes are known to induce ‘mass effects’ in which eddies on the leeward side enhance mixing and deep-water nutrient injection and increased primary production ( Hasegawa et al., 2009 ; James et al., 2020 ). Based on our microbial and environmental observations, as well as historical satellite chlorophyll measurements ( Figure 1C ), we hypothesize that island wakes are contributing to surface nutrient injection and increased microbial activity on the leeward side of several of the Galápagos Islands, such as Española and Santa Cruz (Sites 18, 24). These island wakes may be another important mechanism supporting primary production and structuring microbial communities, and future work is needed to understand the magnitude of their influence in the Galápagos Archipelago. Conclusion Studies of the Galápagos revolutionized our understanding of evolution and ecology by examining biological heterogeneity among terrestrial islands ecosystems. Here we show the marine waters surrounding the islands also have physical and chemical gradients that promote distinct microbial habitats within relatively close proximity. The Galápagos Archipelago thus serves as a natural laboratory for the bottom-up factors that structure marine microbial communities and lead to niche diversification, as well as the potential for certain microbial taxa to be indicators of water mass types. This work also connected volumetric abundances of microbial taxa to environmental niches, working toward a quantitative framework for incorporating microbes into ecosystem and biogeochemical models. Finally, the substantial physical, chemical, and biological shifts the archipelago experienced during El Niño serves as a model for microbial responses to a warming ocean due to climate change."
} | 10,215 |
23848955 | null | s2 | 8,079 | {
"abstract": "The social soil bacterium, Myxococcus xanthus, displays a variety of complex and highly coordinated behaviours, including social motility, predatory rippling and fruiting body formation. Here we show that M. xanthus cells produce a network of outer membrane extensions in the form of outer membrane vesicle chains and membrane tubes that interconnect cells. We observed peritrichous display of vesicles and vesicle chains, and increased abundance in biofilms compared with planktonic cultures. By applying a range of imaging techniques, including three-dimensional (3D) focused ion beam scanning electron microscopy, we determined these structures to range between 30 and 60 nm in width and up to 5 μm in length. Purified vesicle chains consist of typical M. xanthus lipids, fucose, mannose, N-acetylglucosamine and N-acetylgalactoseamine carbohydrates and a small set of cargo protein. The protein content includes CglB and Tgl outer membrane proteins known to be transferable between cells in a contact-dependent manner. Most significantly, the 3D organization of cells within biofilms indicates that cells are connected via an extensive network of membrane extensions that may connect cells at the level of the periplasmic space. Such a network would allow the transfer of membrane proteins and other molecules between cells, and therefore could provide a mechanism for the coordination of social activities."
} | 352 |
31708944 | PMC6819368 | pmc | 8,080 | {
"abstract": "Recent evidence for intimate relationship of plants with their microbiota shows that plants host individual and diverse microbial communities that are essential for their survival. Understanding their relatedness using genome-based and high-throughput techniques remains a hot topic in microbiome research. Molecular analysis of the plant holobiont necessitates the application of specific sampling and preparatory steps that also consider sources of unwanted information, such as soil, co-amplified plant organelles, human DNA, and other contaminations. Here, we review state-of-the-art and present practical guidelines regarding experimental and computational aspects to be considered in molecular plant–microbiome studies. We discuss sequencing and “omics” techniques with a focus on the requirements needed to adapt these methods to individual research approaches. The choice of primers and sequence databases is of utmost importance for amplicon sequencing, while the assembly and binning of shotgun metagenomic sequences is crucial to obtain quality data. We discuss specific bioinformatic workflows to overcome the limitation of genome database resources and for covering large eukaryotic genomes such as fungi. In transcriptomics, it is necessary to account for the separation of host mRNA or dual-RNAseq data. Metaproteomics approaches provide a snapshot of the protein abundances within a plant tissue which requires the knowledge of complete and well-annotated plant genomes, as well as microbial genomes. Metabolomics offers a powerful tool to detect and quantify small molecules and molecular changes at the plant–bacteria interface if the necessary requirements with regard to (secondary) metabolite databases are considered. We highlight data integration and complementarity which should help to widen our understanding of the interactions among individual players of the plant holobiont in the future.",
"conclusion": "Conclusion The emergence of molecular techniques over the last decades has considerably improved and sped up the analysis of plant-associated microorganisms, e.g., i) deep understanding of A. thaliana roots microbiome ( Bulgarelli et al., 2012 ; Lundberg et al., 2012 ) and ii) identification of key bacterial taxa and genes involved in suppression of a fungal root pathogen ( Mendes et al., 2011 ). However, remaining challenges include: i) understanding the high diversity of plants and their microbiome, ii) assembling useful databases, iii) inherent limitations and error in molecular techniques, iv) moving from model systems to the field. A promising approach to understand reciprocal effects of plants, and their microbiota lies in disassembling plant microbiomes and establishing synthetic microbial communities for reconstitution experiments to study interspecies and intraspecies interactions ( Vorholt et al., 2017 ; Duran et al., 2018 ). Here, the use of genome-sequenced and fully characterized species would allow for predicting functional interrelations that could be tested in experiments under gnotobiotic conditions. Due to the high diversity of plants and their sequencing and assembly challenges ( Schatz et al., 2012 ) few plant genomes have been sequenced and well analyzed, while many public plant genome sequences are still represented as a draft. Therefore, experiments conducted in model plants, such as A. thaliana , will still help in establishing computational and database resources ( Genomes Consortium. Electronic address and Genomes, 2016 ), from which information can be transferred to other plants ( Busby et al., 2017 ). Furthermore, the 10,000 Plant Genomes Project has the potential to reduce this limit by sequencing representative species from every major clade of embryophytes, green algae, and protists ( Cheng et al., 2018 ). Long-read DNA sequencing techniques (PacBio, Nanopore) are expected to improve the quality of genome and metagenomic-derived sequences and will overcome the binning and assembly limitation in samples with high richness. Despite the differences in the plant microbial community based on plant species, soil, and environment, it is very important to study if core microbiome functions specific to phyllosphere and rhizosphere exist and, if so, to understand interaction mechanisms between core microbes and plants. These insights will be challenged by our understanding of microbiome contributions to plant health and the development of applications in agriculture. With the reduced cost of sequencing a huge amount of omics data from plant microbial community can be expected. However, there is so far no plant microbiome specific database where species or strains could be stored together with the information about plant and environmental condition. The development of such databases needs to be prioritized to enable the functional and ecological interpretation of the upcoming large-scale multi-omics plant microbiome data."
} | 1,229 |
32655517 | PMC7325975 | pmc | 8,081 | {
"abstract": "The overwhelming majority of studies examining environmental change deliver treatments abruptly, although, in fact, many important changes are gradual. One example of a gradually increasing environmental stressor is heavy metal contamination. Essential heavy metals, such as copper, play an important role within cells of living organisms but are toxic at higher concentrations. In our study, we focus on the effects of copper pollution on filamentous soil fungi, key players in terrestrial ecosystem functioning. We hypothesize that fungi exposed to gradually increasing copper concentrations have higher chances for physiological acclimation and will maintain biomass production and accumulate less copper, compared to fungi abruptly exposed to the highest copper concentration. To test this hypothesis, we conducted an experiment with 17 fungal isolates exposed to gradual and abrupt copper addition. Contrary to our hypothesis, we find diverse idiosyncratic responses, such that for many fungi gradually increasing copper concentrations have more severe effects (stronger growth inhibition and higher copper accumulation) than an abrupt increase. While a number of environmental change studies have accumulated evidence based on the magnitude of changes, the results of our study imply that the rate of change can be an important factor to consider in future studies in ecology, environmental science, and environmental management.",
"introduction": "Introduction Most ecosystems are subjected to anthropogenic and natural environmental drivers that can represent stressful changes for biota. The effects of anthropogenic stressors have been largely studied by investigating responses to different magnitudes of stress. However, other temporal characteristics of stress may be equally important ( Ryo et al., 2019 ). For instance, experiments typically focus solely on the intensity of change, often without taking the rate of change into account. Different rates of environmental change can have diverging impacts on ecological systems ( Klironomos et al., 2005 ; Siteur et al., 2016 ), yet the potential importance of the rate of change remains largely unexplored. Repeated or continuous contamination of a site can lead to a gradual increase in the contaminant concentration in ecosystems over time ( Komárek et al., 2010 ; Ballabio et al., 2018 ). Soil and groundwater contamination is currently one of the greatest concerns related to soil resources in Europe and across the globe ( Tóth et al., 2016 ). Heavy metal contamination is the most common type of soil and groundwater contamination in Europe (35% and 32%, respectively, of contamination cases in Europe) ( Science Communication Unit and University of the West of England, 2013 ). For example, copper has been used extensively as a fungicide in agriculture, the wood industry, and other fields of human activity for more than three centuries ( Karunasekera, 2017 ). In addition, this type of contamination is practically irreversible, because unlike organic compounds, heavy metals cannot be degraded, only potentially immobilized or extracted by hyperaccumulating organisms (e.g., plants and fungi). Copper plays an important role within the cells of living organisms – it is a cofactor of proteins, a component of metalloenzymes ( Nevitt et al., 2012 ) and is needed for homeostatic maintenance. However, a tightly coordinated orchestration of uptake, distribution, and efflux in cells is needed ( Prohaska, 2008 ) to prevent toxic effects at higher concentrations. An excess of copper ions can cause fatal cell damage ( Eaton and Hale, 1993 ; Karunasekera, 2017 ) due to its binding to functional groups, replacing cations, inducing oxidative stress ( Zhang et al., 2015 ), and affecting the membrane transport system ( Cervantes and Gutierrez-Corona, 1994 ; Karunasekera, 2017 ). These changes inside of fungal hyphae, induced by an excess of copper, can lead to reduced fungal biomass production. Given the abovementioned physiological mechanisms, the rate of copper concentration increase in the environment must be critical for fungal growth and copper uptake. Nonetheless, so far, the overwhelming majority of experimental studies on the effects of environmental change use treatments that are delivered abruptly, although in fact, many important changes in the environment are gradual in nature ( Gomaa and Azab, 2013 ). In our study, we selected a set of 17 filamentous fungal strains comprising three fungal phyla (Ascomycota, Basidiomycota, and Mucoromycota) which were isolated from the same soil. These fungi are abundant in their ecosystem, are culturable, and show high versatility in trait expression ( Andrade-Linares et al., 2016 ; Lehmann et al., 2019 ). We focus on the effects of copper on filamentous soil fungi, key players in terrestrial ecosystems functioning ( Went and Stark, 1968 ) by virtue of their role in biogeochemical cycling and immobilization of toxicants ( Brookes, 1995 ; Giller et al., 1998 ). With this set of fungi, we here test the hypothesis that fungi exposed to a gradual increase in copper concentration will have a greater chance for physiological acclimation to copper stress and will show higher biomass production and lower copper accumulation. For this, we investigate in an experiment how the rate of copper application (gradual vs. abrupt) affects fungal biomass and copper accumulation. In a second step, we wish to investigate with these data, (1) if fast-growing strains are more at risk to experience biomass reduction compared to slow-growing strains and if this effect is more pronounced under abrupt copper application; (2) we investigate the impact of the rate of copper application on the trade-off between biomass production and copper accumulation. This relationship reflects stress-response strategies of fungi, which can differ depending on the individual properties of the isolates and type of treatment.",
"discussion": "Discussion Contrary to our hypothesis, as well as some other experimental findings ( Sivaprakasam et al., 2008 ), that typically abrupt environmental changes are more harmful than gradual ones, surprisingly, the isolates showed diverse responses to the treatments, rather than responding uniformly. One plausible explanation for the diverse effects of the treatments on biomass production among the isolates could be that a fast-growing fungus (i.e., having a higher biomass production in the control) had already accumulated higher biomass before application of the treatments and then slowed down growth, and therefore the rate of copper addition intrinsically affected these isolates less strongly. Conversely, a slow-grower is more sensitive to the different treatment application rates. Thus, variability of the effect sizes (biomass) is related to the growth strategy of the isolates. Nevertheless, the growth rate does not explain the difference in effect sizes (biomass) between the gradual and abrupt treatments and did not introduce a bias. We highlight that the dose-day approach we used here, arguably a reasonable approach to compare different rates of change, inevitably entails a difference in the timing of treatments (see Supplementary Figure S1 ). This is necessary to achieve equity of the overall dose. This means that the gradual treatment begins to affect fungi earlier during their growth phase. Nonetheless, for the majority of fungal isolates, including fast-growing ones, mycelial growth was noticeably inhibited by both copper treatments; thus, the exact growth phase in which the treatment was started did not affect the outcome here. Results of the current study also showed that way of copper delivery had a strong effect on copper accumulation by fungal mycelium – it was noticeably higher in the gradual treatment. Possibly, at the early stages of the gradual treatment, fungal cell structures were partly damaged (for example, by copper-induced reactive oxygen species) and when the copper concentration reached the maximum, cells were not able to efficiently apply resource-consuming resistance mechanisms for reducing copper uptake ( Prabhakaran et al., 2016 ). This could explain higher copper accumulation under the gradual copper treatment. Nevertheless, it is important to take into account that accumulation of copper is not an exclusively adaptive and metabolism-dependent process ( Turnlund, 1998 ; Viraraghavan and Srinivasan, 2011 ). A passive mechanism of accumulation plays an important role and includes binding of copper ions to the cell wall ( Viraraghavan and Srinivasan, 2011 ). This process could also explain higher accumulation of copper under the gradual treatment, which implies longer exposure to stress. The final dose of copper was always the same among the treatments; thus, the difference in accumulation is caused by the difference in stress delivery. In the current study, we also looked at the correlation between biomass production and copper accumulation. In our opinion, the relationship between effect size (biomass) and effect size (copper accumulation) represents various response strategies employed by fungi under gradual and abrupt stress. Fungi can have diverse strategies to deal with stress: energy and nutrients can be redirected from mycelial growth to defense and homeostasis maintenance in different ratios. There are a number of “costly” heavy metal defense mechanisms – active efflux of heavy metal ions ( Bruins et al., 2000 ), antioxidant production ( Sánchez, 2017 ; Khan et al., 2018 ), vacuolar metal compartmentalization ( Hall, 2002 ), metallothionein production ( Zhang et al., 2003 ), and excretion of copper-binding agents ( Ross, 1975 ; Jarosz-Wilkolazka and Gadd, 2003 ; Anahid et al., 2011 ). In our study, it was noticed that some fungi (RLCS05, RLCS32, and RLCS12) were producing pigments as protection from heavy metal-induced oxidative stress ( Gmoser et al., 2017 ) and did so differently for the abrupt and gradual treatment. The abovementioned resistance mechanisms can be applied by fungi singly or in various combinations ( Bruins et al., 2000 ; Iram et al., 2009 ). For example, Fusarium solani – a species complex, which includes isolate RLCS12, is able to produce a number of metabolites, including ergosterol, which protects the cells from oxidative stress ( Sánchez, 2017 ; Khan et al., 2018 ) and thiols, which, when excreted, form complexes with copper ions ( Brown and Hall, 1990 ). If we assume that there are two ways to use resources – growth and mentioned costly defense mechanisms (for example, an active copper efflux), then we can distinguish four potential strategies or response types of dealing with copper stress: fungi can (a) show extensive growth, but at the same time accumulate high amounts of copper, e.g., invest resources in growth, possibly trying to escape from the stressful environment; (b) show extensive growth and accumulate low amounts of copper, e.g., be naturally more tolerant and being able to invest resources into copper excretion; (c) show strong inhibition of growth and accumulate high amounts of copper, e.g., be naturally more sensitive to copper stress and not being able to continue growth, nor actively defend against copper stress; (d) show strong inhibition of growth, but accumulate low amounts of copper, e.g., invest the resources into defense, not into biomass production. In the current study, we observed that even though the responses of individual isolates were diverse, the association between effect size (biomass) and effect size (copper accumulation) was positive in both treatments ( Figure 4 ), meaning that isolates for which biomass was not reduced by treatments tended to accumulate more copper. Although the slope of the regression line does not differ between the treatments, the positive correlation between ES biomass (biomass reduction) and ES copper accumulation was stronger for the gradually than for the abruptly treated one. Also, according to our observations, fungi employed abovementioned response strategies (a), (b), and (d) and some isolates applied different strategies to deal with abrupt and gradual treatments. We can conclude that contrary to our hypothesis, conventional wisdom, and previous findings, gradual application of copper overall did not result in better performance in filamentous fungi, and indeed the responses we observed differed widely among the different isolates. Our study was focused on documenting response patterns across a broad suite of fungal isolates. A next step would be to deepen our understanding of the effects of gradual and abrupt copper pollution on filamentous fungi, by elucidating underlying response mechanisms. Some studies report that adaptive strategies can vary at the molecular level ( Lindsey et al., 2013 ; Bleuven and Landry, 2016 ). The effect of differences in the rate of change is largely understudied. It is advisable for studies in stress ecology and ecotoxicology to apply a wider range of treatment scenarios (with different rates of change) to fill this important gap. A better understanding of the temporal nature of stress and response is important to predict how environmental changes, including drivers of global change, affect organisms, communities, and functioning of ecosystems ( Ryo et al., 2019 )."
} | 3,324 |
34910518 | PMC8673773 | pmc | 8,082 | {
"abstract": "Stretchable photodetectors for wearable electronics maintain a high level of performance when stretched by at least 60%.",
"introduction": "INTRODUCTION As technology evolves, the demand for interfaces that connect the digital and physical worlds continues to increase. Wearables, the Internet of Things, soft robotics, and many other emerging technologies use flexible optoelectronics to develop intelligent surfaces that combine sensors, computation, and communication. However, when objects are soft, their surface deforms under stress, i.e., when they experience strain, and flexibility is no longer sufficient to ensure mechanical compliance or ergonomics. Photodetectors are an important class of sensors that generally benefit from having large photoactive areas that are sensitive to strain. Since the surface of soft objects experiences strain under normal conditions, stretchable photodetectors are expected to provide a roughed sensor platform that could find multiple applications for skin-mounted health monitors such as photoplethysmogram sensors ( 1 , 2 ), sensors mounted on the surface of living organisms such as plants for smart agriculture, sensors for artificial skin ( 3 , 4 ) and soft robotics ( 5 – 7 ), electronic eyes on curvilinear surfaces ( 8 ), and sensors for asset tracking, gesture, and motion recognition ( 9 ) mounted on packaging, produce, furniture, or textiles among many others. Device architectures that heterogeneously integrate rigid optoelectronics with soft and stretchable substrates by using strain relief features such as stretchable interconnect remain the most common approach to achieve stretchable optoelectronics ( 6 , 10 ). The complex fabrication of such stretchable optoelectronics could be eased by the use of elastomeric semiconductors, but reports on such materials remain scarce. By elastomeric, it is meant that semiconductor layers have viscoelastic properties, with a low Young’s modulus and a large strain at break. Organic materials provide an attractive route to achieve elastomeric semiconductors because their properties can be engineered by design ( 11 ). For instance, conjugated polymers with long side-chain groups can dissipate strain energy through the amorphous regions while preserving the integrity of charge transport through the more ordered regions ( 12 – 14 ). Another approach is to blend a polymer semiconductor with a soft elastomer matrix [e.g., polystyrene-block-poly(ethylene-ran-butylene)-block-polystyrene, SEBS] to form self-assembled polymer nanofibers inside the elastomer. Such an approach yielded elastomeric organic field-effect transistors with field-effect charge mobility values up to 1 cm 2 V −1 s −1 at a strain value of 100% ( 15 ). Despite recent progress in the development of elastomeric semiconductors, organic photodiodes with elastomeric bulk heterojunction (e-BHJ) photoactive layers showing a small electronic noise have not been demonstrated yet. BHJ photoactive layers require a blend of π donor– and π acceptor–like molecules forming a BHJ morphology to facilitate exciton dissociation and enable efficient photogeneration of charge carriers and efficient carrier extraction. To date, most BHJs cannot be considered skin-like elastomers because even if some are somewhat stretchable, they have large Young’s modulus ( E ) values in the range between ca. 200 MPa and 1 GPa ( 16 – 18 ), which are at least one order of magnitude larger than typical values for human tissues (<30 MPa) ( 19 – 21 ) and, with a few exceptions ( 22 , 23 ), strain at break values smaller than 10% ( 17 ). Despite showing limited mechanical properties, stretchable organic photodiodes (OPDs) based on these BHJs have been demonstrated in the context of photovoltaics ( 18 ) by using prestrained substrates ( 24 ), moderately stretchable BHJ ( 23 , 25 ), or all-polymer BHJ ( 26 , 27 ). To date, stretchable OPDs used in photovoltaics do not retain their performance under illumination beyond strain values ca. 50%, with one notable exception sustaining 100% strain but having a high E of 5.5 GPa ( 23 ). Recently, a ternary blend of polydimethylsiloxane (PDMS), a donor polymer, and a nonfullerene acceptor yielded a high E value of 990 MPa, maintaining a normalized power conversion efficiency of 86.7% up to a strain of 20% ( 28 ). Because these devices were tested for photovoltaic applications, their characteristics in the dark or at low irradiance values were not reported. In the context of photodetection, stretchable OPDs have been demonstrated using conventional BHJ materials by laminating complete devices onto a prestrained substrate. These stretchable OPDs were tested under compressive strain in the context of pulse oximetry ( 2 , 3 ), but the characterization of their performance parameters was limited to measurements of their dark current density values (in the range of 0.1 to 10 μA cm −2 under reverse bias) and their responsivity (ℜ max = 0.144 A W −1 ) under 100 mW cm −2 simulated solar illumination ( 2 ). As recently discussed ( 29 , 30 ), accurate characterization of the performance parameters of a photodetector requires direct measurement of its electronic noise in the dark, as well as a direct measurement of its noise equivalent power (NEP). The electronic noise is defined as the root mean square value ( I rms ) of the current fluctuations ( I dark [ t ]) around the average current value measured in the dark ( I ¯ dark ). Values of I rms are not expected to be limited by shot noise current values when electric measurements are carried out at low-frequency bandwidth values and, consequently, cannot be accurately calculated from steady-state dark current versus voltage characteristics typically reported in the literature. The NEP is defined as the average optical power ( ϕ ¯ ) required to generate an average photocurrent ( I ¯ ph ) with an amplitude that is equal to I rms , i.e., with a signal-to-noise ratio ( SNR = I ¯ ph / I rms ) of 1. Measured NEP values allow the specific detectivity to be calculated as D * ≡ A PD B / NEP , where A PD is the device area and B is the measurement bandwidth. D * is the most common performance metric used to compare different photodetector performance, but the use of approximations in calculating its value can be inaccurate. This is particularly true if the responsivity, i.e., the ratio I ¯ ph / ϕ ¯ , measured at a high optical power is assumed to be independent of the magnitude of the optical power ( 29 , 30 ). For these reasons, calculating performance metrics from reported steady-state current values and measurements at high optical power values is unreliable. Here, we report that a blend of the elastomer SEBS, the donor polymer poly(3-hexylthiophene-2,5-diyl) (P3HT), and the acceptor Indene-C60 bisadduct (ICBA) yields a skin-like e-BHJ with a low E and a high strain at break, comparable to those of SEBS. Although pristine P3HT:ICBA BHJ layers are not elastomeric, this BHJ has enabled OPDs with a level of performance that is comparable to that of low-noise silicon photodiodes (SiPDs) ( 29 ). Here, we demonstrate that stretchable OPDs using this previously unidentified e-BHJ show dark current density values smaller than 600 pA cm −2 under reverse bias, but more importantly from a photodetector perspective, a measured median root mean square electronic noise in the tens of femtoampere range and measured NEP values at 653 nm between 13 and 24 pW at strain values up to 60%, yielding D * values in the 10 10 Jones range.",
"discussion": "DISCUSSION This study demonstrates that stretchable OPDs based on e-BHJs with skin-like mechanical properties can yield a low electronic noise and a high level of performance. Tensile testing on the freestanding film of e-BHJ yields a tensile modulus of 2.4 MPa and a strain at break of 189%, which are within the range of values found in human tissue. Using an e-BHJ, OPDs fabricated on a rigid substrate show low electronic noise values in the tens of femtoampere range and a measured NEP of 39 pW at 653 nm and a corresponding peak D* value of 5.3 × 10 10 Jones at 560 nm. The NEP value of e-BHJ OPDs is larger than that achieved by state-of-the-art P3HT:ICBA OPDs, because devices with an e-BHJ show a smaller responsivity. This is in part because the addition of SEBS at 50 weight % (wt %) reduces the absorption of light in an e-BHJ by at least 50% when compared to a pristine BHJ. In addition, there is a significant reduction of the responsivity values when the optical power is smaller than around 1 nW, which may be due to the presence of traps. Despite these shortcomings, e-OPD based on prestrained PEDOT:PSS and EGaIn electrodes exhibit NEP values in the tens of picowatts range and D* values in the 10 10 Jones range at 653 nm and retain these values up to a strain of at least 60%. While it is clear that further optimization of material composition, selection of donor and acceptor moieties in the BHJs, and device geometry could be carried out, these results constitute a proof-of-principle demonstration of low-noise e-OPDs that combine the mechanical properties of skin-like elastomers while approaching the remarkable performance of rigid organic photodetectors. This unique combination of properties could enable a myriad of new applications by enabling the seamless integration of optoelectronics with soft materials."
} | 2,343 |
36771682 | PMC9920363 | pmc | 8,085 | {
"abstract": "Plants in coastal ecosystems are primarily known as natural sinks of trace metals and their importance for phytoremediation is well established. Salvadora persica L., a medicinally important woody crop of marginal coasts, was evaluated for the accumulation of metal pollutants (viz. Fe, Mn, Cu, Pb, Zn, and Cr) from three coastal areas of Karachi on a seasonal basis. Korangi creek, being the most polluted site, had higher heavy metals (HM’s) in soil (Fe up to 17,389, Mn: 268, Zn: 105, Cu: 23, Pb: 64.7 and Cr up to 35.9 mg kg −1 ) and S. persica accumulated most of the metals with >1 TF (translocation factor), yet none of them exceeded standard permissible ranges except for Pb (up to 3.1 in roots and 3.37 mg kg −1 in leaves with TF = 11.7). Seasonal data suggested that higher salinity in Clifton and Korangi creeks during pre- and post-monsoon summers resulted in lower leaf water ( ΨW o ) and osmotic potential at full turgor ( ΨS o ) and bulk elasticity ( ε ), higher leaf Na + and Pb but lower extractable concentrations of other toxic metals (Cr, Cu, and Zn) in S. persica . Variation in metal accumulation may be linked to metal speciation via specific transporters and leaf water relation dynamics. Our results suggested that S. persica could be grown on Zn, Cr and Cu polluted soils but not on Pb affected soils as its leaves accumulated higher concentrations than the proposed limits.",
"conclusion": "5. Conclusions This study revealed that S. persica could remove multiple trace elements along with salts. Salvadora persica may be effectively grown on soils polluted by Zn, Cr, and Cu. Since most of the metals are phytostabilized and do not exceed toxic levels, leaves may be used for edible purposes, except for Pb, which was higher than the normal suggested limits. Therefore, on Pb-polluted soils, the plant may be solely used for phytoremediation while avoiding it for edible purposes. Based on the metal specificity of the species, extensive lab studies with molecular insights would further enhance bio-monitoring programs for saline and polluted wastelands in a sustainable way.",
"introduction": "1. Introduction Trace metal pollution is known to alter the quality of air, water, and soil, making the environment undesirable as it is a major threat to ecosystems and human society [ 1 , 2 ]. In the modern era, the assessment of potential chemical toxins released from wastewater has gained attention [ 3 ]. Research on hazards caused by trace metal contamination and solid waste management is essential for systemic health effects [ 2 ]. Several methods have been suggested to prevent the entry of heavy metals into the food chain, including the use of chemicals, e.g., surfactants, rhamnolipid solutions, etc., [ 4 ], despite their detrimental effect on the environment. Moreover, soil salinity has also increased the problem of food production in agricultural settings [ 5 ]. In view of vegetation destruction, contamination in terrestrial and aquatic ecosystems, and the ever-increasing human population, food security has become a major challenge for sustainable development goals (SDGs) [ 6 ]. The release of toxic chemicals in the natural environment by anthropogenic activities could supplement their entry into edible plant products beyond recommended limits which is a major concern for human health disorders [ 7 ]. Moreover, the enrichment of soils with heavy metals also brings about changes in soil physio-chemical characteristics, which may decrease the growth and productivity of economically important crops [ 8 ]. For cleaning soils that are contaminated with trace metals, various methods are being practiced, e.g., soil solidification, chemical leaching, soil oxidation, and reduction, etc., yet these methods are expensive and detrimental to the environment [ 3 ]. Phytoremediation is a sustainable approach in the sense that it does not require chemicals for cleaning hence rendered environmentally safe [ 6 ]. Therefore, phytoremediation as a cost-effective green technology is suggested. Phytoremediation of salts using halophytes is gaining special attention for its environment-friendly method [ 9 ]. However, recent studies suggested that halophytes growing in coastal areas may also be used for phytoremediation of polluted lands as some of them use similar physiological strategies for removing metals [ 8 , 10 ]. Salt-resistant halophytes of the coasts could play an important role in metal absorption and translocation, thereby helping clean metal-polluted soils [ 11 ]. Studies suggested that halophytes can resist heavy metals, for example, Cd, Pb, Zn, Cu, etc. [ 8 , 12 , 13 , 14 , 15 ]. However, reports on cross-tolerance mechanisms of heavy metals with salinity are scant. Ecophysiological studies on salt and metal resistance of Atriplex atacamensis [ 16 ], Suaeda maritima [ 17 ], Tamarix gallica [ 18 ], etc., indicated the phytoremediation ability of halophytes. Moreover, halophytes for important bioactive metabolites with commercial value may be cultivated for food, fodder, forage, fuel, and medicinal crops on saline lands [ 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 ]. Hence, halophytes can be used as alternative crops and may be potential candidates for phytoremediation [ 19 ]. However, careful selection of species is needed as some of them may accumulate higher concentrations of trace metals in their edible parts, more specifically in leaves [ 20 ]. Plants with normal permissible limits of metals in leaves and other edible parts, such as seed/fruit, etc., may be used as food, fodder, etc., but those with toxic levels of metals are not advisable to be used [ 21 ]. Several halophytes belonging to different taxa have the potential to remediate soils polluted with trace metals as well [ 21 ]. Recent research articles mainly focused on perennial plants with higher above-ground biomass that may be harvested from time to time [ 10 , 22 ]. However, tree crops may also provide great opportunities for their economic potential besides serving the purpose of phytoremediation. Salvadora persica L. is a facultative halophyte that normally grows in semiarid regions of the Middle East [ 23 ] and can survive in highly saline lands along coastal regions [ 24 ]. This species has the ability to grow and adapt to different habitat types (dunes, Sabkha, and marshes) and can resist frequent tidal inundations near the coasts [ 24 ]. Salvadora persica could grow well in up to 25 dS m −1 (about 250 mM NaCl) under natural conditions [ 24 ] and is classified as a salt-accumulating species [ 25 ]. In Pakistan, S. persica L., grows all along the Indus plain and sandy desert tracts of coastal and near coastal areas of Sindh and Baluchistan [ 26 ]. This plant has traditionally been used as medicine for various ailments like asthma, cough, rheumatism, scurvy, etc. [ 27 ]. Its tender leaves are used as salad and pickles in Pakistan [ 25 ]. The fruit is also edible with a sweet taste, considered carminative and diuretic, and has stomachic properties. Twigs of this plant are used as miswak for cleaning teeth [ 28 ]. The potential of S. persica for the phytoremediation of salts is well established [ 28 , 29 ]. Its immense value as a potential seed oil crop is also well known [ 24 , 25 , 26 , 27 , 28 , 29 , 30 ]. Roots of S. persica are typically known to remove wastewater metals (Cd, Pb, Zn, Cu, Ni, As, etc.) due to their high adsorption capacity [ 31 , 32 ]. However, there are few reports on both salt and metal tolerance of this tree as a non-conventional crop [ 33 ]. Studies on the metal tolerance of S. persica under field conditions and their bio-concentration (BCF) and translocation (TF) factors are scant. Therefore, understanding the fate of trace metals in plant tissues is of crucial importance for ascertaining phytoremediation. This study aimed to evaluate the phytoremediation potential of S. persica to six trace metals (Pb, Cr, Cu, Fe, Mn, and Zn) and its water relation dynamics under fluctuating salinity in field conditions. Three coastal areas (Sandspit, Clifton, and Korangi creek near the Industrial area) were selected ( Figure 1 ). Seasonal fluctuations (winters, pre-monsoon summers, and post-monsoon summers) in metal concentration and BCF and TF in S. persica were recorded. The following hypotheses were tested: (1) Heavy metal accumulation in S. persica would be seasonal and site-specific (2) Spatio-temporal changes in soil salinity would alter the shoot metal accumulation in S. persica .",
"discussion": "4. Discussion Plants of the littoral zones can survive under salt and metal stress [ 8 , 45 ], and they bear different mechanisms to cope with seasonal fluctuations in the environment [ 10 ]. In this study, we tried to elucidate the phytoextraction ability of trace metals in Salvadora persica under fluctuating soil salinity and metal composition in different seasons. Some of the soil physiochemical parameters, e.g., organic matter (OM), bicarbonates (HCO 3 ), and extractable metal concentrations (Mn, Zn, Cu, Pb, etc.), suggested that Korangi creek was the most polluted site, followed by Clifton and Sandspit, as has been reported in earlier findings [ 10 ]. The major cause of the increased level of pollution at Korangi creek is its closest vicinity (about 1 km) to the industries, which outpours waste material into the Malir river and carries it to coastal zones via several streams [ 10 ]. An average of ~350 MGD (million gallons per day) outflow from the Malir river directly into the sea has been reported in earlier studies [ 10 , 36 ]. On the other hand, Sandspit beach is about 4 to 5 km away from the S.I.T.E (Industrial area), mostly affected by sewage dumping and some of the tanneries near Mauripur [ 8 ]. Although soil salinity in terms of EC and Na + increased at Clifton and Korangi in post-monsoon summers, generally lower values of metals in S. persica soil (except Zn and Pb at Korangi) may either be related to plant uptake or dilution effect owing to the tidal influx/rain runoff [ 10 , 46 , 47 ]. In the first instance, salinity (EC) could result in metal chloro-complexation, which generally causes enhanced biosorption of metals by plant roots [ 48 ]. Moreover, the soil pH did not deter metal adsorption as it remained similar (alkaline) throughout the study period (7.2–8.4), as reported in the literature [ 10 , 32 ]. It is generally believed that some of the root exudates may also cause changes in soil metal bioavailability [ 6 ]. However, metal transfer from root to shoot system requires specific transporters [ 14 ] along with water relation dynamics of the plant [ 8 ]. Nevertheless, it is important to identify strategies employed by plants for metal biosorption and their phytoextraction potential, as well as for efficient decontamination of polluted soils [ 6 , 49 ]. However, the use of halophyte plants with higher metal concentrations is not advisable for edible purposes [ 21 ]. Nevertheless, if any plant could grow and phytostabilize such metals while restricting shoot metal translocation below toxic levels, it may be recommended for edible purposes with added benefits of soil remediation [ 50 , 51 ]. Among the tested heavy metals in S. persica , root Fe was the highest in winter (919 mg kg −1 ), which exceeded the normal plant limit (450 mg kg −1 ) [ 50 ] at Sandspit, where tannery waste is disposed of [ 10 ]. However, at Clifton and Korangi, higher root Fe was noted in summer, which may be related to excessive outflow under the tidal influence or formation of root iron plaques. A higher influx of metals into the root system is known to be associated with specific Fe metal transporters [ 51 ]. However, TF > 1 for Fe at Sandspit and Clifton also showed subsequent translocation to leaves. Iron (Fe) concentrations in leaves were found under acceptable limits and never crossed beyond toxic (>600 mg kg −1 ) levels in any season on all study sites. Root Mn was also the highest in pre-monsoon summers with <1 BCF on all study sites but never exceeded the permissible limit of 50 mg kg −1 in any season [ 49 , 50 , 51 ]. Both Fe and Mn are micronutrients and are essentially needed by components of plant antioxidant enzymes in several physiological and biochemical functions [ 52 , 53 , 54 ]. If found well within the suggested ‘normal ranges’, Fe and Mn could be beneficial for plant growth, otherwise damaging in the case of toxic concentrations [ 54 ]. Similarly, Zn is also a micronutrient that could be helpful in chlorophyll synthesis and plant growth within standard permissible ranges [ 50 ]. The adequate level of Zn is <20 mg kg −1 [ 55 ], while the maximum limit is up to 60 mg kg −1 [ 50 ]. In this study, Zn in both the root and leaf remained <60 in S. persica in all seasons on all study sites, although leaf Zn markedly decreased in summer with increases in soil salinity. Among other tested metals, Cu and Cr serve as co-factors for certain enzymes [ 56 , 57 ] and are involved in many redox reactions [ 10 ]. However, at the functional level, the toxicity of Cu in plants (with >40 mg kg −1 ) is still unclear [ 10 ], except that it may lead to stunted growth in many crops [ 58 ]. Lead (Pb), on the other hand, is thought to be a non-essential element for plant growth [ 59 ]. Therefore, the standard Pb range is 0.3 to 0.6 mg kg −1 of dry weight, and values higher than this range could prove toxic for many plants [ 60 ]. In this study, S. persica consistently accumulated Cu well within acceptable ranges but with preferably higher extractable concentrations in roots than leaves. Furthermore, the transport of Cu to leaves also decreased with the increases in soil salinity during summer (pre- and post-monsoon). The accumulation of Pb in both roots and leaves was consistently higher than their normal limits as described above. The higher Pb in S. persica roots during post-monsoon summers may be attributed to Pb binding at the root surface during high tides [ 61 , 62 , 63 ]. However, the higher leaf Pb in winter at Sandspit and Clifton in pre-monsoon summers could be a result of the symplastic transport to shoot, possibly due to the immobilization of Pb by root cell wall components [ 64 ]. Salt-accumulating species are known to have a higher leaf Pb, and S. persica appears no different from other coastal halophytes [ 65 , 66 , 67 ]. Chromium (Cr) is also a non-essential metal, serving as a co-factor for a few enzymes [ 68 ] if found in concentrations <5 mg kg −1 [ 50 ]. Negi [ 69 ] reported Cr in leaves up to 23 mg kg −1 in S. persica ; however, in this study, the highest leaf Cr was 3.37 at Sandspit in winter. Despite the same report, the leaf Pb was up to 54 mg kg −1 in S. persica ; in our case, it ranged between 1.1–4.66 mg kg −1 during different seasons. Apparently, S. persica leaves accumulated only Pb among tested metals with higher values than the suggested (0.6 mg kg −1 ) limit. Leaf Na + content increased during pre- and post-monsoon summers in S. persica at Clifton and Korangi creeks along with the Pb. Higher Na + content in leaves with exceptionally higher TF (5–10) indicated that S. persica is a Na + hyperaccumulator, though increased leaf succulence may help in resisting salt stress [ 70 , 71 , 72 ]. Moreover, the higher leaf K + in both summer seasons and maintained leaf Na/K (~4–7) ratio in S. persica suggested efficient osmotic adjustments [ 24 , 29 ]. It is also reported that the increased leaf succulence further enhances Na + sequestration in the vacuolar compartment carrying along with it certain metals [ 73 , 74 , 75 ]. Salt secretors, on the contrary, efficiently remove salts along with Pb in the apoplast which may be excreted out through specialized glands [ 76 ]. In this aspect, salt accumulators seem to adapt similar physiological and biochemical traits for salt and metal stress. However, vacuolar sequestration of Pb in S. persica requires experimental evidence. Low leaf water potential (more negative) at full turgor ( ΨW o ), as well as at turgor loss point ( ΨTLP ) and bulk elastic modulus in samples collected from Clifton and Korangi during winters, pointed towards a decreased cell hydraulic capacitance. Hydraulic capacitance seemed to increase with the onset of summers on both sites with the increase in soil salinity [ 72 ]. Changes in water relations are known to trigger the regulation of aquaporin gene expression, which may indirectly contribute to reductions in water loss [ 77 ]. Furthermore, the deposition of metals in cell walls could result in their thickening (increased bulk elasticity), which may cause reduced rates of water movement via the vacuolar continuum [ 77 ]. Marginal increases in bulk elasticity during winters in S. persica indicated deposition of some metals, e.g., Cr, Cu, and Zn, which were lower in leaves during summers. These findings suggested that seasonal and spatial increases in soil salinity could have promoted decreasing metal transfer to S. persica foliage. Increases in soil salinity are also associated with the increase in some of the proteinogenic amino acids (e.g., Glutamine, Aspargine, etc.), and these are potentially known to be metal chelators [ 28 ]. Although it is not confirmed, the decreased metal transfer may also be associated with such kinds of active chelators among other metal transporters. It may be summed up that seasonal flux in extractable trace metal may be related to water relation dynamics besides metal speciation associated with specific transporters. However, further elaborative experiments are needed with an emphasis on dose-dependent salt and metal stress in halophyte trees such as S. persica . In view of trace metal selectivity, lab trials to check the extent of metal tolerance should be designed for more realistic and applicable measures. Moreover, since the fruit of S. persica is also edible, it would be interesting to know the extent of trace metal accumulation, which has not been reported in prior studies. This study has also provoked us to ask a few more questions: (1) How does the salinity affect the transport of different metals to shoots via root, especially in tree halophytes? (2) What anatomical differences are caused at root and leaf levels for metal transport under saline conditions? (3) Is there any proteinogenic amino acid involved that promotes metal chelation, thereby affecting metal transfer? Information on metal-binding proteins/transporters at the root and leaf level would help improve bioremediation processes to get rid of toxic metals from the soils."
} | 4,647 |
28949325 | PMC5739006 | pmc | 8,086 | {
"abstract": "Massive biofilms have been discovered in the cave of an iodine-rich former medicinal spring in southern Germany. The biofilms completely cover the walls and ceilings of the cave, giving rise to speculations about their metabolism. Here we report on first insights into the structure and function of the biofilm microbiota, combining geochemical, imaging and molecular analytics. Stable isotope analysis indicated that thermogenic methane emerging into the cave served as an important driver of biofilm formation. The undisturbed cavern atmosphere contained up to 3000 p.p.m. methane and was microoxic. A high abundance and diversity of aerobic methanotrophs primarily within the Methylococcales ( Gammaproteobacteria ) and methylotrophic Methylophilaceae ( Betaproteobacteria ) were found in the biofilms, along with a surprising diversity of associated heterotrophic bacteria. The highest methane oxidation potentials were measured for submerged biofilms on the cavern wall. Highly organized globular structures of the biofilm matrix were revealed by fluorescent lectin staining. We propose that the extracellular matrix served not only as an electron sink for nutrient-limited biofilm methylotrophs but potentially also as a diffusive barrier against volatilized iodine species. Possible links between carbon and iodine cycling in this peculiar habitat are discussed.",
"conclusion": "Conclusions Here the Sulzbrunn spring cave is described as a unique habitat for microbial biofilm growth. Although the cave is situated just several meters below the surface, microbial communities largely independent from surface carbon and energy inputs were discovered. In contrast to our initial expectation, biofilm microbiota were surprisingly diverse, with a host of populations closely related to well-known methanotrophs, methylotrophs and also potentially iodine-cycling bacteria. These findings provide further evidence for the relevance of subterranean methane sinks by microbes ( McDonough et al. , 2016 ; Lennon et al. , 2017 ). We propose that the massive extracellular polymeric substance production observed could serve as an electron sink for the nutrient-limited and therefore growth-limited methylotrophs. Although these first insights into an apparently unique subsurface biofilm system are very intriguing, many open research questions remain. The application of 13 C-labeled methane and methylotrophic substrates in combination with nucleic acid-based stable isotope probing is currently ongoing and will help to further unravel the complex patterns of carbon and energy sharing to be expected within the biofilms. Future research should also address the spatial organization and metagenomic repertoire of biofilm microbiota, as well as the possible role of Archaea , Protozoa , phage and fauna, in the food web of this ecosystem apparently dominated by prokaryotes.",
"introduction": "Introduction Natural microbiota often organize as biofilms, where structural features and microbial interactions give rise to an enhanced ability of biofilm microbiota to be active and persist under challenging environmental conditions. Extensive biofilm production has been previously reported mostly for energy-rich surface water systems dominated by phototrophic primary production ( Battin et al. , 2016 ) or in engineered water systems ( Boltz et al. , 2017 ). In subsurface and groundwater systems, biofilms are largely considered oligotrophic ( Griebler and Lueders, 2009 ; Ortiz et al. , 2014 ). Nonetheless, a number of caves and karstic systems have been reported to host biofilms rich in microbial diversity and with elevated, mostly lithotrophic biogeochemical activities ( Holmes et al. , 2001 ; Engel et al. , 2010 ; Jones et al. , 2010 ; Rusznyák et al. , 2012 ; Barton et al. , 2014 ; Riquelme et al. , 2015 ). In this study, we report on an exceptionally extensive and massive biofilm formation that has recently been discovered in a semiartificial cave of a historic medicinal spring in Sulzbrunn ( Schott, 1858 ), situated in prealpine southern Germany. Subaerial and submersed microbial biofilms completely cover the walls and ceiling of this seminatural cave ( Figure 1 ), giving rise to extensive pendulous, mucous structures of up to 15 cm in length also known as snottites ( Hose and Pisarowicz, 1999 ). To date, microbial snottites have mostly been described to harbor low-diversity communities of lithotrophs in acidophilic, thermophilic or sulfidic habitats ( Bond et al. , 2000 ; Holmes et al. , 2001 ; Northup et al. , 2003 ; Jones et al. , 2010 ; Ziegler et al. , 2013 ). Such extreme conditions do not seem to prevail in Sulzbrunn. Thus our objective was to understand the primary biogeochemical drivers of this peculiar microbial habitat. The Sulzbrunn cave is located in the Allgäu Alps (Bavaria, Germany) at an altitude of 875 m above sea level. The cave lies in a well-jointed sandstone of the Weissach-Schichten of the subalpine Lower Freshwater Molasse. Within a radius of 18 km from Sulzbrunn, natural gas has been repeatedly observed to emerge from deep drill holes that reach Tertiary formations of the subalpine Molasse. The porous sandstone of Bausteinschichten from the Lower Marine Molasse is identified as a reservoir for migrating hydrocarbons. The subjacent organic-rich clays are a potential source of brines with high iodine concentrations ( Hesse and Schmidt-Thomé, 1975 ). Water enters the cave in the form of upwelling mineral spring water, as well as percolating seepage water. Under normal hydraulic regimes, this semiartificial cave is approximately half-filled with water, with the water level controlled by a simple overflow system. Historic ( Schott, 1858 ), as well as recent water analyses (LfU—Bavarian Environment Agency, personal communication 2014), report high iodine loads of up to 23 mg l −1 emerging with the mineral spring water, which mixes with recent meteoric groundwater in the spring cavern. These high iodine levels, which exceed regular freshwater concentrations by a thousand-fold ( Whitehead, 1984 ), as well as elevated salinity in the mineral spring water, are an indicator of upwelling formation water, which has been in contact with oil- and gas-laden sediment deposits ( Lu et al. , 2015 ). The sources of hydrocarbons in the subalpine Molasse basin are autochthonic, originating from mesozoic sediments ( Hiltmann et al. , 1999 ) overthrusted by Molasse formations during the alpine orogeny. Fossilized algal biomass is typically highly enriched in iodine, which has been found at concentrations of up to 150 mg l −1 in a drilled artesian well in the area (LfU, personal communication 2014). In Sulzbrunn, the sediments of the Lower Marine Molasse are situated >1000 m below the surface. It can be assumed that the upwelling of iodine-rich waters occurs together with natural gases seeping from deeper hydrocarbon formations along deeply penetrating fault systems. Although the microbiota of marine gas seeps have been intensively investigated ( Ruff et al. , 2015 ; Paul et al. , 2017 ), comparably little information is available about such systems in the terrestrial subsurface. Aerobic methanotrophs and biofilms have been previously found in groundwater and drinking water systems, where they can be involved in the oxidation of methane or methylated compounds ( Newby et al. , 2004 ; Stoecker et al. , 2006 ). The Movile Cave in Romania, receiving deep thermal waters rich in hydrogen sulfide ( Sarbu et al. , 1996 ), also hosts microbial mats of active methanotrophs ( Hutchens et al. , 2004 ; Chen et al. , 2009 ). Recently, the role of microbial methane oxidation within cave and karst ecosystems has been addressed globally ( Fernandez-Cortes et al. , 2015 ; McDonough et al. , 2016 ; Lennon et al. , 2017 ). Methane-driven communities can comprise a multitude of interactions between methanotrophs, methylotrophs and heterotrophs ( Beck et al. , 2013 ; Kalyuzhnaya et al. , 2013 ; Oshkin et al. , 2015 ; Paul et al. , 2017 ). Energetic constraints imposed by the various pathways of carbon assimilation under low concentrations of oxygen and methane have been shown to trigger substantial exopolysaccharide production in methanotrophs ( Linton et al. , 1986 ; Strong et al. , 2015 ), which could potentially explain such massive biofilm production. The appearance and uniform distribution of the snottites ( Figure 1 ) pointed toward the use of a gaseous substrate for growth. Thus we posit that deep gaseous energy inputs emerging with the upwelling water, possibly light alkanes or methane, could be a major driver of biofilm formation in the Sulzbrunn cavern. We hypothesize that the snottites, as well as subaerial and submersed biofilms, on the wall should be dominated by a low diversity of autotrophs capitalizing on the available energy inputs. The compartmentalization of the cave and possible distinctions in substrate supply should be reflected in distinct biofilm subtypes, substrate turnover rates and isotopic signatures. Finally, we ask whether possible links between methane and iodine cycling can be inferred for this peculiar microbial habitat.",
"discussion": "Discussion Methane as the driver of biofilm formation Here we provide first insights into the biogeochemistry and microbiology of a peculiar biofilm system discovered in prealpine southern Germany. We show that deep formation water enters the spring cave together with appreciable amounts of methane, as indicated by the elevated mixing ratios of methane in the water and atmosphere of the cave. Carbon isotope signatures clearly identified the methane as thermogenic in origin ( Aelion et al. , 2009 ), consistent with the well-established presence of fossil deposits and gas reservoirs in this region of the subalpine Molasse ( Hiltmann et al. , 1999 ; Etiope, 2009 ). In Sulzbrunn, the seeping gas can be speculated to actually lift up the deep briny mineral water that ascends into the cave. Although seeping gas bubbles have been reported to induce porewater flow velocities of up to several meters per day in coastal seeps ( O'Hara et al. , 1995 ), further investigations will be necessary to delineate the hydrogeological setting in Sulzbrunn. End member mixing calculations based on water isotopes showed that the influx of deep formation water contributed roughly 40–50% to the spring water in Sulzbrunn. It is likely that this mixing of distinct water inputs, at least in part, contributes to the definition of the unique biogeochemical system in the cave. Despite the detection of low amounts of oxygen directly in the mineral spring water ( Table 1 ), we assume the upwelling formation water to be anoxic, and oxygen exposure or mixing with more aerated surface water to take place only in the last meters before entering the cave. Were the mineral spring water aerated, we would have expected to detect a high abundance of aerobic methanotrophs in these samples, which was not the case. Apart from methane, inputs of DOC into the cave via the different water fluxes seemed negligible. Still, comparably low amounts of DOC in seeping surface water have been shown to support appreciable populations of heterotrophic bacteria in caves ( Ortiz et al. , 2014 ). Also, we cannot exclude potential seasonality in DOC inputs from the surface, which might have been missed during our time points of sampling. The unambiguous δ 13 C signature identified thermogenic methane to be the main driver of biofilm formation, especially for the submersed biofilms. As shown above, this had the highest methane oxidation rates and methanotroph/methylotroph abundance. The CH 4 consumption rates of up to 25 μmol g biofilm FW −1 day −1 were >4 orders of magnitude higher than rates recently reported for the water column above methane seeps in Lake Constance ( Bornemann et al. , 2016 ) and in a similar high range as reported for other methane-venting geothermal sites ( Gagliano et al. , 2016 ; Lennon et al. , 2017 ). Upscaling this for biofilm mass estimates in the cave, a potential methane turnover of ~1.6 mol day −1 (~35.8 l CH 4 day −1 ) can be extrapolated for the submersed biofilms alone. Methane oxidation rates were unfortunately not determined for the mixed cave water in this study. The high abundance of methanotrophs in the water ( Figure 5 ) and the reduced oxygen concentrations compared with surface seepage water ( Table 1 ) suggested that at least part of the methane oxidation could also have been allocated to the water body itself. However, the much lower total bacterial abundances in the water ( Supplementary Figure S1 ) combined with a steady discharge and thus purging of lotic populations could still result in biofilms being the most relevant for total methane turnover. In contrast to submersed biofilms, the δ 13 C signature of subaerial biofilms and snottites less directly pointed toward thermogenic methane as being their main carbon input. However, the isotopic signatures of CH 4 and CO 2 in the cave atmosphere were both substantially heavier than directly in seeping gas ( Figure 2 ), suggesting strong stable isotope fractionation ( Preuss et al. , 2013 ) to occur during oxidation between the compartments. The placement of the aerial biofilms at approximately −31‰ δ 13 C in between the signature of both gaseous end members in the cave atmosphere indicated an equal importance of both methanotrophy and autotrophic or heterotrophic CO 2 fixation for biofilm buildup, as previously inferred for other biofilms in caves ( Sarbu et al. , 1996 ; Chen et al. , 2009 ). Nevertheless, the lower methane oxidation rates and lower abundance of potentially C 1 -oxidizing microbes both seem to point toward a possible role of electron donors other than methane in aerial biofilms. This will be discussed further down. The interpretation of observed nitrogen isotope signatures in biofilms was not possible due to the lack of defined input signals. The depleted δ 15 N isotope values of the submersed biofilms (−11‰) were comparable to values found in Movile Cave biofilms ( Sarbu et al. , 1996 ). The much higher values of aerial biofilms suggested distinct inputs, possibly connected to the known capacity of many methanotrophs to fix atmospheric dinitrogen ( Knief, 2015 ). Nevertheless, the major sources and routes of nitrogen cycling in the cave system remain to be specifically elucidated. Biofilm community composition The formation of pendulous snottites and other macroscopic biofilm structures in caves has been observed before but mostly under acidic or otherwise extreme conditions. In comparison to the massive biofilm structures (pH ~7.5) now reported for the Sulzbrunn cave, previously discovered snottites appeared much thinner in shape, were less densely distributed and formed lower amounts of extracellular polymeric substances ( Bond et al. , 2000 ; Holmes et al. , 2001 ; Northup et al. , 2003 ; Jones et al. , 2010 ; Ziegler et al. , 2013 ). Together with the rich diversity of methylotrophs and other bacterial lineages now discovered in the Sulzbrunn biofilms, this points toward distinct biogeochemical and ecophysiological drivers of biofilm formation in the different systems. We suggest the identified biofilm compartments to be a function of methane influx, water submersion and oxygen and nutrient supply within the cave. The high abundance of methanotrophs and methylotrophs of up to ~45% in submersed biofilms and between 10 and ~20% in the other biofilm compartments was consistent with the importance of methane as the driver of biofilm formation. An abundance of aerobic methanotrophs of up to 40% has been reported previously for a terrestrial methane seep ( Gagliano et al. , 2016 ). However, central questions remain how carbon and energy flows are shared between the methanotrophs, other methylotrophs and the diverse non-methylotrophic lineages discovered in the Sulzbrunn biofilms. Distinguishing between obligate and facultative methanotrophs requires genomic and proteomic information, which is not yet available for the investigated system. However, the ecophysiology of some of the microbes detected can be cautiously extrapolated from the literature. For example, Methylobacter spp. are generally considered as obligate methanotrophs ( Knief, 2015 ), while Methylotenera spp. and other Methylophilaceae are mostly known as obligate non-methane-utilizing methylotrophs ( Kalyuzhnaya et al. , 2012 ). The co-occurrence of these methanotrophs and methylotrophs, especially in the submersed biofilms, suggest methane-fueled cooperation ( Chen et al. , 2009 ). Members of the Methylococcaceae and Methylophilaceae have been previously reported to trophically interact in methane-fueled systems under oxic and microoxic conditions ( Beck et al. , 2013 ; Oshkin et al. , 2015 ). Members of the Methanococcaceae have been shown to shunt carbon to diverse non-methylotrophic community members in microbial mats situated at marine hydrocarbon seeps ( Paul et al. , 2017 ). Thus, in the Sulzbrunn biofilms, complex communities and interaction networks can be considered to drive methane oxidation rather than single microbial species. Methanotrophs are also well known as producers of abundant extracellular polysaccharides ( Linton et al. , 1986 ; Strong et al. , 2015 ). Many of them possess the ribulose monophosphate pathway to fix methyl-group-derived carbon. The production of extracellular polysaccharides from methanol is balanced in terms of adenosine triphosphate and reducing equivalents ( Linton et al. , 1986 ). The observed exopolysaccharide production is conceivable as an energy-spilling reaction, preventing the buildup of toxic formaldehyde under excess methane supply, and providing methane-derived reduced carbon to other heterotrophic members of the biofilm community. Some methanotrophs have been shown to ferment methane and release large amounts of reduced carbon under oxygen-limited conditions ( Kalyuzhnaya et al. , 2013 ). Growth limitation by limited nitrogen or phosphorous supply, as suggested especially for the aerial biofilms by high C:N:P ratios, would support this scenario. Although many methanotrophs are capable of fixing dinitrogen ( Knief, 2015 ), P limitation will not be readily complemented in aerial biofilms. The C:P (~4700) and N:P (~80) ratios observed in biofilms are clearly much higher than canonical Redfield ratios or than C:N:P ratios suggested to indicate bacterial P limitation ( Vrede et al. , 2002 ). Therefore, we propose that the massive extracellular matrix formed in the Sulzbrunn biofilms serves, at least in part, as an electron sink for nutrient-limited methylotrophs. Besides well-known proteobacterial methanotrophs and methylotrophs, members of the candidate genus Methylomirabilis were also detected but appeared restricted to submersed biofilms in Sulzbrunn. These are known as nitrate-dependent anaerobic methane oxidizers proposed to intra-aerobically oxidize methane under NO dismutation ( Ettwig et al. , 2010 ). Their detection points toward the possible occurrence of anaerobic methane oxidation in specific microniches of the Sulzbrunn biofilms. Furthermore, we are currently investigating whether Archaea could also possibly be involved in methane cycling in the system. Preliminary data suggest that a low abundance of largely uncultured archaeal lineages can be found in the submersed biofilms and water samples but not in aerial biofilms. Furthermore, the abundant detection of putatively sulfur-oxidizing ( Watanabe et al. , 2014 ) and iron-oxidizing ( Emerson et al. , 2013 ), as well as iron-reducing ( Cummings et al. , 1999 ), members of the Betaproteobacteria , especially in spring and mixed cave waters, points toward active sulfur and iron cycling in the cave. However, these processes, as well as their possible link to carbon cycling, could not be further traced in the present study but will be the subject of future work. Possible role of iodine The visualization of the biofilm matrix revealed unique structural features of the biofilms. Although large globular structures have been previously reported for biofilms in technical systems ( Okabe et al. , 1999 ; Weissbrodt et al. , 2013 ), a comparably massive embedding of single or small numbers of cells in capsules and networks of glycoconjugates, to the best of our knowledge, has not been observed. It is tempting to speculate that besides a possible role as an electron sink, the biofilm matrix could also serve as protective barrier against harmful agents possibly present in the Sulzbrunn system. The concept of biofilms as a diffusive barrier against antimicrobials is well established ( Flemming et al. , 2016 ). In the iodine-rich waters and biofilms of the Sulzbrunn cave, the possibility of bactericidal activity of iodine species should be discussed. Iodine is well known as a disinfectant, but interestingly, the mechanisms of its toxicity are still not fully elucidated, probably owing to its complex chemistry ( Küpper et al. , 2011 ). Elemental iodine (I 2 ) is not stable in aqueous solution, where it readily hydrolyses to iodide (I − ), hypoiodous acid (HOI) and several other iodine species ( Gottardi, 1999 ). Under elevated pH, the formation of iodate (IO 3 − ) by chemical disproportionation is also possible. Iodide and iodate are considered as non-toxic, while elemental iodine, hypoiodous acid and triiodide (I 3 − ) are suggested as bactericidal oxidizing agents ( Gottardi, 1999 ). Owing to its complex behavior as a solute, comprehensive iodine speciation is challenging and has not yet been accomplished for different Sulzbrunn samples. Although we assume that most of the total iodine emerging with the reduced mineral water was iodide, this could undergo a number of microbially driven oxidation and volatilization reactions in the cave. The oxidation of iodide to elemental iodine in the presence of polysaccharides has been shown for Pseudomonas iodooxidans ( Gozlan and Margalith, 1974 ) and distinct Alphaproteobacteria ( Amachi et al. , 2005 ), which were even stimulated under high iodide concentrations ( Arakawa et al. , 2012 ). An Arenibacter sp. ( Bacteroidetes ) has been reported to accumulate iodine during that process ( Ito et al. , 2016 ). Moreover, various isolates from iodine-rich habitats, including Erythrobacter , Pseudomonas and Rhizobium spp., have been shown to methylate iodide, thus volatilizing it as highly reactive iodomethane (CH 3 I) ( Amachi et al. , 2005 ; Fujimori et al. , 2012 ). And finally, Pseudomonas sp. SCT has been shown capable of anaerobic growth with iodate as sole electron acceptor or while simultaneously reducing nitrate ( Amachi et al. , 2007 ). The abundant detection of all of the above genera in the Sulzbrunn biofilms, as well as the higher iodine concentrations found in the snottites ( Table 2 ), imply that volatilization processes may actually have been ongoing in the cave. The volatilization as iodomethane and subsequent oxidation by methyl halide oxidizers in aerial biofilms ( McDonald et al. , 2002 ) seems plausible and could establish a link between the cycling of methane and iodine in the system. It can be cautiously speculated that iodide released upon iodomethane oxidation by methylotrophs in snottites could then be oxidized to iodine by other community members, thus possibly contributing to iodine stress and glycoconjugate production in biofilms. As a first step to follow-up on this, we have tried to quantify iodomethane in the cave atmosphere by gas chromatography. Although we were able to detect it upon several occasions (data not shown), a consistent and reproducible quantification was not accomplished so far, possibly due to the highly reactive nature of this methylating agent."
} | 5,968 |
39294211 | PMC11411068 | pmc | 8,087 | {
"abstract": "Understanding the factors driving the maintenance of long-term biodiversity in changing environments is essential for improving restoration and sustainability strategies in the face of global environmental change. Biodiversity is shaped by both niche and stochastic processes, however the strength of deterministic processes in unpredictable environmental regimes is highly debated. Since communities continuously change over time and space—species persist, disappear or (re)appear—understanding the drivers of species gains and losses from communities should inform us about whether niche or stochastic processes dominate community dynamics. Applying a nonparametric causal discovery approach to a 30-year time series containing annual abundances of benthic invertebrates across 66 locations in New Zealand rivers, we found a strong negative causal relationship between species gains and losses directly driven by predation indicating that niche processes dominate community dynamics. Despite the unpredictable nature of these system, environmental noise was only indirectly related to species gains and losses through altering life history trait distribution. Using a stochastic birth-death framework, we demonstrate that the negative relationship between species gains and losses can not emerge without strong niche processes. Our results showed that even in systems that are dominated by unpredictable environmental variability, species interactions drive continuous community assembly.",
"introduction": "Introduction Understanding the mechanisms underlying the long-term maintenance of biodiversity is essential for improving conservation efforts and preventing further biodiversity loss 1 , 2 . Ecological communities change over time and through space as a function of numerous internal and external processes 3 . In this continuous assembly process some species persist while others disappear (species losses) and (re)appear (species gains) over time 4 , 5 while maintaining local diversity. Various internal and external factors shape community assembly, therefore observing compositional changes over time might shed light on what factors drive assembly processes as well as how biodiversity is maintained in the face of environmental change 5 . The combination of two major mechanisms can lead to continuous community assembly; dispersal-assembly, whereby stochastic processes such as dispersal, random birth and death events dominate 6 , and selection- or niche-based assembly 7 , whereby species interactions drive community assembly. Ecological communities are on the spectrum between niche-based and dispersal-based regimes, where their relative positions according to analytic arguments depend on population sizes and the variability of the environment 8 . Under highly stochastic environmental conditions, such as in river ecosystems driven by cycles of flood and drought disturbances, community assembly is often assumed to be dominated by external factors such as hydrologic variability that override biotic control of communities 9 , 10 . However, empirical evidence suggests that species interactions in stream communities, such as competition, predation and herbivory, exert important effects on population and community dynamics 11 – 13 . Species traits such as average body size, voltinism and feeding habits (e.g. predation) have been extensively shown to influence the dynamics of benthic communities 14 . In particular, benthic predators often influence the evolution of prey trait distributions. Predatory effects include increase in prey body size and change in body shape, increase in movement speed 15 , 16 , or change in voltinism such that prey species grow more slowly in the presence of predators 17 . In order to empirically detect the driving force of ecological communities, we investigate the temporal relationship between species (re)appearances (gains) and disappearances (losses) in the community. Community assembly driven primarily by stochastic processes should render species gains and losses independent, uncorrelated events. However, it is possible that the same external factors drive local population disappearances or (re)appearances, potentially leading to correlated gain-loss processes—also known as the confounding effect 18 . By contrast, niche-based assembly theory asserts that species diversity arises from ecological selection (i.e. partially or non-overlapping niches). Species fitness differences and interactions are the main drivers of assembly that hypothetically might lead to not only correlated but causally-related species gain-loss events 19 . To test this cause-effect relationship, we use time-series data of benthic invertebrate communities from 66 locations across New Zealand recorded between 1990 and 2019 (Fig 1 a). River flow regimes are a dominant external force in regulating stream biodiversity 20 – 22 . Therefore, we couple these community data with continuously monitored river flow data and species traits to generate causal linkages. Due to its maritime climate, New Zealand running waters are highly unpredictable and aseasonal relative to continental systems 23 , 24 . First, we establish our causal hypothesis for how species gains and losses are related and how external processes, in the form of highly dynamic river flow regimes, regulate this connection. To discover these causal hypotheses, we employed a nonparametric causal discovery approach based on conditional independence testing 18 , 25 . Since observational data are often confounded, they fail to establish cause-effect relationships. In this line, causal inference tools have been developed that allow us to infer causation from observational data 18 , 25 . Then, based on the discovered causal links we use a stochastic dynamic model combined with scaling theory 26 to theoretically investigate what processes can potentially generate the observed cause-effect relationship between species gains and losses.",
"discussion": "Discussion Both empirical and theoretical findings suggest that species gains and losses are causally-related driven by strong biotic interactions in these stochastic environments. Species gains and losses empirically showed negative association, similarly to previous observations 28 , 34 . The relationship between species gains and losses is the product of the combination of interaction structure and stochastic processes, whereby a small fraction of species persisted over time, another fraction of species had an intermediate temporal presence and the remainder species rarely appeared potentially resulting from stochastic processes and weak competitive abilities. Our theoretical predictions based on body size scaling relationships also supported that biotic interactions are needed to reconstruct the observed fluctuating relationship between species gains and losses. The role of biotic interactions in the dynamics of river ecosystems have been long debated because of the strong external forcing from cycles of floods and droughts 9 , 10 and are therefore deemed to be highly-context dependent 14 . For instance, while previous work found that flow variability breaks down competitive hierarchies 11 and predator–prey interactions 35 , benthic predators have been suggested to have cascading effects on altering prey abundance, size or age structure, behavior, and morphology 14 . Our causal inference analysis identified predatory effects to be partly responsible for the observed continuous community assembly reflected by species gains and losses. Second, the synthetic analysis strongly supported the role of predator-prey and competitive interactions shaping community dynamics closely matching the empirical observations. We showed that environmental stochasticity affects the number of generations per year (voltinism), i.e. communities under higher environmental noise comprised more species with longer generation time. However, more precise information on changes in voltinism in low and high environmental noise requires further investigation with measured species trait distributions. We observed a limited effect of environmental noise on the communities in these dynamic rivers. This weak influence is expected in living systems due to species adapting to the fluctuation structure of their environment (e.g. variances and correlations) given that it remains constant over evolutionary timescales 36 . In our case, the highly autocorrelated noise with relatively small or in some cases nonexistent characteristic signal present in stream flow measurements (Fig. 1 b) suggests that species will have developed adaptive strategies such as bet hedging 37 . For instance, most predatory species in our analysis were also generalists suggesting an adaptive feeding behavior to a constantly-changing environment. Due to its maritime climate and unpredictable flow regimes, New Zealand stream communities are a case in point of such adaptation, being highly generalist and opportunistic 23 . Our synthetic analysis generated predictions tightly coupled to the observed metrics. As expected, increasing internal constraints reduced the number of species present from the regional pool and reduced evenness due to stronger predation and competitive exclusion within the communities. The presence of internal structure led some species to persist and some species to disappear and reappear according to stochastic events, which creates the observed fluctuations of species gains and losses. When species weakly interact, more species were included in the local communities from the regional species pool leading to highly even species distributions and low species turnover, which rendered species disappearances and (re)appearances independent events confirming previous expectations 19 . The synthetic analysis also revealed that the discovered causal relationships among species traits in stochastic model communities can be utilized to closely reproduce observed biodiversity patterns, without directly inferring species interactions coefficients from empirical data. In our theoretical investigation, we assumed that biological rates and interactions vary as a function of species body sizes. Body size, as a master trait, is known to scale with other species traits such as dispersal ability 38 , predation 39 , and voltinism 40 . Here we empirically demonstrated that body size not only correlates with, but is causally-related to other species traits and biological processes in stream communities. Predation and dispersal changed body size distribution in benthic communities corroborating previous observations 15 , 38 . The increase in average body sizes can be explained by size-selective predation of smaller-bodied prey species. Therefore, we assumed that macroinvertebrate communities are size-structured and likely governed primarily by predator-prey and competitive interactions, however, other interactions types such as facilitation might have an important role in macroinvertebrate communities 41 . For instance, aggregation, a form of facilitation, reduces the individual risk of predation and can benefit individuals by recycling each other’s byproducts 42 . Nevertheless, the causal association between predators and gains and losses, and the lack of any other direct association, indicates a dominant role of antagonistic interactions in structuring these communities. In this work, we showed that species occurrence information allow the detection of mechanisms driving community dynamics by combining causal inference analysis with theoretical models. Following a causal discovery approach, we identified causal links between species traits, environmental noise and internal processes. Then, we used the information obtained from causal discovery to calibrate and parameterize a stochastic trait-based dynamical model. Given the high match between the theoretical results and observations, we believe that our work provides a future avenue towards a data-driven general framework to investigate continuous community assembly."
} | 3,003 |
26571098 | null | s2 | 8,088 | {
"abstract": "Expansion of the genetic code with nonstandard amino acids (nsAAs) has enabled biosynthesis of proteins with diverse new chemistries. However, this technology has been largely restricted to proteins containing a single or few nsAA instances. Here we describe an in vivo evolution approach in a genomically recoded Escherichia coli strain for the selection of orthogonal translation systems capable of multi-site nsAA incorporation. We evolved chromosomal aminoacyl-tRNA synthetases (aaRSs) with up to 25-fold increased protein production for p-acetyl-L-phenylalanine and p-azido-L-phenylalanine (pAzF). We also evolved aaRSs with tunable specificities for 14 nsAAs, including an enzyme that efficiently charges pAzF while excluding 237 other nsAAs. These variants enabled production of elastin-like-polypeptides with 30 nsAA residues at high yields (∼50 mg/L) and high accuracy of incorporation (>95%). This approach to aaRS evolution should accelerate and expand our ability to produce functionalized proteins and sequence-defined polymers with diverse chemistries."
} | 266 |
27513570 | PMC4981452 | pmc | 8,090 | {
"abstract": "Polyhydroxyalkanoate (PHA) is a biopolyester/bioplastic that is produced by a variety of microorganisms to store carbon and increase reducing redox potential. Photosynthetic bacteria convert carbon dioxide into organic compounds using light energy and are known to accumulate PHA. We analyzed PHAs synthesized by 3 purple sulfur bacteria and 9 purple non-sulfur bacteria strains. These 12 purple bacteria were cultured in nitrogen-limited medium containing acetate and/or sodium bicarbonate as carbon sources. PHA production in the purple sulfur bacteria was induced by nitrogen-limited conditions. Purple non-sulfur bacteria accumulated PHA even under normal growth conditions, and PHA production in 3 strains was enhanced by nitrogen-limited conditions. Gel permeation chromatography analysis revealed that 5 photosynthetic purple bacteria synthesized high-molecular-weight PHAs, which are useful for industrial applications. Quantitative reverse transcription polymerase chain reaction analysis revealed that mRNA levels of phaC and PhaZ genes were low under nitrogen-limited conditions, resulting in production of high-molecular-weight PHAs. We conclude that all 12 tested strains are able to synthesize PHA to some degree, and we identify 5 photosynthetic purple bacteria that accumulate high-molecular-weight PHA molecules. Furthermore, the photosynthetic purple bacteria synthesized PHA when they were cultured in seawater supplemented with acetate. The photosynthetic purple bacteria strains characterized in this study should be useful as host microorganisms for large-scale PHA production utilizing abundant marine resources and carbon dioxide.",
"conclusion": "Conclusion In this study, we found that all photosynthetic purple bacteria tested were able to accumulate PHAs. PHA production had been previously reported in Rdv . sulfidophilum [ 13 ], whereas this is the first report of PHA production in the other 11 photosynthetic purple bacteria. Purple sulfur bacteria accumulated the PHB homopolymer. Some purple non-sulfur bacteria did not increase PHA content under nitrogen-limited conditions, implying that nitrogen was not limited in these strains, likely due to strong nitrogen fixation activity. All of the purple non-sulfur photosynthetic bacteria were able to produce copolymers consisting of 3HB and 3HV units. GPC analysis revealed that some of the photosynthetic purple bacteria synthesized high-molecular-weight PHA molecules due to decreased level of PhaC and PhaZ, which is an important property for industrial production. We also demonstrated that photosynthetic purple bacteria synthesized PHA in seawater supplemented only with acetate. We believe that the candidate photosynthetic purple bacteria strains identified in this study will be useful host microorganisms for industrial PHA production using marine resources.",
"introduction": "Introduction Polyhydroxyalkanoate (PHA) is a biopolyester that functions both as an intracellular carbon and energy storage molecule as well as a sink for reducing redox potential [ 1 , 2 ]. PHA has garnered attention as an alternative to petroleum-derived plastics due to its biodegradability and biocompatibility [ 3 ]. One of the best studied types of bacteria in the context of PHA production is Ralstonia eutropha H16, and recombinant strains of this bacterium are used in numerous industrial bioprocesses [ 4 , 5 ]. Although efforts have been made to reduce the price of PHA, the cost of the necessary carbon sources, such as sugars or plant oils, is still high compared with petroleum-derived plastics. To solve this problem, some researchers have focused on direct fixation of CO 2 to PHAs via photosynthesis in an attempt to reduce the price of PHA production. For example, transgenic higher plants have been modified to produce higher levels of PHA [ 6 ]. Furthermore, several strains of cyanobacteria have been reported to contain active PHA synthases and to accumulate 3-hydroxybutyrate (3HB) [ 7 , 8 ]. However, high PHA productivity in higher plants or cyanobacteria has yet to be achieved. In addition to higher plants and cyanobacteria, anoxygenic photosynthetic bacteria have also been reported to accumulate PHA [ 9 ]. Anoxygenic photosynthetic bacteria can be divided into the following five categories based on pigments: electron donors, and aerobic/anaerobic condition: purple sulfur bacteria, purple non-sulfur bacteria, green sulfur bacteria, green non-sulfur (filamentous) bacteria and aerobic photosynthetic bacteria. Unlike higher plants and cyanobacteria, anoxygenic photosynthetic bacteria extract electrons from molecules other than water, such as organic compounds, sulfur compounds and hydrogen. The majority of anoxygenic photosynthetic bacteria can grow as photoautotrophs or photoheterotrophs in the light, and some members can grow in the dark as chemoheterotrophs. These bacteria can utilize various types of organic compounds as carbon sources. Due to these characteristics, photosynthetic bacteria have been tested for use in a variety of applications, including purification of industrial wastewater and hydrogen production [ 9 ]. PHA production has been studied in a small number of freshwater purple non-sulfur bacteria strains such as Rhodospirillum rubrum [ 10 ], Rhodobacter sphaeroides [ 11 ] and Rhodopseudomonas palustris [ 12 ], with a focus on carbon source, culture conditions and PHA yield. Rhodospirillum rubrum is the best characterized strain with respect to PHA production, and it showed 50 wt% PHA content by dry cell weight when butyrate was used as the sole carbon source [ 10 ]. It was reported that Rhodobacter sphaeroides and Rhodopseudomonas palustris accumulated PHA levels of 60–70 wt% [ 11 ] and 4 wt% [ 12 ], respectively. In contrast, studies of PHA production in marine photosynthetic bacteria are limited to only a few strains [ 13 , 14 ]. The marine purple non-sulfur bacterium Rhodovulum sulfidophilum reportedly possesses the ability to synthesize poly[( R )-3-hydroxybutyrate] (PHB) up to 50 wt% of its dry weight [ 13 ]. Marine bacteria are attracting attention as new biotechnological resources, and it is expected that they will yield a wealth of new bioactive compounds [ 15 – 17 ]. However, the potential of these bacteria remains largely unexplored. The utilization of marine bacteria has a number of potential advantages in terms of commercial applications. For example, when marine bacteria are used for commercial scale cultivation, sterilized seawater can be used as a culture medium without the need for a synthetic medium, leading to considerable savings on fresh water. Additionally, bacterial contamination is a serious problem for commercial production involving microbial fermentation. However, the high salt concentration of seawater inhibits contamination from the air during the cultivation of marine bacteria. Considering those potential advantages, we focused on marine photosynthetic purple bacteria as a host microorganism for PHA production. In this study, we evaluated PHA production in marine photosynthetic purple bacteria and characterized the resultant PHAs, and we found them to be suitable new host microorganisms for photosynthetic PHA production.",
"discussion": "Results and Discussion We cultured 16 purple sulfur bacteria and 17 purple non-sulfur bacteria strains, as shown in S1 Table , yielding a total of 33 strains of photosynthetic purple bacteria that were tested for growth in liquid culture. Of these strains, 3 purple sulfur bacteria and 9 purple non-sulfur bacteria showed relatively high growth in liquid culture ( Table 1 ). These 12 strains were further characterized as candidates for PHA production. One candidate strain, Rdv . sulfidophilum , was previously reported to accumulate PHA [ 14 ], whereas the remaining 11 strains had not been previously characterized for PHA production. We searched the public database and found that whole genome sequences have been determined only in Rdv . sulfidophilum . We found the phaC gene encoding PHA synthase which belongs to the class I in the genome of Rdv . sulfidophilum . 10.1371/journal.pone.0160981.t001 Table 1 Candidate strains of photosynthetic purple bacteria. Sulfur type Resource No. Organism Original marine area Sulfur DSM5653 Thiohalocapsa marina Mediterranean Sea Sulfur JCM14889 Thiophaeococcus mangrovi Orissa, India Sulfur JCM13911 Marichromatium bheemlicum Bhimunipatnam, India Non-sulfur DSM2698 Afifella marina Kagoshima, Japan Non-sulfur DSM4868 Rhodovulum euryhalinum Russia Non-sulfur JCM13589 Rhodovulum imhoffii Bhimunipatnam, India Non-sulfur ATCC35886 Rhodovulum sulfidophilum Groningen, Netherlands Non-sulfur ATCC BAA1573 Rhodovulum tesquicola Soda Lake, Russia Non-sulfur JCM13531 Rhodovulum visakhapatnamense Visakhapatnam, India Non-sulfur ATCC BAA447 Roseospira marina Arcachon Bay, France Non-sulfur JCM14191 Roseospira goensis Goa, India Non-sulfur ATCC BAA1365 Roseospira visakhapatnamensis Kakinada, India PHA accumulation is known to be enhanced when excess carbon is present and other nutrient(s), such as nitrogen, phosphorus or sulfur, are limited [ 18 ]. In the case of photosynthetic bacteria, PHA production can be induced under nitrogen- or vitamin-limited conditions [ 10 ], [ 13 ]. In addition, acetic acid was shown to be an efficient carbon source for PHA production in photosynthetic bacteria [ 13 , 19 ]. Therefore, in this study, we used a nitrogen-limited medium (ammonium chloride-free) containing sodium acetate to test PHA production. Carbon dioxide was supplied by 0.1% NaHCO 3 . Twelve photosynthetic purple bacteria strains were cultured in growth medium until the cell cultures reached an approximate OD 660 value of 1.0, indicating they were in log phase, and these cells were harvested and used as growth conditions without supplementation and depletion. Intracellular PHAs under growth condition were analyzed using GC-MS. The log phase cell cultures were diluted to an OD 660 of 0.1 in nitrogen-limited media supplemented with 0.5% sodium acetate and/or 0.1% NaHCO 3 . After 7 days, just prior to stationary phase, the cells were harvested, and intracellular PHA levels were characterized. Three of the purple sulfur bacteria ( Thc . marina , Tpc . mangrove , and Mch . bheemlicum ) accumulated less than 0.1 wt% PHA by dry cell weight under growth conditions ( Fig 1 , white bars). In contrast, 9 purple non-sulfur bacteria strains accumulated PHA levels ranging from 2.0 to 30 wt%, even under growth conditions. Intracellular PHAs were analyzed when the bacteria were grown in nitrogen-limited media containing both sodium acetate and NaHCO 3 . Three purple sulfur bacteria strains accumulated more PHAs (5 to 11 wt%) under these conditions compared with growth conditions ( Fig 1 , light gray bars). Although increased PHA production was observed in 3 purple non-sulfur bacteria ( Rdv . tesquicola , Ros . goensis , and Ros . visakhapatnamensis ), the degree of PHA induction was not remarkable compared with the purple sulfur bacteria. PHA accumulation was not enhanced in the remaining 6 purple non-sulfur bacteria ( Rps . marina , Rdv . euryhalinum , Rdv . imhoffii , Rdv . sulfidophilum , Rdv . visakhapatnamense , and Ros . marina ). 10.1371/journal.pone.0160981.g001 Fig 1 PHA content (wt%) of photosynthetic purple bacteria. Photosynthetic purple bacteria strains were cultured in growth medium until the cell cultures reached an approximate OD 660 value of 1.0 and then diluted to an OD 660 of 0.1 in nitrogen-limited media supplemented with 0.5% sodium acetate and/or 0.1% NaHCO 3 . After 7 days, the cells were harvested, and intracellular PHA levels were characterized using GC-MS. Intracellular PHAs under growth conditions were analyzed using cells showing approximately OD 660 = 1.0 without supplementation and depletion. Data are the mean ± SD of at least three cultures. *Values that show significant differences compared to the growth conditions (p<0.05). In some bacterial species, it has been proposed that nitrogen fixation competes with PHA formation for reducing equivalents [ 4 ]. Photosynthetic bacteria have the ability to fix nitrogen due to the presence of nitrogenase enzymes. We identified two nitrogenases in the genome of Rdv . sulfidophilum [ 20 , 21 ], suggesting that it has nitrogen fixation activity. Some strains showed higher CDW under nitrogen-limited conditions compared to growth condition ( S1 Fig ), implying that photosynthetic bacteria have nitrogen fixation activity, even though direct assay related to nitrogen fixation such as nitrogenase catalyzed acetylene reduction experiment is needed to clear the nitrogen fixation activity. Based on these observations, we suggest that PHA production was not enhanced under nitrogen-limited conditions due to strong nitrogen fixation activity in the 6 purple non-sulfur bacteria. Other deficiency conditions, such as phosphorus-, sulfate- and trace element-limited conditions, have been used to induce PHA production in other bacteria [ 4 , 18 , 22 ]. Indeed, PHA production was shown to be induced in Rdv . sulfidophilum when grown in vitamin-free medium [ 13 ]. Therefore, the optimization of PHA induction conditions is necessary to maximize PHA productivity in photosynthetic bacteria in the future. PHA production was also investigated under nitrogen-limited culture conditions with only sodium acetate or NaHCO 3 as a carbon source ( Fig 1 , acetate; dark gray bars, NaHCO 3 ; black bars). Eleven photosynthetic purple bacteria showed PHA accumulation, which ranged from 8 to 25 wt% under nitrogen-limited culture conditions containing acetate as the carbon source. In one strain, Rdv . visakhapatnamense , PHA content was significantly decreased. PHA increased significantly under nitrogen limitation by the addition of only acetate in Rps . marina although there was no significant increase under nitrogen limitation with both 0.5% acetate and 0.1% NaHCO 3 . We next compared PHA levels under these conditions to those from mixed carbon sources (acetate/NaHCO 3 ). When acetate was used as the sole carbon source, compared with mixed carbon sources, PHA content was higher in six bacteria strains ( Thc . marina , Tpc . mangrove , Mch . bheemlicum , Rdv . tesquicola , Ros . goensis , and Ros . visakhapatnamensis ). PHAs are highly reduced compounds, and therefore, their accumulation affects the redox state of the cell. Indeed, it has been proposed that PHAs are important for maintaining the proper redox state in nitrogen-fixing bacteria [ 4 ]. Under mixed carbon conditions, CO 2 could modify the intracellular redox state through photosynthetic electron transport, resulting in decreased PHA levels in these 6 photosynthetic bacteria. The PHA contents of these six bacteria significantly increased under nitrogen-limited conditions, implying that they have little or no nitrogen fixation activity. In the case of such bacteria, reducing the redox state could be used to reduce CO 2 . None of the photosynthetic purple bacteria strains could accumulate PHA (<0.1 wt% to 4 wt%) in the nitrogen-limited medium containing only NaHCO 3 as a carbon source ( Fig 1 ), indicating that conversion of NaHCO 3 into PHA by photosynthetic purple bacteria was quite low under this condition. As a result, the redox state was not optimal, and the concentration of NaHCO 3 was not sufficient for PHA production. The cell dry weights (CDW) of the 12 strains were measured under all conditions ( S1 Fig ). CDW was low (less than 500 mg L -1 culture) when the majority of the photosynthetic bacteria were grown in nitrogen-limited medium containing only NaHCO 3 . PHA content is expressed as the percentage of CDW per 1 L of cell culture ( S2 Fig ). Among all strains under all conditions, Rdv . visakhapatnamense showed the highest PHA content (302 ± 42 mg/L culture) under growth conditions. Five photosynthetic purple bacteria ( Mch . Bheemlicum , Rdv . euryhalinum , Rdv . imhoffi , Rdv . sulfidophilum , and Rdv . visakhapatnamense ) showed yields higher than 200 mg/L in PHA culture. Brandl et al . reported production levels of 500 mg/L PHA in R . sphaeroides and 390 mg/L PHA in Rhodospirillum rubrum [ 10 ]. Although further optimization of growth conditions will be required to increase PHA yield, several of the tested photosynthetic purple bacteria are promising host strains for PHA production. PHAs are found in the cytoplasm as insoluble inclusions called PHA granules. Mch . bheemlicum (purple sulfur bacteria) and Rdv . visakhapatnamense (purple non-sulfur bacteria) were cultured in growth media and then transferred to nitrogen-limited media containing sodium acetate. The PHA granules of these photosynthetic purple bacteria were then investigated by transmission electron microscopy (TEM) ( Fig 2 ). In the cells of Mch . bheemlicum , no granules were observed under growth conditions ( Fig 2a ). In contrast, most cells harbored multiple large PHA granules under nitrogen-limited conditions ( Fig 2b ). These observations are consistent with low PHA content under growth conditions and increased PHA content under nitrogen-limited conditions ( Fig 1 ). The diameters of the PHA granules were approximately 0.59 ± 0.14 μm, which is comparable to the average cell diameter of most bacterial species (0.4 to 1 μm). In the majority of Rdv . visakhapatnamense cells, only a single large PHA granule was observed under growth conditions ( Fig 2c ). In contrast, most cells contained numerous smaller PHA granules under nitrogen-limited conditions ( Fig 2d ). The diameters of the PHB granules were 0.52 ± 0.13 μm under growth conditions and 0.38 ± 0.07 μm under nitrogen-limited conditions. The number of PHA granules observed in Mch . bheemlicum cells was 0.06 ± 0.24 (n = 18) under growth conditions and 3.25 ± 1.28 (n = 12) under nitrogen-limited conditions. The number of PHA granules in Rdv . visakhapatnamense was 0.79 ± 0.70 (n = 14) under growth conditions and 3.50 ± 0.94 (n = 14) under nitrogen-limited conditions. 10.1371/journal.pone.0160981.g002 Fig 2 TEM images of intracellular PHA granules in Mch . bheemlicum and Rdv . visakhapatnamense . Mch . bheemlicum cells were cultured in growth medium (a) and in nitrogen-limited medium containing sodium acetate (b). Rdv . visakhapatnamense cells were cultured in growth medium (c) and in nitrogen-limited medium containing sodium acetate (d). PHA granules are known to be coated by various granule-associated proteins [ 23 , 24 ] In particular, the proteins that coat PHA granules are PHA synthase (PhaC), PHA depolymerase (PhaZ), repressor protein (PhaR) and PHA phasin (PhaP) [ 25 – 27 ]. The expression level of PhaP is known to affect the size and number of PHA-granules [ 28 , 29 ]. R . eutropha expresses several copies of the phaP gene and contains large numbers of small PHA granules [ 29 , 30 ]. The mRNA levels of phaP gene was analyzed by quantitative reverse transcription polymerase chain reaction (RT-PCR) under nitrogen-limited and acetate supplemented conditions ( Fig 3 ). Rdv . sulfidophilum cells were used for expression analysis because whole genome sequences have been determined only in this strain. The mRNA levels of phaP gene was decreased under nitrogen limited conditions contrary to expectation. Changes in the number and size of PHA granules might be regulated by factors other than the levels of PhaP in photosynthetic purple bacteria. Further investigations will be required to clarify the mechanisms underlying the regulation of the number and size of PHA granules. 10.1371/journal.pone.0160981.g003 Fig 3 Expression levels of phaC , phaP and phaZ genes under nitrogen-limited conditions. RNA of Rdv . sulfidophilum was extracted under growth condition which cells were in the log phase and nitrogen-limited conditions which cells were cultured in nitrogen-limited medium for 7 days. rpoD gene was used as a housekeeping gene for normalizing the expression of target genes. The expression levels were shown as the relative values compared with those of growth conditions. *Values with significant differences compared with the growth conditions ( p <0.05). Data are the mean ± SD from at least three cultures. The chemical structures of the synthesized PHAs were determined using 1 H NMR on chloroform-extracted samples from freeze-dried cells ( Fig 4 ). The 1 H NMR spectra showed the characteristic peaks for 3HB and 3HV. GC-MS analysis further revealed that purple sulfur bacteria ( Thc . marina , Tpc . mangrove , and Mch . Bheemlicum ) synthesized the homopolyester of 3HB under all conditions ( Table 2 ). In contrast, all of the purple non-sulfur bacteria were able to produce copolyesters containing 3HB and 3HV units. This has also been observed in purple sulfur bacteria isolated from freshwater habitats [ 19 ]. In purple non-sulfur bacteria, the PHA compositions were variable depending on strain and carbon source. Five purple non-sulfur bacteria ( Rps . marina , Rdv . euryhalinum , Rdv . imhoffii , Rdv . sulfidophilum , and Rdv . visakhapatnamense ) synthesized more than 90 mol% PHB. The remaining four purple non-sulfur bacteria ( Rdv . tesquicola , Ros . marina , Ros . goensis , and Ros . visakhapatnamensis ) produced copolymers containing 25–90 mol% 3HV units, and the 3HV composition was higher under growth conditions. Thermal properties of the synthesized PHAs were analyzed by DSC ( S2 Table ). The T g values were in the range of -4 to -1°C. Values of T m were ranging from 74 to 174°C. T m of PHBs was reported to be in the range of 160 to 175 [ 31 ]. Three purple non-sulfur bacteria ( Rps . Marina , Ros . marina , and Ros . goensis ) relatively lower T m , which is because these strains synthesized low-molecular-weight PHAs as described hereinafter with high 3HV composition ( Table 2 ). 10.1371/journal.pone.0160981.g004 Fig 4 1 H-NMR spectra of purified PHA. 1 H-NMR analysis was carried out using purified PHA from the cells of Thc . marinavi (a) Mch . bheemlicum (b), Rdv . tesquicola (c) and Ros . goensis (d). 10.1371/journal.pone.0160981.t002 Table 2 PHA composition (mol%) under growth and nitrogen-limited conditions. Organism Growth condition Nitrogen-limited conditions 0.5% acetate, 0.1% NaHCO 3 0.5% acetate 3HB 3HV 3HB 3HV 3HB 3HV Thc . marina 100 0 100 0 100 0 Tpc . mangrovi 100 0 100 0 100 0 Mch . bheemlicum 100 0 100 0 100 0 Rps . marina 96.0 ± 2.8 4.0 ± 2.8 95.9 ± 3.5 4.1 ± 3.5 93.9 ± 5.3 6.1 ± 5.3 Rdv . euryhalinum 99.0 ± 0.8 1.0 ± 0.8 99.2 ± 0.7 0.8 ± 0.7 97.2 ± 0.9 2.8 ± 0.9 Rdv . imhoffii 100 0 100 0 96.8 ± 3.2 3.2 ± 3.2 Rdv . sulfidophilum 100 0 94.9 ± 3.0 5.1 ± 3.0 92.6 ± 1.6 7.4 ± 1.6 Rdv . tesquicola 14.9 ± 2.2 85.1 ± 2.2 63.3 ± 11.1 36.7 ± 11.1 74.7 ± 11.3 25.3 ± 11.3 Rdv . visakhapatnamense 99.4 ± 1.0 0.6 ± 1.0 97.9 ± 0.9 2.1 ± 0.9 98.4 ± 1.5 1.6 ± 1.5 Ros . marina 9.8 ± 2.3 90.2 ± 2.3 49.9 ± 7.0 50.1 ± 7.0 70.6 ± 7.0 29.4 ± 7.0 Ros . goensis 15.9 ± 7.0 84.1 ± 7.0 56.2 ± 4.2 43.8 ± 4.2 34.0 ± 8.9 66.0 ± 8.9 Ros . visakhapatnamensis 20.6 ± 16.1 79.4 ± 16.1 72.1 ± 10.1 27.9 ± 10.1 69.9 ± 11.1 30.1 ± 11.1 Photosynthetic purple bacteria strains were cultured in growth medium until the cell cultures reached an approximate OD 660 value of 1.0 and then diluted to an OD 660 of 0.1 in nitrogen-limited media supplemented with 0.5% sodium acetate and/or 0.1% NaHCO 3 . After 7 days, the cells were harvested, and intracellular PHA levels were characterized using GC-MS. Intracellular PHAs under growth conditions were analyzed using cells showing approximately OD 660 = 1.0 without supplementation and depletion. Data are the mean ± SD of at least three cultures. The number-average molecular weight and PDI were determined from the GPC analysis of the PHAs ( Table 3 ). The number-average molecular weight of the purified PHAs was between 3,000 and 994,000 g/mol, and the PDI was between 1.5 and 6.7. The PDI values were lower in photosynthetic purple bacteria that synthesized lower molecular weights of PHAs such as Rps . marina , Ros . marina and Ros . goensis . The PDI values were higher in higher molecular weight PHAs. In this study, PHAs were extracted from the cells grown in nitrogen-limited medium for 7 days. This long-term cultivation might induce the degradation of the PHA, resulting in the broad molecular-weight distributions. To evaluate relationship between the PHA content and molecular weight, we calculated the coefficient of correlation. The value was -0.05, indicating that there was no correlation between the PHA content and molecular weight. As shown in the GPC chromatogram, the molecular weights of PHA synthesized by several types of photosynthetic purple bacteria were ranged from approximately 30,000 g/mol to over 3,000,000 g/mol, which was larger than the column limit and the molecular weight standards ( S3 Fig ). The number-average molecular weight was greater than 500,000 g/mol in 5 photosynthetic purple bacteria ( Thc . marina , Mch . bheemlicum , Rdv . imhoffii , Rdv . tesquicola , and Rdv . visakhapatnamense ). In cyanobacteria, the molecular weight and PDI were reported to be 135,000 g/mol and 1.4, respectively [ 32 ]. Therefore, when comparing cyanobacteria and photosynthetic purple bacteria, some photosynthetic purple bacteria can produce PHA molecules with extremely high molecular weights. 10.1371/journal.pone.0160981.t003 Table 3 Number-average molecular weight and PDI of the purified PHAs. Organism Number-average molecular weight (g/mol) PDI Thc . marina 645 × 10 3 3.7 Tpc . mangrovi 72 × 10 3 2.9 Mch . bheemlicum 994 × 10 3 5.8 Rps . marina 4 × 10 3 1.5 Rdv . euryhalinum 447 × 10 3 3.4 Rdv . imhoffii 570 × 10 3 6.7 Rdv . sulfidophilum 300 × 10 3 3.9 Rdv . tesquicola 504 × 10 3 3.4 Rdv . visakhapatnamense 713 × 10 3 3.4 Ros . marina 3 × 10 3 1.7 Ros . goensis 17 × 10 3 2.0 Ros . visakhapatnamensis 147 × 10 3 5.8 PHA can be degraded within the cells by PhaZ, and indeed, bacterial cells lacking PhaZ, such as E . coli , can synthesize ultra-high-molecular-weight PHA molecules [ 33 , 34 ]. Expression level of phaZ gene was slightly decreased under nitrogen-limited conditions in Rdv . sulfidophilum ( Fig 3 ), which synthesized high-molecular-weight PHAs ( Table 3 ). This result suggests one possibility that decreased level of phaZ gene induced production of high-molecular-weight PHAs. The expression levels of phaZ were reported to increase under nitrogen-limited conditions in Ralstonia eutropha [ 35 ]. PhaZ expression might not be induced by lack of nitrogen in case of Rdv . sulfidophilum due to its nitrogen fixation activity, as described above. Another possible explanation for production of high molecular weight PHAs is that the frequency of the chain transfer (CT) reaction was altered under nitrogen-limited conditions. PhaC catalyzes the CT reaction in which the PHA polymer chain is transferred from PhaC to a CT reagent, such as water or alcohol, following the polymerization of PHA [ 36 ]. Thus, the frequency of the CT reaction determines the molecular weight of PHA. The frequency of the CT reaction catalyzed by PhaC can range widely, leading to very different molecular weights for PHAs among photosynthetic bacteria. The molecular weight of PHA can be controlled by modulating the amount of PhaC in E . coli , and lower expression of PhaC leads to PHAs of higher molecular weight [ 37 ]. In this study, expression level of phaC gene was lower under nitrogen-limited conditions in Rdv . sulfidophilum ( Fig 3 ), leading to the formation of high-molecular-weight PHAs due to lower CT reaction frequency. Molecular weight is one of the most important properties of polymeric materials, as it can significantly affect physical and mechanical characteristics. PHA molecules with higher molecular weights are desirable for practical applications, especially considering that decreases in molecular weight have been reported during PHA extraction and purification processes [ 38 ], [ 39 ]. Moreover, PHAs with higher molecular weights are known to possess better mechanical properties [ 40 ]. The PHAs with molecular weight of more than 1× 10 6 g/mol are categorized as ultra-high-molecular-weight PHA. Higher plants and E . coli lacking the phaZ gene have been shown to produce ultra-high-molecular-weight PHAs [ 41 , 42 ]. Ultra-high-molecular-weight PHAs of approximately 2,000,000 g/mol can be produced by recombinant E . coli under specific conditions [ 41 ]. Sugarcane can produce PHB with molecular weights greater than 2,000,000 g/mol [ 42 ]. In the current study, we found that certain photosynthetic purple bacteria could produce PHAs with high molecular weights under natural nutrient-limited conditions. We believe these novel findings offer significant advantages for the production of PHAs for industrial applications. The use of seawater as culture medium is one way to reduce the production cost of cultivation. PHA production was investigated using artificial seawater. The log phase cell cultures of Rdv . sulfidophilum were diluted to an OD 660 of 0.1 in seawater with or without yeast extract and 0.5% acetate. The cells were harvested after 7 days, and intracellular PHA levels were characterized by GC-MS ( Fig 5 ). CDW of cells cultured only in seawater was nearly identical to that of pre-cultured cells ( S4 Fig ). Seawater contained only low levels of nutrients especially carbon, nitrogen, phosphate and iron [ 43 ]. This suggests that photosynthetic purple bacteria could not grow well in seawater due to deficiency of nutrients. Rdv . sulfidophilum cells did not accumulate PHA only in seawater because of poor cell growth ( Fig 5 ). CDWs were increased by the addition of yeast extract and acetate ( S4 Fig ). The addition of yeast extract did not lead to PHA production despite of recovery of the cell growth. On the other hand, Rdv . sulfidophilum cells accumulated 9 wt% PHA by the addition of acetate. The addition of both yeast extract and acetate did not enhance PHA production. These results indicate that acetate is a good carbon source for PHA production in seawater. The yield of PHA was 16 and 21 mg/L culture in seawater supplemented with acetate and both acetate and yeast extract, respectively. Thus, we demonstrated that PHA production could be achieved using seawater in photosynthetic purple bacteria. Optimization of culture conditions such as light conditions (light intensity and light quality) and carbon concentrations will be required to increase the CDW and PHA content using seawater. Two-stage cultivation system to separate PHA production from bacterial growth might also be effective for increasing the PHA content. 10.1371/journal.pone.0160981.g005 Fig 5 PHA content (wt%) of photosynthetic bacteria cultured in seawater. Rdv . sulfidophilum cells were cultured in growth medium until the cell cultures reached an approximate OD 660 value of 1.0 and then diluted to an OD 660 of 0.1 in s supplemented with 0.5% sodium acetate and/or 0.4 g/L of yeast extract. After 7 days, the cells were harvested, and intracellular PHA levels were characterized using GC-MS. Intracellular PHAs under growth conditions were analyzed using cells showing approximately OD 660 = 1.0. n. d., not detected. Data are the mean ± SD of at least three cultures. *Values that show significant differences compared to the growth conditions (p<0.05). According to a previous study on life cycle assessment (LCA) of PHA [ 44 ], costs for the PHA production using a recombinant strain of Ralstonia eutropha and life cycle inventories of energy consumption and CO 2 emissions have been calculated. Based on the LCA report, we evaluated the PHA production costs using photosynthetic purple bacteria. Photosynthetic purple bacteria can grow photoautotrophically, resulting the reducing the cost of carbon source because of utilization of photosynthetic product. In addition, well-known PHA-producing bacteria such as R . eutropha and E . coli are cultivated at 30–37°C, while photosynthetic purple bacteria are grown at around 25°C. Under this growth temperature, we spend less energy to keep the temperature of cell culture, leading to reducing the cost due to saving of electricity. Although lighting electricity is needed for growth of photosynthetic purple bacteria, LED is extremely efficient and solar light does not need any electricity. In the LCA for PHA production, cost for ammonia is set to 0.20 USD/kg, whereas other minerals are set to 0.004 USD/kg [ 44 ]. In the case of photosynthetic purple bacteria, nitrogen cost can be reduced because our study suggests that candidate strains have the nitrogen fixation ability. Furthermore, the use of seawater for PHA production by photosynthetic purple bacteria can reduce the cost of culture medium ( Fig 5 ). On the basis of these factors, photosynthetic purple bacteria have several advantages over soil bacteria and are potentially applicable to industrial PHA production."
} | 8,291 |
39671188 | PMC11665918 | pmc | 8,091 | {
"abstract": "Significance Natural physical systems evolve with certain global quantities being minimized or maximized due to physical laws. For example, charges in conductors redistribute to reach electrostatic equilibrium, minimizing electrostatic energy, and gases spread to maximize entropy. This research leverages these natural efficiencies by encoding optimization problems, like training artificial neural networks, into the evolution of physical systems. The concept is called “physical self-learning” where systems’ intrinsic parameters autonomously evolve guided by natural laws. Specifically, a physical Hopfield neural network using a magnetic thin film is developed. Inputs are encoded as electric signals that manipulate magnetic textures within the film through Oersted fields, enabling the film to learn from external inputs and perform tasks like associative memory of similar patterns.",
"discussion": "Discussion We have provided a proof-of-principle study to show that magnetic textures play as a promising platform for self-learning in the physical system. In terms of adapting training algorithms, such a system offers several potential advantages. First, because the speed of physical evolution is governed by the spin dynamics which is on the order of nanoseconds in ferromagnetic permalloy as illustrated in Fig. 5 , the training can be accomplished extremely fast without the weight updates from external computers or circuits that usually take much longer time. We note that the relatively long training voltage pulses used (50 μs) in our experiment are due to instrumental limitation of impedance mismatch, and much shorter pulses should be sufficient to train the magnetic texture as shown in our simulation results. Such issues can be potentially solved by optimizing the external circuit connections and employing advanced power source. These efforts will further improve the training efficiency of the network. Second, since the weight updating process is mainly driven by local conductance response to local external stimulus, the self-learning approach is parallel in nature where an increased number of nodes would not significantly increase the amount of training time as illustrated in Fig. 5 ( 14 , 19 , 20 ). Last but not least, the stability and high speed of spintronics devices mean that they can be rewritten or reconfigured frequently over the lifetime of a circuit, a feature that is essential in many emerging computing concepts ( 4 ). Several concepts related to physical self-learning have been proposed in various systems, offering promising ways to leverage natural phenomena for optimization. In memristor networks, an emergent Lyapunov force allows the system to efficiently explore complex energy landscapes and find optimal solutions ( 21 , 22 ). A similar approach called “learning by mistakes” has also been proposed in memristor networks, although it still requires peripheral computation for trials and corrections ( 64 , 65 ). Another interesting concept is equilibrium propagation ( 24 , 66 ), a learning framework for energy-based models that utilizes two phases (nudged and free phase) to perform learning. This concept has given rise to contrastive local learning, which has been realized in nonlinear resistive networks ( 67 ). Additionally, recent work has demonstrated supervised and reinforcement learning in nanowire networks by leveraging inherent nonlinear dynamics and heterogeneous connectivity ( 68 ). These approaches, along with physical self-learning realized by magnetic textures, offer promising avenues for allowing nature to perform optimization tasks efficiently. Although promising as a prototype demonstration, several questions need to be addressed in further studies. One question is how to amplify the output signal since the AMR in ferromagnetic materials is relatively small. A possible way is to use the current in plane (CIP) structure of giant magnetoresistance (GMR) to enhance the conductance difference ( 46 ), and the output signal strength can be further boosted by operational amplifiers which is widely used in Complementary Metal Oxide Semiconductor (CMOS) technologies. Scaling such a system to maintain good performance requires further validation in future studies. Also, further extension on how to achieve more functionalities, for example, implementations in the deep neural network with backpropagation and Boltzmann machine, will be interesting topics to explore in the future."
} | 1,114 |
31882916 | PMC6934592 | pmc | 8,092 | {
"abstract": "Sugar refinery washing water (SRWW) contains abundant levels of carbon sources and lower levels of contaminants than other types of wastewater, which makes it ideal for heterotrophic cultivation of microalgae. Here, carbon sources in SRWW were utilized for conversion into the form of value-added docosahexaenoic acid (DHA) using Aurantiochytrium sp. KRS101. Since SRWW is not a defined medium, serial optimizations were performed to maximize the biomass, lipid, and DHA yields by adjusting the nutrient (carbon, nitrogen, and phosphorus) concentrations as well as the application of salt stress. Optimum growth performance was achieved with 30% dilution of SRWW containing a total organic carbon of 95,488 mg L −1 . Increasing the nutrient level in the medium by supplementation of 9 g L −1 KH 2 PO 4 and 20 g L −1 yeast extract further improved the biomass yield by an additional 14%, albeit at the expense of a decrease in the lipid content. Maximum biomass, lipid, and DHA yields (22.9, 6.33, and 2.03 g L −1 , respectively) were achieved when 35 g L −1 sea salt was applied on a stationary phase for osmotic stress. These results demonstrate the potential of carbon-rich sugar refinery washing water for DHA production using Aurantiochytrium sp. KRS101 and proper cultivation strategy.",
"conclusion": "Conclusion SRWW containing high levels of organic carbon in the form of saccharides was applied to the heterotrophic cultivation of Aurantiochytrium sp. KRS101. Compared with the general basal medium, cultivation in optimized 30% SRWW resulted in higher biomass (2.41-fold increase), lipid content (2.23-fold higher), and DHA yield (1.54-fold increase). In addition, the total DHA yield was improved by 28% when the cells were subjected under sea salt stress by supplementation of the medium with 35 g L −1 additional sea salt at the stationary stage. It is likely that the overall lipid content and DHA production could be further improved by increasing the C:N ratio.",
"introduction": "Introduction Among an estimated total of over 300,000 species of microalgae 1 , numerous species have been found to have commercially desirable phenotypes including high biomass production, lipid content, and potential for value-added products 2 , 3 . In particular, a number of microalgal strains are capable of accumulating high levels of polyunsaturated fatty acids (PUFAs) and have been identified as a potential source of feedstock for the production of PUFAs as value-added products 4 – 6 . PUFAs are categorized as omega-3, omega-6, or omega-9 fatty acids depending on the position of the first double bond in relation to the methyl terminus 7 . Various types of PUFAs, such as omega-3 fatty acids including α-linolenic acid (ALA; C18:3 n-3), eicosapentaenoic acid (EPA; C20:5 n-3), and docosahexaenoic acid (DHA; C22:6 n-3) are essential fatty acids in the human diet 8 . DHA is a key omega-3 fatty acid that has beneficial health effects, including reducing the risks of human cardiovascular diseases, cancer, schizophrenia, and Alzheimer’s disease 9 . It also plays an important role as a structural lipid in cell membranes and it is necessary for proper visual and neurological development in infants 10 . While the majority of DHA in the nutraceutical market is derived from fish oils, there has been increasing interest in the commercial production of microalgal DHA. Microalgae-derived DHA have several advantages to overcome current concerns on fish-derived DHA. First of all, because of the food chain system in the ocean, fish tend to accumulate more amount of heavy metals and other toxic chemicals than microalgae 11 . In addition, it is reported that DHA separation process from microalgae is easier than fish’s profiles. Even more, DHA originated from microalgae have better absorbing property than that from fish oil, too 12 . Furthermore, recent research indicates that the production of omega-3 lipids from fish oil presents a sustainability issue because over 85% of the world’s fisheries are subject to overfishing or are depleted 13 . However, in the case of microalgae, it could be fully produced by designed cultivation system in the industry, therefore, there are no concerns about the fluctuation in the production or depletion. Of course, major microalgae culture system using photosynthesis might have regular fluctuation caused by light/dark cycle and seasonal changes. However, the value-added product like DHA could justify its higher cost for heterotrophic production using carbon sources and it means there will be well controlled system to produce DHA compensate the demand with stable production facility. Thus, PUFAs from oleaginous microalgae have attracted much attention as a sustainable source of essential omega-3 oils 14 . Aurantiochytrium sp. KRS101 is a candidate as a novel source of omega-3 fatty acids. This marine heterotroph requires conventional saccharides for carbon and energy sources 15 . Although the heterotrophic cultivation of microalgae can achieve a much higher cell density and faster growth rates compared with photoautotrophic cultivation, the cost of organic substrates (e.g. glucose) in a heterotrophic medium is much greater; the carbon source has been calculated to comprise of approximately 80% of the total cost of the growth medium 16 . To decrease the cultivation costs, alternative carbon sources have been intensively studied with respect to their conversion into fatty acids 17 – 19 . Various organic wastewaters have been studied as an alternative carbon source for economic heterotrophic cultivation of microalgae. However, applications of wastewater were generally limited to chemicals or biofuel production rather than food and nutraceutical products due to the possible presence of toxic chemicals, heavy metals, as well as unsanitary nature of most wastewaters 20 . In this point of view, finding a clean and safe carbon-rich wastewater is important for the production of human-edible products. Wastewater resulting from food manufactory facilities, such as sugar refineries can be a major target source as they contain high concentrations of organic carbon and low level of contamination 21 . The wastewaters arise from various uses ranging from washing the sugar cane, melting, concentrating, filtering, purifying the sugar and washing the vessel and line. This wastewater contains high levels of organic carbons which are in most cases recycled to be used in molasses or yeast production systems 22 . However, the sugar refinery washing water (SRWW) which results from cleaning equipment and transfer lines are primarily used as an additive in cattle feeds. Therefore, the advantage of using SRWW for low-cost fermentation processes is apparent, though, careful characterization and optimization will be needed for application on specific target strains and products. Generally, the productivity of certain metabolites based product is determined by the biomass productivity and the metabolites contents. While biomass productivity could be enhanced under favorable growth conditions, increasing the contents of some metabolites requires environmental stress. Therefore, various environmental factors have been applied as stimuli during cultivation in order to increase the contents of target metabolites 3 , 23 , 24 . It has been reported that lipid accumulation and composition are affected by environmental, chemical, and physical stimuli including salinity, growth medium pH, and temperature 25 . Among these, salinity is an important chemical stimulus causing physical osmotic pressure and commonly used to increase the lipid content of microalgae 26 , 27 . However, these factors are more often unfavorable for the growth of the organism and can reduce the overall biomass productivity. Taking these into account, the timing and level of the stimuli during cultivation also should be tested to maximize the productivity of the target metabolites by achieving the highest target product content when the cell biomass productivity was maximized 28 . In this study, sugar refinery washing water (SRWW) was used as a carbon source for the production of DHA during heterotrophic cultivation of the marine microalga Aurantiochytrium sp. KRS101. To maximize the DHA yield, a serial optimization on culture nutrient and salt stress strategy were implemented. Firstly, the SRWW concentration and macronutrients (C:N:P) ratio were optimized to increase the biomass yield during the first stage of cultivation. Subsequently, sea salt stress was applied during the exponential or stationary phase to increase the DHA content. Finally, the effects of both the sea salt concentration and the timing of stress induction on the DHA content and yield were investigated.",
"discussion": "Results and Discussion Chemical properties of sugar refinery washing water (SRWW) The growth profile and lipid productivity of Aurantiochytrium sp. KRS101 have been well studied using various carbon sources 29 . However, in the case of the undefined source such as SRWW, it is difficult to determine the nutrient consumption profile and substrate yield without proper characterization. Hence, in order to optimize Aurantiochytrium sp. KRS101 cultivation using SRWW as a sole carbon source, chemical and trace element properties of SRWW were analyzed (Table 1 and see Supplementary Materia l ). The results revealed that there were sufficient concentrations of calcium (32 times higher), ferric (212 times higher), and magnesium (8 times higher) ions compared with the basal media (containing 10 g L −1 yeast extract), and the levels of other components were similar to those in conventional media. The initial pH of SRWW was 3.4, which is less than optimum for the cultivation of this strain 30 . Therefore, in subsequent experiments, the pH was adjusted to 7.0 using a 10 N NaOH solution. The total organic carbon (TOC) and chemical oxygen demand (COD) in SRWW were estimated to be 95,488 ± 3,818 and 295,600 ± 2,837 mg L −1 , respectively. The glucose and sucrose concentrations in SRWW were measured separately and estimated to be 69,100 ± 930 and 5,050 ± 212 mg L −1 , respectively. These results show that SRWW contained sufficient carbon sources to previous researches using 5 to 80 g L −1 of only glucose or combination with fructose, and sucrose for the heterotrophic cultivation of Aurantiochytrium sp. KRS101 31 . However, the concentrations of other essential nutrients, including nitrogen (ammonia-nitrogen: 2.34 mg L −1 and nitrate-nitrogen 27.15 mg L −1 ) and phosphorus (phosphate: 63.38 mg L −1 ), were relatively lower than previous research (ammonia-nitrogen: 246.40 mg L −1 , nitrate-nitrogen: 246.40 mg L −1 , phosphate: 105.00 mg L −1 ) or the basal medium (yeast extract: 10,000 mg L −1 and phosphate: 6,300 mg L −1 ) which is ordinarily used for Aurantiochytrium sp. KRS101 (Table 1 ) 30 . Thus in subsequent experiments, nitrogen and phosphorus were supplemented in the form of yeast extract and KH 2 PO 4 , respectively. Table 1 Characteristics of the sugar refinery washing water (SRWW). Parameter Sugar refinery washing water (SRWW) pH 3.40 Total organic carbon (TOC, mg L −1 ) 95,488 ± 3,818 Chemical oxygen demand (COD, mg L −1 ) 295,600 ± 2,837 Total carbohydrate (TC, mg L −1 ) 138,263 ± 867 Glucose (mg L −1 ) 69,100 ± 930 Sucrose (mg L −1 ) 5,050 ± 212 Ammonia-nitrogen (NH 4 -N, mg L −1 ) 2.387 ± 0.163 Nitrate-nitrogen (NO 3 -N, mg L −1 ) 27.147 ± 0.620 Nitrite-nitrogen (NO 2 -N, mg L −1 ) ND Phosphorus-phosphate (PO 4 -P, mg L −1 ) 63.377 ± 3.008 ND: not detected. Effect of SRWW dilution ratio on the heterotrophic cultivation of Aurantiochytrium sp. KRS101 The effects of various concentrations of SRWW on growth, glucose concentration, and lipid production of Aurantiochytrium sp. KRS101 are shown in Fig. 1 . Heterotrophic cultivation was tested using five dilutions of SRWW (10, 20, 30, 40, and 50%), and the growth parameters were compared with those achieved during cultivation in the modified basal media containing 30 g L −1 glucose (Fig. 1a ). The biomass yield of Aurantiochytrium sp. KRS101 was measured as dry cell weight and it showed increased biomass yield as the concentration of SRWW increased (10.62, 16.59, and 19.55 g L −1 , respectively, linear correlation (R 2 = 0.9636)) from 10 to 30% at day 5. However, growth was inhibited when the SRWW concentration was higher than or equal to 40%, and there was no growth at 50% SRWW indicating that there was an optimal concentration of SRWW suitable for heterotrophic cultivation. Several studies have shown that excessive nutrients in growth media cause osmotic stress, which inhibits algal growth 32 , 33 . This is the main reason why high-density heterotrophic cultivation is often performed in continuous or semi-continuous fed-batch mode rather than with all the carbon source added to the medium at the start of cultivation. Consistent with previous research 34 , it appeared that excessive glucose at the commencement of culture caused osmotic shock to Aurantiochytrium cells, as cell disruption was observed when the cells were exposed to 50% SRWW. When the SRWW concentration was increased further (up to 60%), it was rare to find any normal cells in the culture liquid (see Supplementary Material). The concentration of glucose declined rapidly during cultivation, except in the treatment containing 50% SRWW, where no growth occurred (Fig. 1b ). Figure 1 Effect of various concentrations of sugar refinery washing waster (SRWW) on the: ( a ) biomass yield (dry cell weight), ( b ) glucose concentration, and ( c ) lipid content of Aurantiochytrium sp. KRS101 cultured under heterotrophic conditions. Error bars indicate mean ± standard deviation (n = 6 for ( a ), and 4 for ( b ) and ( c )). Statistical analysis was conducted with ANOVA tests (significant, P < 001) for ( a ) and ( c ) at day 5, and Student t-test, where ***P < 0.001, **P < 0.01, *P < 0.05 for all at day 5. Here, it should be noted that although the 30% SRWW medium contained less glucose (20 g L −1 ) than modified basal medium (30 g L −1 ), the maximum biomass yield achieved was greater in the former medium. One explanation for this observation is the presence of other carbon sources in SRWW. As sucrose can be disassociated into glucose and fructose under low pH conditions (Table 1 ) 35 , there were additional amounts of glucose and fructose that were not accounted for. A previous study also reported that Aurantiochytrium sp. KRS101 is capable of using various organic carbon sources 36 . Further studies will be needed to assess the possibility of carbon catabolite repression and the effects of multiple sugars in growth media during heterotrophic cultivation of Aurantiochytrium sp. KRS101. Another important factor in industrial fermentation is the conversion ratio from the glucose feedstock into cell biomass. As the SRWW concentration in the medium was increased (10, 20, 30, and 40%), the glucose to biomass conversion ratio declined (1.13, 0.97, 0.82, and 0.55 g biomass g −1 glucose, respectively). However, if the fructose converted from all the sucrose in the medium is taken into account, the total sugar to biomass conversion ratio for 40% SRWW would be 0.28, which is comparable to that in the basal medium control (Fig. 1b ). The lipid content was also affected by the concentration of SRWW (Fig. 1c ) and showed a proportional correlation with the biomass yield (Fig. 1a , linear correlation (R 2 = 0.9797)) when 10 to 30% SRWWs were used (30% SRWW - 19.55 g L −1 and 36.48% wt. biomass, 20% SRWW - 16.59 g L −1 and 32.56% wt. biomass, and 10% SRWW - 10.62 g L −1 and 16.74% wt. biomass). Among the tested conditions, the highest biomass yield (19.55 g L −1 at 5 days) and lipid content (36.48% wt. biomass) were achieved at 30% SRWW. In the control medium (30 g L −1 glucose), the cells entered death phase immediately after all the glucose in the medium was depleted; the biomass yield and lipid content in the control were 9.28 g L −1 in 5 days and 25.70% wt. biomass, respectively. These results confirmed that SRWW could be used as an alternative carbon source for the heterotrophic cultivation of Aurantiochytrium sp. KRS 101, with no negative effect on the lipid content. Consequently, 30% SRWW was used in subsequent experiments. Effect of the concentrations of KH 2 PO 4 and yeast extract on cell growth and lipid production The effects of nutrient conditions on cell growth and lipid production were investigated by testing various concentrations of nitrogen (yeast extract: 5, 10, 15, and 20 g L −1 ) and phosphorus (KH 2 PO 4 : 9 and 18 g L −1 ) in the medium (Fig. 2 ). There was a negligible difference in the biomass yield and lipid content between media containing 9 and 18 g L −1 KH 2 PO 4 ; this is because 9 g L −1 exceeded the minimum phosphorus requirement for growth. The concentration of phosphorus in organisms is far less than that of carbon or nitrogen; the Redfield ratio for C, N, and P in oceanic plankton is 106:16:1 37 . To prepare for prolonged periods of exposure to conditions where phosphorus may be limiting, microalgae continuously uptake phosphorus and store the excess in the form of intracellular phosphate granules 38 . Figure 2 Changes in biomass yield (dry cell weight) (gray bars) and lipid content (black squares) of Aurantiochytrium sp. KRS101 using 30% SRWW supplemented with various concentrations of yeast extract and KH 2 PO 4 . The control involved the culture grown in conventional modified basal media containing 30 g L −1 glucose. Two concentrations of KH 2 PO 4 (9 and 18 g L −1 ) and four concentrations of yeast extract (5, 10, 15, and 20 g L −1 ) were tested. Error bars indicate mean ± standard deviation (n = 3 and 6). ANOVA tests were conducted for biomass yield and lipid content, and both showed significant differences (P < 0.001). ANOVA test with post-hoc Tukey Honestly Significant Difference showed that groups having same concentration of phosphate ((9.5)–(18, 5), (9, 10)–(18, 10), (9, 15)–(18, 15), and (9, 20)–(18, 20)) have no significant differences (P > 0.05) for biomass yield and lipid content. Student t-test was also conducted and showed significant differences with control as ***P < 0.001, **P < 0.01, *P < 0.05. In contrast to phosphorus, the nitrogen content affected both the biomass yield and the lipid content (Fig. 2 ). The proportion of nitrogen in cell mass is relatively high compared with that of phosphorus and is directly linked to the de novo synthesis of proteins responsible for growth, metabolism, and other biological processes. Therefore, cultures supplied with higher levels of yeast extract showed higher biomass yield but had lower lipid content levels. These findings are consistent with previous research 31 , which showed that increased nitrogen concentrations had a negative relationship with lipid accumulation. In addition, a previous study 30 showed that the C:N ratio is a critical factor determining lipid accumulation in cells. As the microalgae had very low C:N ratios under the higher nitrogen concentrations tested, it is likely that higher lipid content and productivity could be achieved by feeding an additional carbon source. The maximum biomass yield (22.44 g L −1 in 5 days) was obtained in the medium containing 9 g L −1 KH 2 PO 4 and 20 g L −1 yeast extract, but the highest lipid content (47.93% wt. biomass) was obtained in the medium containing 9 g L −1 KH 2 PO 4 and 5 g L −1 yeast extract. Thus, the optimum growth condition for the first stage of cultivation was determined to be 9 g L −1 KH 2 PO 4 and 20 g L −1 yeast extract based on the biomass yield. Effect of salinity stress on biomass and lipid accumulation of Aurantiochytrium sp. KRS101 Optimization of the SRWW concentration as well as the levels of KH 2 PO 4 and yeast extract successfully increased the overall biomass production (Fig. 2 ). However, the increase in biomass yield was accompanied by a decrease in the lipid content, because the C:N ratio was suboptimal for lipid content. To attempt to compensate for this loss, the effect of sea salt stress on DHA accumulation in Aurantiochytrium sp. KRS101 was investigated. The effects of higher sea salt concentrations (30 and 35 g L −1 ) during the exponential (Fig. 3 ) and stationary (Fig. 4 ) phases on DHA yields, were investigated. It should be noted that the cells underwent 24 and 48 hours of osmotic stress when the stress was implemented on exponential and stationary phases, respectively. Figure 3 Effect of various concentrations of sea salt on the: ( a ) biomass yield (dry cell weight), ( b ) DHA yield (bar), and DHA content (line) of Aurantiochytrium sp. KRS101 cells in exponential phase. Error bars indicate mean ± standard deviation (n = 3). Statistical analysis were conducted with ANOVA tests for ( a ) and ( b ) at 48 h, and ( a ) at 48 h has no significant differences (P > 0.05) and DHA yield and DHA content at 48 h have significant differences as P < 0.001 and P < 0.01, respectively. Also, Student t-test was conducted and showed significant differences with no treatment as ***P < 0.001, **P < 0.01, *P < 0.05. Figure 4 Effect of various concentrations of sea salt on the: ( a ) biomass yield (dry cell weight), ( b ) DHA yield (bar), and DHA content (line) of Aurantiochytrium sp. KRS101 cells in stationary phase. Error bars indicate mean ± standard deviation (n = 3). ANOVA tests were conducted for ( a ) and ( b ) at 24 h, and ( a ) at 24 h showed no significant differences (P ≈ 0.05) and DHA yield and DHA content have significant differences as P < 0.001 and P < 0.05, respectively. Also, Student t-test was conducted and showed significant differences with no treatment as ***P < 0.001, **P < 0.01, *P < 0.05. When the culture was treated with 35 g L −1 of additional sea salt during the exponential phase, growth suppression was observed after 12 h, although gradual recovery occurred towards the end of the cultivation period (48 h; Fig. 3a ). Interestingly, however, the addition of 30 g L −1 sea salt resulted in an almost identical growth curve to that of the control indicating that the sea salt concentration did not cause osmotic stress. In addition, a slight increase in the overall DHA content was observed with 30 g L −1 of osmotic stress, while a small decrease was observed with 35 g L −1 . Subjecting the cells to 30 g L −1 of salt stress resulted in an increase in the DHA yield, but 35 g L −1 of additional salt. The utilization the overall yield because of the combination of lower biomass production and lower DHA content per unit biomass. In general, it appeared that subjecting the cells to osmotic stress during the exponential phase did not result in a substantial increase in DHA production. It is likely due to the fact that the culture was bottlenecked by the lack of carbon availability, and particularly that the higher nitrogen content during the first stage of growth resulted in greater cell proliferation. Thus, the cells were unable to assimilate extra carbon from the environment for de novo lipid synthesis, despite being under osmotic stress. When additional sea salt was added at the stationary phase there was no significant change in biomass yield under any tested conditions (Fig. 4a ). This is probably because the cells had assimilated all the nutrients during the first stage of growth. The DHA content in the control culture showed a minor decrease, from 7.96 ± 0.36% wt. biomass at the start of the stationary phase to 7.04 ± 0.06% wt. biomass after 24 h. However, cultures under osmotic stress showed an increase in the DHA content with 30 g L −1 and 35 g L −1 of additional sea salt yielding DHA contents of 7.89 ± 0.23% wt. biomass and 8.85 ± 0.25% wt. biomass, respectively (Fig. 4b ). The increase in the DHA content also resulted in an improvement in the DHA yield under both the 30 and 35 g L −1 treated osmotic stress conditions. Therefore, these results indicated that subjecting the cells to osmotic stress at the beginning of the stationary phase was more effective at improving DHA production than applying the stress during the exponential phase. Though DHA content in stationary phase treatment looked similar with that in exponential phase treatment, it is coupled with stable biomass yield and enhanced lipid content, and resulted in the highest DHA yield with 35 g L −1 sea salt treatment at day 5 as Fig. 4b . Previous studies have reported that Aurantiochytrium sp. is insensitive to the sea salt concentration during the initial phase of growth 31 , 39 . In contrast, these results revealed that treating the culture with higher concentrations of sea salt during the exponential phase caused some reduction in biomass production, while osmotic stress applied during the stationary phase resulted in higher DHA production with little negative impact on the biomass. However, it should be noted that the study was unable to exploit the full potential of the sea salt stress, due to the limitations on de novo lipid synthesis imposed upon by low C:N ratio. Comparison of biomass yield, lipid yield, DHA yield, and the fatty acid profile of cells under various culture conditions To assess the effects of SRWW concentration, nutrient optimization, and stress induction on the biomass, lipid, and DHA yields, the fatty acid profiles of Aurantiochytrium sp. KRS101 were compared as shown in Fig. 5 . Use of 30% SRWW significantly increased the biomass yield, lipid yield, and DHA yield (biomass yield (DCW): 9.27 to 19.55 g L −1 ; lipid yield: 2.38 to 7.13 g L −1 ; DHA yield: 1.02 to 1.31 g L −1 ) of Aurantiochytrium sp. KRS101 (Fig. 5a ), mainly because of the enhanced DCW and lipid content. The total DHA yield also increased, despite the fact that the DHA composition in the fatty acid profile decreased from 29.50 to 25.66% (Fig. 5b ). It appears that the higher TOC level in the 30% SRWW enabled the microalgae to achieve higher biomass yields as well as lipid content. Substitution of glucose with SRWW also caused changes in the fatty acids profile that there was increase in the portion of saturated fatty acids (SFAs) and it was mainly caused by a shift from C14:0 (9.54, 4.18%, respectively) to C16:0 (44.09, 59.96%, respectively) and a decrease in the portion of one of the polyunsaturated fatty acids (PUFAs, especially DHA; C22:6 n-3). In the previous research 19 , similar sugar factory wastewater was used as an alternative carbon source on green algae, Ettlia sp., and it showed decrease in the portion of both SFAs and PUFAs, and increase in the portion of monounsaturated fatty acids (MUFAs). The utilization of carbon sources from both SRWW and sugar factory wastewater showed better cell growth and lipid accumulation in both cases, but differences in a genus and specific culture conditions caused verified changes in fatty acids profile. Additional optimization of the nitrogen and phosphorus sources further enhanced the performance of the 30% SRWW, as the total DCW increased up to 22.44 g L −1 . Despite the decrease lipid content (30% SRWW - 36.48 to optimized 30% SRWW - 23.71%wt. biomass, Fig. 2 ) caused by excessive nutrients, the increase in the DHA content in the lipid (30% SRWW - 18.45 to 35 g L −1 sea salt stress - 32.04%wt. fatty acids, Fig. 5b ) resulted in a marked improvement in the DHA yield (up to 1.57 g L −1 ). The DHA yield was also improved (up to 2.03 g L −1 ) by subjecting stationary phase cells to sea salt stress. Therefore, adopting 30% SRWW is successfully increase the biomass yield, optimized nutrient condition stabilize DHA content, and sea salt stress further enhanced DHA content. Figure 5 Changes in the: ( a ) biomass yield (dry cell weight, gray bars), lipid yield (blue squares), DHA yield (red circles), and ( b ) fatty acid profiles of Aurantiochytrium sp. KRS101 cultured under various heterotrophic conditions of sea salt stress. Error bars indicate mean ± standard deviation (n = 3). ANOVA tests were conducted for ( a ) and it showed significant differences (P < 0.001) for all biomass yield (dry cell weight), lipid yield, and DHA yield. Also, Student t-test was conducted and showed significant differences with no treatment as ***P < 0.001, **P < 0.01, *P < 0.05."
} | 7,079 |
35491853 | PMC9239258 | pmc | 8,093 | {
"abstract": "ABSTRACT Cellulose is the most abundant polysaccharide in plant biomass and an important precursor of soil organic matter formation. Fungi play a key role in carbon cycling dynamics because they tend to decompose recalcitrant materials. Here, we applied [ 12 C]cellulose and [ 13 C]cellulose to distinguish the effects of application of compost, nitrogen-phosphorus-potassium (NPK) fertilizer, and no fertilizer (control) for 27 years upon cellulose decomposition via RNA-based stable isotope probing (RNA-SIP). The loss ratio of added cellulose C in compost soil was 67.6 to 106.7% higher than in NPK and control soils during their 20-day incubation. Dothideomycetes (mainly members of the genus Cryptococcus ) dominated cellulose utilization in compost soil, whereas the copiotrophic Sordariomycetes were more abundant in NPK and unfertilized soils. Compared with NPK and control soils, compost application increased the diversity of 13 C-assimilating fungi. The 13 C-labeled fungal communities in compost soil were more phylogenetically clustered and exhibited greater species relatedness than those in NPK and control soils, perhaps because of stringent filtering of narrow-spectrum organic resources and biological invasion originating from added compost. These changes led to an augmented decomposition capacity of fungal species for cellulose-rich substrates and reduced cellulose C sequestration efficiency. The RNA-SIP technique is more sensitive to responses of fungi to altered soil resource availability than DNA-SIP. Overall, long-term compost application modified fungal community composition and promoted fungal diversity and phylogenetic relatedness, accelerating the decomposition of substrate cellulose in soil. This work also highlights the RNA-SIP technique’s value for comprehensively assessing the contributions of active fungi to the substrate decomposition process.",
"conclusion": "Conclusions. How long-term application of compost and NPK fertilizers affects soil fungal communities and the consequences for cellulose decomposition were both experimentally investigated in this study. Dothideomycetes (mainly the genus Cryptococcus ) dominated cellulose utilization in compost soil, whereas the copiotrophic Sordariomycetes were more abundant in both NPK and unfertilized soils. The compost amendment promoted fungal diversity and phylogenetic relatedness and strengthened the decomposition capacity of fungi for cellulose-rich substrates by enhancing synergistic interactions. The RNA-based SIP technique is sensitive enough to detect responses of fungi to local shifts in soil resource availability and could efficiently distinguish slow-growing microorganisms. Overall, because of the augmented decomposition capacity of fungal species for cellulose-rich substrates, the accumulation of cellulose-derived C is less efficient in compost-treated soil.",
"introduction": "INTRODUCTION Increasing soil organic carbon (SOC) sequestration improves soil fertility and mitigates climate change ( 1 ). The input of organic materials such as crop residues, whose biomass is now 3.8 × 10 9 tons year −1 globally ( 2 ), offers an effective and promising approach to sequester more SOC ( 3 , 4 ). Cellulose is the richest component in crop residues ( 5 ), but its degradation depends on the concerted action of multiple enzymes, such as endoglucanases, cellobiohydrolases, and β-glucosidase ( 6 ). During the decomposition of cellulose, part of cellulose-derived C is mineralized into CO 2 , whereas the other portion can accumulate in soil as microbial necromass and metabolites ( 7 ). Fungi are pivotal for cellulose decomposition because they can extend their hyphae to access substrates and produce extracellular enzymes which break down recalcitrant compounds, namely, cellulose ( 8 ). Certain fungal taxa, such as Sordariomycetes , Staphylotrichum , and Dothideales , are the main utilizers of cellulose in soils ( 9 , 10 ). However, a fundamental understanding of how fungal community composition and diversity affect cellulose decomposition is still lacking. Long-term application of organic fertilizers to soil can shift fungal community composition toward more saprotrophic fungi and higher fungal diversity ( 11 , 12 ), possibly due to the increased organic substances and colonization by exogenous species from organic amendments ( 13 ). Recently, Fang et al. ( 14 ) found that an increase in saprotrophic fungal abundance resulted in higher rates of decomposition of leaf litter in forest soil around arbuscular mycorrhizal trees than ectomycorrhizal trees. Earlier, Ling et al. ( 15 ) demonstrated that in comparison with chemical fertilizers, organic amendments support stronger functional potential by enhancing the diversity and abundance of functional groups with respect to C-, N- and P-related metabolism. In particular, it has been shown that cocultures of diverse species can break down substrate biomass (i.e., lignocellulose and cellulose) more efficiently than can the same species in monocultures ( 16 , 17 ). In general, greater microbial diversity entails more complex microbial interactions and effectively promotes soil functioning, such as C decomposition, by producing complementary enzymes acting at different sites of targeted compounds or by enhancing overall enzyme production ( 18 – 20 ). For example, “sugar” fungi, which cannot break down cellulose, are able to use the labile products of cellulose decomposition by cellulolytic fungi, such as cellobiose ( 21 ). This contributes to improving the cellulase activities of cellulolytic species by alleviating product inhibition ( 22 ), thereby accelerating the substrates’ decomposition. Nucleic acid-based stable isotope probing (SIP), whereby stable isotopes such as 13 C derived from labeled substrates are incorporated into microbial nucleic acids followed by high-throughput sequencing, can provide a way to link phylogenetic information of microbes to their functioning ( 23 ). The DNA-SIP technique has been widely used to investigate active microbes utilizing organic substances, such as the organic compounds glucose ( 24 ), cellulose ( 10 , 25 ), and lignin ( 26 ), as well as some heterogeneous materials, such as straw residues ( 27 ) and root ( 28 ). However, because DNA has a long residence time in soil, any relic DNA, including extracellular DNA and nondecomposed DNA from dead cells, may obscure the real changes in metabolically active microbial communities ( 29 ). In contrast, RNA-SIP has higher sensitivity than DNA-SIP due to the faster turnover and isotopic incorporation of RNA than DNA ( 30 ); hence, it is useful for identifying microbial communities that are actively involved in ecological processes at the temporal scale of sampling. However, the instability of RNA renders this technique more challenging for assessing specific functions of the active microbial community. In this study, soils sampled from the plots of three treatments in a long-term (27-year) fertilization field experiment were incubated with [ 12 C]cellulose and [ 13 C]cellulose. 13 C RNA-SIP with subsequent high-throughput sequencing was used to characterize the soil fungal communities during cellulose decomposition. The objectives were 3-fold: (i) to identify 13 C-assimilating fungal communities and determine their impact on cellulose decomposition, (ii) to evaluate the influence on cellulose-using fungi of different fertilizers’ application, and (iii) to compare differences in the response of fungal species to cellulose amendment as determined by RNA-SIP and DNA-SIP techniques. We hypothesized that long-term compost application alters fungal community composition, thereby stimulating cellulose decomposition and turnover to soil organic matter.",
"discussion": "DISCUSSION Fungal communities regulated by fertilization influence cellulose decomposition. Long-term compost amendment altered the composition of the 13 C-assimilating fungal community and strongly influenced soil cellulose C turnover. Dothideomycetes dominated cellulose utilization in compost soil, whereas Sordariomycetes were more prevalent in both NPK and unfertilized soils ( Fig. 3 ). These results are consistent with those of Schneider et al. ( 31 ), who found that Sordariomycetes and Dothideomycetes (all Ascomycetes ) were the dominant cellulase producers for cellulose decomposition and reported their key involvement in the breakdown of plant biomass ( 32 , 33 ). Dothideomycetes commonly occur in more extreme ecological niches and exhibit a considerable capacity to maintain cooperative metabolic associations with other species ( 34 ). For example, Dothideomycetes were associated with the depolymerization of recalcitrant polymers during plant litter decomposition ( 35 ) and could serve as indicators for slow and passive organic C decomposition in the upper-layer soil (0- to 15-cm depth) of the Alaskan tundra ( 36 ). Accordingly, in compost soil, the input of complex organic materials favored the growth of Dothideomycetes ( 37 ), thereby contributing to the breakdown of cellulose. In contrast, Sordariomycetes are ubiquitous in agricultural soils ( 38 ), largely because members of this class are fast-growing species that become quickly abundant there given their high capacities to use labile C resources ( 39 ). Our previous study found that compared with NPK and control soils, the oxygen effective diffusion coefficient in compost soil was decreased to 1.30 × 10 −6 m 2 s −1 from 3.05 × 10 −6 to 5.19 × 10 −6 m 2 s −1 due to more macroaggregate formation ( 40 ). It is likely that more oxygen availability in NPK and unfertilized soils favors the proliferation of Sordariomycetes species, in that most of them are aerobic. Members of Sordariomycetes are able to use a wide variety of substrates, and the majority of them are known to have saprotrophic abilities ( 41 ). Therefore, they generally flourish in response to cellulose-rich straw amendments and are key decomposers of organic materials in soils ( 42 ). Microbial biomarker analysis can advance the understanding of how microbial communities modulate the decomposition process of organic materials in soils. Here, the genus Cryptococcus , in the phylum Basidiomycota , was more abundant in compost soil than NPK and control soils ( Fig. 4 ). Members of Cryptococcus are characterized as oligotrophs and often adapt well to severe environments, such as polar regions ( 43 ) and arid soils ( 44 ), with the help of polysaccharide capsules, which enable a better access to nutrients via fungal hyphae ( 45 ). The unfavorable soil niches in compost soil, like labile C deficiency and low oxygen concentration ( 37 , 40 ), therefore are beneficial for the proliferation of Cryptococcus . Previous studies documented that Cryptococcus has the potential to improve soil C cycling, inhibit pathogens, and promote crop yield ( 46 ). It seems that some members of Cryptococcus improved microbiota activity by suppressing the cytotoxicity of pathogens and accelerated substrate C turnover. Furthermore, Cryptococcus is well known for its high capacity to decompose complex organic substances by producing extracellular enzymes ( 47 ) and shows negative correlations with SOC content ( 48 ). Consequently, the enhanced population of Cryptococcus potentially increased catabolism rates of cellulose derived C by increasing enzyme production and reduced 13 C sequestration efficiency. We found that the NTI values for 13 C-assimilating fungi were higher than zero in compost soil yet close to zero in NPK and control soils, indicating that 13 C-labeled fungal communities in compost soil were phylogenetically clustered and had higher species relatedness. Environmental filtering is thought to play a key role in the assembly of fungal communities ( 49 ). In this respect, the availability of organic materials has been shown to impose a stringent filter on fungal taxa for the selection of closely related species ( 50 , 51 ). First, compost amendment typically incorporates narrow-spectrum C resources, such as stable hydrophobic materials and lignocellulose, into soil ( 37 ). This would strengthen the niche-filtering effect on the fungal community according to the species-sorting concept ( 52 ), since most fungal species have particular preferences for certain substrates ( 53 ), resulting in phylogenetic niche conservatism of fungal communities in compost soil ( 54 ). Second, biological invasion from added organic fertilizers possibly filtered out some native soil microbial species, whose competitive advantage is low, through strengthened interspecific competition ( 13 ). These processes would lead to the extinction of some fungal species due to their poor adaptation to abrupt changes in environmental conditions and, accordingly, reduced fungal diversity ( 55 ). However, compost soil harbored higher fungal diversity than NPK and control soils ( Fig. 2 ). The direct input of organic fertilizers introduces diverse fungal species, the majority of which can persistently colonize the soil due to their preference for recalcitrant resources ( 56 , 57 ). Following a 15-year organic fertilization, Sun et al. ( 13 ) found that exogenous fungal species from added manure accounted for up to 10.9% of soil fungal richness. Therefore, the greater diversity we observed in compost-treated soil could have arisen from the introduction of exogenous fungi. Microbial diversity is pivotal in soil nutrient cycling processes such as C decomposition ( 58 – 60 ). Here, the diversity of 13 C-labeled fungi was positively correlated with cellulose decomposition rates ( Fig. 5 ). This result is consistent with work by Juarez et al. ( 61 ) and Maron et al. ( 62 ); using a dilution-to-extinction approach in microcosm experiments, they found that SOC mineralization increased as soil microbial diversity increased. These findings suggest that the coexistence of multiple fungal groups may promote their functional capacities and hasten the C cycling process ( 63 , 64 ). The complementarity function niche hypothesis states that many distinct species can utilize C resources successively, by producing complementary enzymes during the substrate decomposition process ( 65 ). Consequently, fungal communities with higher diversity are more apt to generate greater complementarity effects, which could have contributed to the depolymerization of cellulose in compost soil. Moreover, the observation that the diverse fungal taxa were characterized by pronounced clustering and connectivity in compost soil suggests a strengthened pattern in synergistic interactions for C utilization ( 66 ). Microbial groups with a high degree of interspecies dependence can induce more complex and positive interactions, leading to high C consumption in soils with long-term unbalanced fertilization ( 67 ). Therefore, it is likely that in our study, the compost amendment increased the capacity of soil fungal species to decompose cellulose-rich substrates by enhancing such complementarity interactions, whose outcome is a better collective exploitation of cellulose-derived C in soil ( 68 ). Comparison of 13 C-assimilating fungal communities determined by DNA- and RNA-SIP. Similar to our previous measurement of 13 C-assimilating fungal community using DNA-SIP ( Fig. S5 ), the RNA-SIP technique also identified Ascomycota dominating cellulose utilization across all soil treatments ( Fig. 3 ). This is because those members of Ascomycota (mostly saprotrophic fungi) are highly enriched in arable soils and thrive in response to cellulose amendments ( 38 , 41 ). However, the RNA-SIP and DNA-SIP techniques uncovered different 13 C-labeled fungal communities in soils. Compost amendment increased the relative abundance of Basidiomycota at the RNA level while increasing that of Ascomycota at the DNA level compared with NPK and unfertilized soils. The RNA-based microbial species are more sensitive to changes in soil resource availability due to their rapid incorporation of substrate-derived C into RNA ( 69 ). As such, they are expected to be metabolically active at the time of sampling ( 30 , 70 ). Another advantage to using RNA-SIP is that it requires a lower substrate 13 C enrichment of 10 atom% ( 71 ) than the 20 atom% needed for DNA-SIP ( 72 ). Hence, the RNA-based SIP technique could effectively target slow-growing microbial species capable of actively synthesizing RNA but not DNA. The low oxygen availability in compost soil due to increased macroaggregation possibly suppressed the growth of fast-growing Ascomycota ( 40 ). The reduced 13 C content in compost soil during incubation also adversely affected Ascomycota ’s proliferation, since its members generally tend to thrive on C-rich substrates ( 42 ). Conversely, more recalcitrant organic substances derived from cellulose, such as microbial necromass and by-products, were readily available for Basidiomycota , whose members are characterized by low growth rates and prefer to decompose recalcitrant polymers ( 39 ). In contrast, the DNA-SIP technique may favor fast-growing fungi with high turnover rates that incorporate most of the newly added 13 C to repair or duplicate their DNA ( 73 ). Moreover, the DNA-SIP analysis tends to target the most abundant functional members of a community, including its dead and metabolically active taxa, simply because DNA persists longer than RNA in soil ( 74 ). Consequently, compared with RNA-SIP, the DNA-SIP approach is liable to overestimate the relative abundance of metabolically active Ascomycota . Our results suggest that RNA-based microbial analysis could be more robust at detecting ecologically active microorganisms, especially slow-growing microbes, in response to variations in available soil resources. The RNA-SIP technique revealed higher levels of 13 C-labeled fungal diversity across all test soils in comparison with DNA-SIP ( Fig. 2 and Fig. S6 ), indicating that RNA-SIP could recover fungal diversity more comprehensively than DNA-SIP ( 75 ). This is because microorganisms with low isotopic incorporation arising from their low growth rate and low competitive advantage for C resources can be reliably detected by RNA-SIP ( 70 , 71 ). Interestingly, at the RNA level, the compost soil featured higher fungal diversity than the NPK and control soils, but this pattern was reversed at the DNA level. This suggests that in compost treatment, more diverse species participated in cellulose utilization and fungal synergistic interactions might have played a more important role than expected by DNA-SIP. Therefore, our work emphasizes the importance of using the RNA-SIP technique to discern active participants in substrate utilization and to comprehensively assess microbial contributions to decomposition processes in soils. Conclusions. How long-term application of compost and NPK fertilizers affects soil fungal communities and the consequences for cellulose decomposition were both experimentally investigated in this study. Dothideomycetes (mainly the genus Cryptococcus ) dominated cellulose utilization in compost soil, whereas the copiotrophic Sordariomycetes were more abundant in both NPK and unfertilized soils. The compost amendment promoted fungal diversity and phylogenetic relatedness and strengthened the decomposition capacity of fungi for cellulose-rich substrates by enhancing synergistic interactions. The RNA-based SIP technique is sensitive enough to detect responses of fungi to local shifts in soil resource availability and could efficiently distinguish slow-growing microorganisms. Overall, because of the augmented decomposition capacity of fungal species for cellulose-rich substrates, the accumulation of cellulose-derived C is less efficient in compost-treated soil."
} | 4,959 |
28522969 | PMC5415673 | pmc | 8,096 | {
"abstract": "We introduce Equilibrium Propagation, a learning framework for energy-based models. It involves only one kind of neural computation, performed in both the first phase (when the prediction is made) and the second phase of training (after the target or prediction error is revealed). Although this algorithm computes the gradient of an objective function just like Backpropagation, it does not need a special computation or circuit for the second phase, where errors are implicitly propagated. Equilibrium Propagation shares similarities with Contrastive Hebbian Learning and Contrastive Divergence while solving the theoretical issues of both algorithms: our algorithm computes the gradient of a well-defined objective function. Because the objective function is defined in terms of local perturbations, the second phase of Equilibrium Propagation corresponds to only nudging the prediction (fixed point or stationary distribution) toward a configuration that reduces prediction error. In the case of a recurrent multi-layer supervised network, the output units are slightly nudged toward their target in the second phase, and the perturbation introduced at the output layer propagates backward in the hidden layers. We show that the signal “back-propagated” during this second phase corresponds to the propagation of error derivatives and encodes the gradient of the objective function, when the synaptic update corresponds to a standard form of spike-timing dependent plasticity. This work makes it more plausible that a mechanism similar to Backpropagation could be implemented by brains, since leaky integrator neural computation performs both inference and error back-propagation in our model. The only local difference between the two phases is whether synaptic changes are allowed or not. We also show experimentally that multi-layer recurrently connected networks with 1, 2, and 3 hidden layers can be trained by Equilibrium Propagation on the permutation-invariant MNIST task.",
"introduction": "1. Introduction The Backpropagation algorithm to train neural networks is considered to be biologically implausible. Among other reasons, one major reason is that Backpropagation requires a special computational circuit and a special kind of computation in the second phase of training. Here, we introduce a new learning framework called Equilibrium Propagation, which requires only one computational circuit and one type of computation for both phases of training. Just like Backpropagation applies to any differentiable computational graph (and not just a regular multi-layer neural network), Equilibrium Propagation applies to a whole class of energy based models (the prototype of which is the continuous Hopfield model). In Section 2, we revisit the continuous Hopfield model (Hopfield, 1984 ) and introduce Equilibrium Propagation as a new framework to train it. The model is driven by an energy function whose minima correspond to preferred states of the model. At prediction time, inputs are clamped and the network relaxes to a fixed point, corresponding to a local minimum of the energy function. The prediction is then read out on the output units. This corresponds to the first phase of the algorithm. In the second phase of the training framework, when the target values for output units are observed, the outputs are nudged toward their targets and the network relaxes to a new but nearby fixed point which corresponds to slightly smaller prediction error. The learning rule, which is proved to perform gradient descent on the squared error, is a kind of contrastive Hebbian learning rule in which we learn (make more probable) the second-phase fixed point by reducing its energy and unlearn (make less probable) the first-phase fixed point by increasing its energy. However, our learning rule is not the usual contrastive Hebbian learning rule and it also differs from Boltzmann machine learning rules, as discussed in Sections 4.1 and 4.2. During the second phase, the perturbation caused at the outputs propagates across hidden layers in the network. Because the propagation goes from outputs backward in the network, it is better thought of as a “back-propagation.” It is shown by Bengio and Fischer ( 2015 ) and Bengio et al. ( 2017 ) that the early change of neural activities in the second phase corresponds to the propagation of error derivatives with respect to neural activities. Our contribution in this paper is to go beyond the early change of neural activities and to show that the second phase also implements the (back)-propagation of error derivatives with respect to the synaptic weights, and that this update corresponds to a form of spike-timing dependent plasticity, using the results of Bengio et al. ( 2017 ). In Section 3, we present the general formulation of Equilibrium Propagation: a new machine learning framework for energy-based models. This framework applies to a whole class of energy based models, which is not limited to the continuous Hopfield model but encompasses arbitrary dynamics whose fixed points (or stationary distributions) correspond to minima of an energy function. In Section 4, we compare our algorithm to the existing learning algorithms for energy-based models. The recurrent back-propagation algorithm introduced by Pineda ( 1987 ) and Almeida ( 1987 ) optimizes the same objective function as ours but it involves a different kind of neural computation in the second phase of training, which is not satisfying from a biological perspective. The contrastive Hebbian learning rule for continuous Hopfield nets described by Movellan ( 1990 ) suffers from theoretical problems: learning may deteriorate when the free phase and clamped phase land in different modes of the energy function. The Contrastive Divergence algorithm (Hinton, 2002 ) has theoretical issues too: the CD 1 update rule may cycle indefinitely (Sutskever and Tieleman, 2010 ). The equivalence of back-propagation and contrastive Hebbian learning was shown by Xie and Seung ( 2003 ) but at the cost of extra assumptions: their model requires infinitesimal feedback weights and exponentially growing learning rates for remote layers. Equilibrium Propagation solves all these theoretical issues at once. Our algorithm computes the gradient of a sound objective function that corresponds to local perturbations. It can be realized with leaky integrator neural computation which performs both inference (in the first phase) and back-propagation of error derivatives (in the second phase). Furthermore, we do not need extra hypotheses such as those required by Xie and Seung ( 2003 ). Note that algorithms related to ours based on infinitesimal perturbations at the outputs were also proposed by O'Reilly ( 1996 ) and Hertz et al. ( 1997 ). Finally, we show experimentally in Section 5 that our model is trainable. We train recurrent neural networks with 1, 2, and 3 hidden layers on MNIST and we achieve 0.00% training error. The generalization error lies between 2 and 3% depending on the architecture. The code for the model is available 1 for replicating and extending the experiments.",
"discussion": "6. Discussion, looking forward From a biological perspective, a troubling issue in the Hopfield model is the requirement of symmetric weights between the units. Note that the units in our model need not correspond exactly to actual neurons in the brain (it could be groups of neurons in a cortical microcircuit, for example). It remains to be shown how a form of symmetry could arise from the learning procedure itself (for example from autoencoder-like unsupervised learning) or if a different formulation could eliminate the symmetry requirement. Encouraging cues come from the observation that denoizing autoencoders without tied weights often end up learning symmetric weights (Vincent et al., 2010 ). Another encouraging piece of evidence, also linked to autoencoders, is the theoretical result from Arora et al. ( 2015 ), showing that the symmetric solution minimizes the autoencoder reconstruction error between two successive layers of rectifying (ReLU) units, suggesting that symmetry may arise as the result of an additional objective function making successive layers form an autoencoder. Also, Lillicrap et al. ( 2014 ) show that the backpropagation algorithm for feedforward nets also works when the feedback weights are random, and that in this case the feedforward weight tend to “align” with the feedback weights. Another practical issue is that we would like to reduce the negative impact of a lengthy relaxation to a fixed point, especially in the free phase. A possibility is explored by Bengio et al. ( 2016 ) and was initially discussed by Salakhutdinov and Hinton ( 2009 ) in the context of a stack of RBMs: by making each layer a good autoencoder, it is possible to make this iterative inference converge quickly after an initial feedforward phase, because the feedback paths “agree” with the states already computed in the feedforward phase. Regarding synaptic plasticity, the proposed update formula can be contrasted with theoretical synaptic learning rules which are based on the Hebbian product of pre- and post-synaptic activity, such as the BCM rule (Bienenstock et al., 1982 ; Intrator and Cooper, 1992 ). The update proposed here is particular in that it involves the temporal derivative of the post-synaptic activity, rather than the actual level of postsynaptic activity. Whereas our work focuses on a rate model of neurons, see Feldman ( 2012 ) for an overview of synaptic plasticity that goes beyond spike timing and firing rate, including synaptic cooperativity (nearby synapses on the same dendritic subtree) and depolarization (due to multiple consecutive pairings or spatial integration across nearby locations on the dendrite, as well as the effect of the synapse's distance to the soma). In addition, it would be interesting to study update rules which depend on the statistics of triplets or quadruplets of spikes timings, as in Froemke and Dan ( 2002 ) and Gjorgjievaa et al. ( 2011 ). These effects are not considered here but future work should consider them. Another question is that of time-varying input. Although this work makes back-propagation more plausible for the case of a static input, the brain is a recurrent network with time-varying inputs, and back-propagation through time seems even less plausible than static back-propagation. An encouraging direction is that proposed by Ollivier et al. ( 2015 ) and Tallec and Ollivier ( 2017 ), which shows that computationally efficient estimators of the gradient can be obtained using a forward method (online estimation of the gradient), which avoids the need to store all past states in training sequences, at the price of a noisy estimator of the gradient."
} | 2,694 |
35465293 | null | s2 | 8,097 | {
"abstract": "Automation of the process of developing biophysical conductance-based neuronal models involves the selection of numerous interacting parameters, making the overall process computationally intensive, complex, and often intractable. A recently reported insight about the possible grouping of currents into distinct biophysical modules associated with specific neurocomputational properties also simplifies the process of automated selection of parameters. The present paper adds a new current module to the previous report to design spike frequency adaptation and bursting characteristics, based on user specifications. We then show how our proposed grouping of currents into modules facilitates the development of a pipeline that automates the biophysical modeling of single neurons that exhibit multiple neurocomputational properties. The software will be made available for public download via our site cyneuro.org."
} | 229 |
37985709 | PMC10963064 | pmc | 8,098 | {
"abstract": "Abstract Awareness is growing that human health cannot be considered in isolation but is inextricably woven with the health of the environment in which we live. It is, however, under-recognized that the sustainability of human activities strongly relies on preserving the equilibrium of the microbial communities living in/on/around us. Microbial metabolic activities are instrumental for production, functionalization, processing, and preservation of food. For circular economy, microbial metabolism would be exploited to produce building blocks for the chemical industry, to achieve effective crop protection, agri-food waste revalorization, or biofuel production, as well as in bioremediation and bioaugmentation of contaminated areas. Low pH is undoubtedly a key physical–chemical parameter that needs to be considered for exploiting the powerful microbial metabolic arsenal. Deviation from optimal pH conditions has profound effects on shaping the microbial communities responsible for carrying out essential processes. Furthermore, novel strategies to combat contaminations and infections by pathogens rely on microbial-derived acidic molecules that suppress/inhibit their growth. Herein, we present the state-of-the-art of the knowledge on the impact of acidic pH in many applied areas and how this knowledge can guide us to use the immense arsenal of microbial metabolic activities for their more impactful exploitation in a Planetary Health perspective.",
"conclusion": "Conclusions In this review, we highlighted the importance of the exploitation of the knowledge on the responses and activity at low pH of micro-organisms, both neutralophilic and acidophilic, for the development of effective strategies for disease management in agriculture, implementation of bioprocesses and biotechnological applications in waste valorization, sustainable, and natural preservation of foods and their functionalization. Figure 4 shows the network analysis based on the literature (titles and abstracts) used in this review visualized with the software VOS (van Eck and Waltman 2010 ). Using the parameters provided in the legend to Fig. 4 , the analysis generated five clusters of terms: the blue cluster includes mostly food-related terms; the green cluster includes terms related to bioproduction of platform chemicals and very close to this cluster there is the yellow cluster which includes waste valorization for biogas production and circular economy; the red cluster includes terms that are more related to crop protection and remediation of polluted environments; finally, the violet cluster includes terms of medical interest. The proximity of “lactic acid” “yield” and “productivity” with “waste,” “value,” and “biogas production” highlights the dedication to the circular economy concept and the consideration of the financial and efficiency aspects. This aspect will need to be acknowledged in future developments of highly productive micro-organisms, efficient in the presence of stressors, including acidic pH. Interestingly “lactic acid bacteria” (LAB) are closely connected to “food” in the blue cluster, however, “lactic acid”, though linked to LAB, belongs to another cluster: this highlights the transition of LAB from only food-relevant micro-organisms to producers of a valuable platform chemical. This offers an elegant model for expanding the use of organic acids microbial producers to the large-scale bioproduction of platform chemicals. Figure 4. Occurrence and links of terms found in abstracts and titles of the scientific and review articles cited in this review. The Network is generated using VOSviewer (version 1.6.19) (van Eck and Waltman 2010 ). Criteria for map generation included 15 minimum occurrences of a term. For network visualization, default settings were used for normalization and layout, except for clustering for which a minimum of six terms was set to generate a cluster. A total of 105 terms were extracted, of which the most relevant terms (60% of total, as set by default) were visualized after manually removing 12 terms (mutant, host, water, response, ability, glucose, paper, factor, microbe, cell, bacterium, and mechanism) that though occurring frequently were much less specific than other terms which could be better visible in the network. A thesaurus file was generated and used to count some terms as the same term (e.g. PAW as plasma activated water; LAB as lactic acid bacteria; and volatile fatty acids as VFA). As discussed, engineering of highly productive micro-organisms and improvement in process engineering could decrease the environmental footprint of processes, maximizing substrate valorization and minimizing side stream generation. Huge advancements were already made for itaconic acid production and this path is expected to be followed in future for other biobased organic acids. The high-value applications of biodegradable polymers from platform chemicals was the driving force for innovations in fermentations and development of strains for lactic acid and polylactides. A similar trend could be expected in future for others platform chemicals, in particular for biobased production of succinic acid. In particular the knowledge gathered on the mechanisms of microbial response to acid stress can be applied to the development of more robust acid tolerant industrial strains either through engineering at the genome-scale level to improve the acid stress tolerance or through metabolic engineering by overexpressing acid-resistance elements detected by systems biology approaches (Guan et al. 2016 , Deparis et al. 2017 ). In recognition of the need for wider application and exploitation of microbial products as probiotics, synbiotics, and so on, a new category of live biotherapeutic products was recently introduced in European and earlier in US legislation (Cordaillat-Simmons et al. 2020 ). This will hopefully pave the way to innovations and applications for next-generation probiotics and help exploit the potential of microorganism for the benefit of all. As showed in this review, low pH is a key parameter to best exploit the beneficial effect of these micro-organisms. As we have explained in this review, microbes are challenged by acidic conditions during bioprocesses and these conditions hinder product yields in many bioreactors and in open fermentations. Thus, identifying or improving micro-organisms that can tolerate acidic conditions, coculturing different species and strains, and/or isolating and characterizing acid-tolerant enzymes for revalorizing specific waste material will surely have a positive impact to tackle the current limitation of product development under acidic conditions (Awasthi et al. 2018 , Li et al. 2018 , Ijoma et al. 2021 ). Furthermore, the production of specific bioactive compounds on food wastes may be anticipated through artificial neural network modeling (Sabater et al. 2020 ). As for biogas production, the microalgal cultivation on DF effluents is a solution intensively studied in recent years (Lacroux et al. 2023 ). In general, the role of artificial intelligence can indeed be of help for such complex contexts: a machine learning approach, including artificial neural networks to predict biogas production in a biogas plant, was recently employed (Frankowski et al. 2020 , Hosseinzadeh-Bandbafha et al. 2022 ) and the use of nanotechnological solutions to improve biohydrogen production was also proposed (Bosu and Rajamohan 2022 , Cao et al. 2022 , Vadalà et al. 2023 ). As a large community of scientiists working in the areas of research discussed in this review, we believe that interdisciplinary research will surely make possible to develop stronger links between areas of research where scientists communicate less; this is particularly important in medicine, which typically is less connected with the others. Nowadays, the paradigm micro-organism = pathogen has been revolutionized and microbes are now regarded as important (if not fundamental) allies to promote our health as well as that of our planet. Literature, mostly on fundamental knowledge, and network expertise can also be accessed via a dedicated website ( https://euromicroph.eu/ ).",
"introduction": "Introduction The extractive and polluting nature of the linear economy (take–make–consume–waste) has by far passed the limits of environmental sustainability (Despoudi et al. 2021 ). In the last two centuries, especially since the second industrial revolution, the anthropocentric perspective has prevailed over that of the planet and the environments in which we live (Baporikar 2020 ). Though Nature is resilient and has an incredible ability for self-renewal, the rate at which humankind pollute and the kind of waste generated has now reached a point of no return, i.e. by far exceeding that of Earth’s self-regeneration (Folke et al. 2021 ). A circular bioeconomy model (i.e. to stop waste accumulation and aiming at reduce–reuse–recycle) would be more sustainable, and the development of such an economy is now a stated target of governments and companies worldwide (Neves and Marques 2022 ). The circular bioeconomy model incorporates two important notions: generation of renewable energy and production of chemicals that are less-toxic and, most of all, recyclable (Tan and Lamers 2021 ). In a circular bioeconomy a fundamental role can be played by micro-organisms (archea, bacteria, and fungi), which are capable of colonizing the most disparate environments and niches on our planet and possess a very broad range of metabolic activities (Sauer 2022 ). Exploiting waste material is therefore a fundamental component of the circular bioeconomy and its main aim is to generate high-value products and bioenergy from waste streams (Priya et al. 2023 ). For its practical realization to large scale waste material refining, a considerable effort of interdisciplinary teams is needed. This also applies to bioremediation and bioaugmentation when it comes to polluted sites. As we will discuss in this review, micro-organisms have the potential to be extremely valuable in regard to the above because of their very broad range of different metabolic activities, many of which have not yet been exploited (O’Connor 2021 ). Synthetic biology is paving the way to microbial cell factories that will meet human needs in a greener way than current processes do (Sauer 2022 ). Key physical–chemical parameters that need to be understood and, when needed, manipulated for the full exploitation of the microbial metabolism include the presence/absence of molecular oxygen, the pH, the salinity, the osmotic pressure, and the temperature (Breznak and Costilow 2014 ). This is true regardless of whether single species and microbial community are being considered. In this review, we highlight the role and the importance of acidic pH (low pH) in many areas of applied sciences that can contribute to the circular bioeconomy. Acidic pH greatly impacts foods shelf life and safety because it reduces spoilage and inhibits pathogens growth (Lund et al. 2020 ), Acidity can be imposed by the addition of acidic molecules (for the most part organic) during food processing or generated by the natural metabolic activities of beneficial micro-organisms that are present in food. As we will discuss in the following section, the substances produced by microbial processes at acidic pH, mostly driven by fermentation, play a vital role not only in food production, preservation, and shelf life, but also in increasing the final nutritional value, functional properties (i.e. benefits beyond basic nutrition) and sensory quality of the final food products. Fermented foods are “foods made through desired microbial growth and enzymatic conversions of food components” (Marco et al. 2021 ), most of which are intrinsically acidic. Fermented acid foods, including many traditional food and drinks (e.g. yogurt, cheese, sour krauts, pickled vegetables, kefir, and different types of fermented milks), are the result of the biotransformations performed by micro-organisms and provide additional health benefits for human and animal health. However, the role and key importance of microbial activities at low pH go beyond food safety, and plant, animal, and human health and disease. The acidification of soil and oceans is for example a key parameter to monitor and ideally manage, because it shapes the microbial communities living in these environments and negatively impacts on the microbial biodiversity (Peixoto et al. 2022 ), with inevitable adverse consequences on food chains. Even in clouds acidic pH is a key parameter that, in combination with sunlight, may influence the survival of bacteria and affect their metabolism and ability to degrade organic acids in clouds (Liu et al. 2023 ). On the other hand, weak organic acids, such as itaconic acid, lactic acid, and succinic acid, represent important building blocks with the potential for microbial production under low pH, as it will be discussed in one of the following sections. Itaconic acid, for example, is a platform chemical the microbial production of which can be improved by strain development and process optimization at low pH. Lactic acid, the most commonly used term for 2-hydroxypropionic acid, is mostly produced today by fermentation: its demand has increased significantly due to its utilization as a monomer for production of poly-lactides and poly-coglycolates. These polymers are thermostable, biocompatible, and biodegradable and also suitable for biomedical applications and food packaging with significant advantages over petroleum-based polymers for the mentioned applications (Djukić-Vuković et al. 2019 , Magalhães Júnior et al. 2021 ). Bio-based production of succinic acid as a building block has the potential to replace monomers obtained from fossil oil in the production, for example, of polybutylene succinate, a biodegradable polymer of the polyesters family, suitable for the production of disposable items (Mancini et al. 2020 ). Routes for microbial production of succinic acid are still not sufficiently developed to make it competitive with the currently dominant petroleum-based production, however, initiatives are active in the European market ( https://www.european-bioplastics.org/ ). As the above examples show, understanding and ultimately enhancing the activity at low pH of neutralophilic micro-organisms and acidophilic micro-organisms, through appropriate biotechnological applications and strategies can be channeled into the needs of the circular bioeconomy. This review aims to provide an updated account of where we are in many applied science fields that exploit microbial responses to low pH to enhance both our and planet health."
} | 3,687 |
26610024 | PMC5152751 | pmc | 8,099 | {
"abstract": "Nitrification, the oxidation of ammonia via nitrite to nitrate, has\nalways been considered as a two-step process catalyzed by chemolithoautotrophic\nmicroorganisms oxidizing either ammonia or nitrite. No known nitrifier carries\nout both steps, although complete nitrification should be energetically\nadvantageous. This functional separation has puzzled microbiologists for a\ncentury. Here we report on the discovery and cultivation of a completely\nnitrifying bacterium from the genus Nitrospira , a globally\ndistributed group of nitrite oxidizers. The genome of this chemolithoautotrophic\norganism encodes both the pathways for ammonia and nitrite oxidation, which are\nconcomitantly expressed during growth by ammonia oxidation to nitrate. Genes\naffiliated with the phylogenetically distinct ammonia monooxygenase and\nhydroxylamine dehydrogenase genes of Nitrospira are present in\nmany environments and were retrieved on Nitrospira -contigs in\nnew metagenomes from engineered systems. These findings fundamentally change our\npicture of nitrification and point to completely nitrifying\n Nitrospira as key components of nitrogen-cycling microbial\ncommunities.",
"introduction": "Introduction Nitrification is catalyzed by ammonia-oxidizing bacteria (AOB) 1 or archaea (AOA) 2 and nitrite-oxidizing bacteria (NOB) 1 . Since the pioneering studies by Sergei Winogradsky more than a century ago 3 , nitrifying microorganisms are generally perceived as specialized chemolithoautotrophs that obtain energy for growth by oxidizing either ammonia or nitrite. The known ammonia-oxidizing microbes (AOM) and NOB are phylogenetically not closely related, and none of these organisms can oxidize both substrates. This separation of the two nitrification steps in different organisms leads to a tight cross-feeding interaction and the frequently observed co-aggregation of AOM with NOB in nitrifying consortia 4 . However, the functional separation is a puzzling phenomenon since complete nitrification would yield more energy (ΔG°'=-349 kJ mol -1 NH 3 ) than either single step (ΔG°'=-275 kJ mol -1 NH 3 for ammonia oxidation to nitrite and ΔG°'=-74 kJ mol -1 NO 2 - for nitrite oxidation to nitrate). Thus, an organism catalyzing complete nitrification should have growth advantages over the “incomplete” AOM and NOB. Based on kinetic theory of optimal pathway length 5 , 6 , Costa et al . 7 argued that a hypothetical complete nitrifier would likely be outcompeted by incomplete, cross-feeding AOM and NOB in many environments. However, the same authors 7 also pointed out that a complete nitrifier might be competitive under conditions that favour the maximization of growth yield rather than growth rate and coined the term “comammox” ( com plete amm onia ox idizer) to describe such a hypothetical microbe. Conditions selecting for comammox may be characterized by slow, substrate influx-limited growth with a spatial clustering of biomass in microbial aggregates and biofilms 7 . A prerequisite for the existence of comammox would also be that any biochemical incompatibilities of ammonia and nitrite oxidation can be overcome by adaptations of enzymes or cellular compartmentalization 7 . Aside from these theoretical considerations, the old question of whether comammox exists in nature has not been resolved. The globally distributed genus Nitrospira represents the most diverse known group of NOB. Nitrospira members have been found in terrestrial 8 and limnic habitats 9 , 10 , marine waters 11 , deep sea sediments, sponge tissue 12 , geothermal springs 13 , drinking water distribution systems 14 , corroded iron pipes 15 , and wastewater treatment plants (WWTPs) 10 , 16 . At least six phylogenetic sublineages of Nitrospira exist, of which lineage II appears to be most widely distributed in both natural and engineered ecosystems 10 . The ecological success of Nitrospira has been linked to an economical pathway for nitrite oxidation 17 and a substantial metabolic versatility, which includes the utilization of various organic compounds in addition to nitrite and CO 2 10 , 11 , 17 – 19 , cyanate or urea degradation and nitrification by reciprocal feeding with AOM 19 , 20 , and chemolithoautotrophic aerobic hydrogen oxidation 21 .",
"discussion": "Discussion The first cultured comammox organism Ca . N. inopinata is a moderately thermophilic Nitrospira member, and uncultured mesophilic comammox Nitrospira were identified by metagenomics in this study, too. The genus Nitrospira is one of the most diverse 8 , 18 known nitrifier groups and colonizes virtually all oxic ecosystems 10 including high-temperature environments 13 , 15 . It is tempting to speculate that the environmental distribution of comammox is largely congruent with that of Nitrospira , which are mostly uncultured and poorly characterized. Previous research was based on the dogma that all Nitrospira use nitrite, but not ammonia, as energy source. Due to this firm expectation, comammox Nitrospira were overlooked for decades and some repeatedly observed phenomena could not be well explained. For example, conspicuously high in situ abundances of uncultured Nitrospira , which exceeded the abundances of known AOM in the same samples, were detected in nitrifying biofilms, activated sludge, freshwater sediments, and drinking water distribution systems 14 , 18 , 43 – 45 . These puzzling observations are inconsistent with the classical concept of nitrification, which suggests a AOM:NOB ratio greater than one 46 . Aside from other energy-conserving metabolic activities of NOB in addition to nitrite oxidation 10 , 21 , 46 , the presence of comammox organisms in those Nitrospira communities would be a plausible explanation for the increased ratio of Nitrospira over known AOM. Indeed, we detected amo and hao genes in the Nitrospira metagenome from WWTP VetMed ( Figure 1 , Extended Data Figures 8 and 9 ), a system in which Nitrospira outnumber AOB according to FISH and comammox represents 43 to 71% of the Nitrospira population as estimated from gene abundances in the metagenomic datasets. A high relative abundance of comammox (58 to 74% of all Nitrospira ) was also estimated for the GWW based on metagenome analysis. More precise analyses of comammox abundance as well as its spatial interactions with other community members will require the development of assays to rapidly differentiate in situ between strictly nitrite-oxidizing and comammox Nitrospira . Studies with strictly nitrite-oxidizing representatives of this genus characterized Nitrospira as slow-growing microbial K-strategists adapted to low substrate concentrations 18 , 43 , 47 , 48 . Many Nitrospira , including Ca . N. inopinata, also form microcolonies, flocs, and biofilms 10 , 43 . These properties, if generally shared by comammox Nitrospira , would be in agreement with the theoretically predicted 7 ecological niche of comammox. The engineered systems surveyed in this study are characterized by biofilm or floc formation. Diffusion barriers and ammonium or nitrite concentration gradients 47 in biofilms could create niches with limited substrate influx, where comammox might outcompete incomplete nitrifiers. Complex biofilm or floc architectures with numerous microenvironments may support diverse nitrifier communities like in WWTP VetMed, which consist of comammox as well as canonical AOB and NOB. Future comammox isolates from the Ca . N. inopinata culture and from other enrichments may offer chances to experimentally define the conditions that select for these organisms and to study the competition of comammox with other nitrifiers, including strictly nitrite-oxidizing Nitrospira and AOA adapted to low substrate concentrations 48 , 49 . The discovery of comammox has revealed that the division of metabolic labour in nitrification is not obligate and will thus have far-reaching implications for future studies on the microbiology of nitrogen cycling. It opens a new field in nitrification research and some of the most pressing open questions range from the biochemistry, regulation, inhibition, and kinetics of complete nitrification to the diversity, population dynamics, metabolic versatility, and biological interactions of comammox organisms. In particular, the integration of comammox in studies on the niche specialization and niche partitioning of AOB and AOA 50 or NOB 43 will be crucial to obtain a picture of nitrification as it actually occurs in nature. Such insights may lead to refined strategies to manage nitrification in sewage treatment, drinking water supply, and agriculture. The presence of new AMO and HAO types, which share common ancestry with these enzymes of betaproteobacterial AOB, in the phylogenetically deep-branching genus Nitrospira 15 impressively exemplifies the modular evolution of the nitrogen cycle 28 and adds further complexity to the intricate evolutionary history of nitrification 17 , 28 ."
} | 2,239 |
26483827 | PMC4591488 | pmc | 8,100 | {
"abstract": "In a field experiment conducted in a Mediterranean area of inner Sicily, durum wheat was inoculated with plant growth-promoting rhizobacteria (PGPR), with arbuscular mycorrhizal fungi (AMF), or with both to evaluate their effects on nutrient uptake, plant growth, and the expression of key transporter genes involved in nitrogen (N) and phosphorus (P) uptake. These biotic associations were studied under either low N availability (unfertilized plots) and supplying the soil with an easily mineralizable organic fertilizer. Regardless of N fertilization, at the tillering stage, inoculation with AMF alone or in combination with PGPR increased the aboveground biomass yield compared to the uninoculated control. Inoculation with PGPR enhanced the aboveground biomass yield compared to the control, but only when N fertilizer was added. At the heading stage, inoculation with all microorganisms increased the aboveground biomass and N. Inoculation with PGPR and AMF+PGPR resulted in significantly higher aboveground P compared to the control and inoculation with AMF only when organic N was applied. The role of microbe inoculation in N uptake was elucidated by the expression of nitrate transporter genes. NRT1.1, NRT2 , and NAR2.2 were significantly upregulated by inoculation with AMF and AMF+PGPR in the absence of organic N. A significant down-regulation of the same genes was observed when organic N was added. The ammonium (NH 4 + ) transporter genes AMT1.2 showed an expression pattern similar to that of the NO 3 - transporters. Finally, in the absence of organic N, the transcript abundance of P transporters Pht1 and PT2-1 was increased by inoculation with AMF+PGPR, and inoculation with AMF upregulated Pht2 compared to the uninoculated control. These results indicate the soil inoculation with AMF and PGPR (alone or in combination) as a valuable option for farmers to improve yield, nutrient uptake, and the sustainability of the agro-ecosystem.",
"conclusion": "Conclusion In conclusion, the results of the present study showed that soil inoculation with AMF increased plant growth and N uptake of durum wheat compared to the uninoculated control irrespective of fertilization. CDA suggested that the effects of the inoculation with AMF on the expression of P and N transporters in the plant root were evident only in unfertilized condition. Soil inoculation with PGPR benefitted plant growth and nutrient uptake only when organic fertilizer was added. Agronomic benefits from the soil inoculation with beneficial microbes could depend on the availability of nutrient for the microbe: AMF, which receive photosynthates only from the host plant, in our experiment benefitted the crop under both fertilized and unfertilized conditions, whereas PGPR, which can also take C from the soil, benefitted the crop only in plots where the organic fertilizer was added. These results indicate soil inoculation with AMF and PGPR (alone or in combination) is a valuable option for farmers to improve nutrient uptake and the sustainability of the agro-ecosystem. Further studies are needed to evaluate the benefit of the soil inoculation with efficient consortia of both AMF and PGPR at varying the doses and characteristics of the fertilizers applied.",
"introduction": "Introduction Plants live in the soil engaging a wide range of interaction with soil microorganisms. Such interaction can include a benefit, a disadvantage or a null effect on plant growth and nutrient uptake and such an effect also depends on soil conditions, especially nutrient availability for the plant and the microorganisms. Arbuscular mycorrhizal fungi (AMF) and plant growth-promoting rhizobacteria (PGPR) are important components of the soil microbiota and usually have major effects on plant growth under stressing conditions thanks to their ability to influence many pivotal physiological processes of both the plant, such as seed germination rate, root growth and branching, photosynthetic rates, etc., and soil, e.g., aggregate stability, pH, activity of pathogens, and so on ( Berg , 2009 ; Venkateshwaran et al., 2013 ). In addition, AMF can also provide alternative nutrient uptake pathways ( Finlay, 2004 ), which are particularly important for plant growth when nutrient availability is low. For example, the mobility of phosphate (Pi) is low, especially in alkaline soils, and its uptake rapidly leads to the development of depletion zones around the roots, which further limits P uptake ( Schachtman et al., 1998 ). Pi acquisition in plants is ensured by members of plasma membrane Pi transporter family 1 ( Pht1 ; Kobae et al., 2010 ), which are also involved in Pi translocation among plant cells and tissues as well as Pi remobilization from senescent to novel onset organs ( Lambers et al., 2008 ). Homologous Pht1 genes have been characterized in many plant species, including Arabidopsis thaliana ( Misson et al., 2004 ), tomato ( Daram et al., 1998 ), maize ( Nagy et al., 2006 ), and wheat ( Liu et al., 2013 ). Numerous Pht1 members act under high-affinity systems and thus play critical roles in plant Pi uptake under Pi deprivation ( Bucher, 2007 ). The effects of AMF on the enhancement of P uptake are well known and involve different genes encoding Pht1 transporters ( Javot et al., 2007 ). More recently, the differential expression of two Pi transporter genes ( Pht1;3 and Pht1;6 ) in maize root colonized by different AMF was also highlighted ( Tian et al., 2013 ). Unlike Pi, NO 3 - , the dominant N form in most agricultural soils, is highly mobile, and its uptake proceeds by at least two transport systems—a low-affinity transport system (LATS; active at NO 3 - concentration >0.2 mm) and a high-affinity transport system (HATS; operating within 0–0.2 mm)—that allow plants to maximize NO 3 - acquisition under low NO 3 - -N availability. HATS is particularly important for plant nutrition when limited or no N fertilizer is applied ( Malagoli et al., 2004 ). In bread wheat ( Triticum aestivum ), an NRT2.1 , an important HATS family, has been isolated and characterized, and its transcript abundance decreased in roots in response to NO 3 - and NH 4 + ( Wang et al., 2011 ). Furthermore, an NAR2-like protein actively interacted with NRT2.1 to form a functional HATS effective in NO 3 - transport ( Orsel et al., 2006 ). Arbuscular mycorrhizal fungi root colonization positively affected nitrate uptake and allocation in tomato shoot compared to an uninoculated control, preferentially mediated by a higher expression of NRT2.3 ( Hildebrandt et al., 2002 ), which is also responsible for long-distance N translocation in other species ( Jing et al., 2012 ). This mechanism was confirmed by an increased expression of four different AMF-related nitrate transporter genes in mycorrhizal Medicago truncatula roots ( Hohnjec et al., 2005 ). Unlike NO 3 - , NH 4 + tends to be buffered by interactions with negatively charged soil particles (i.e., by the cation exchange complex). Saturable and non-saturable systems operating at low and high external NH 4 + concentrations, respectively, have been characterized in several plant species ( von Wittgenstein et al., 2014 ). The uptake of ammonium at low concentrations (i.e., under high-affinity conditions) in plant roots is mediated by AMT1-type ammonium transporters (AMTs), whose activity depends on several factors, including the plant species. For example, in Zea mays , such transport is most probably mediated by two rhizodermis-localized transporters (ZmAMT1;1a and ZmAMT1;3; Gu et al., 2013 ). In addition, in mycorrhizal Lotus japonicus roots, an AMT ( LjAMT2;2 ) is implicated in NH 4 + uptake and is upregulated by the AMF partner ( Guether et al., 2009 ). Such as AMF, PGPR can improve the availability of nutrients for plants through different mechanisms, including soil acidification, chelation, exchange reactions, and organic acid biosynthesis ( Lugtenberg and Kamilova, 2009 ). The effects of PGPR on plants depend on the specific interactions between microbe and crop species. The Plant responses to the inoculation of PGPR with varying Zn-mobilizing activity varied among different wheat genotypes ( Abaid-Ullah et al., 2015 ). Microarray studies have been conducted to gain insight into gene and pathway regulatory networks in response to inoculations of PGPR in maize and Arabidopsis ( Fan et al., 2012 ). Proteomic approaches have also been used to elucidate posttranscriptional regulation mechanisms ( Cheng et al., 2009 ). However, little information is available about the regulation mechanisms of plant gene expression mediated by the PGPR–plant interaction. Considering the ability of both PGPR and AMF to help plants take up nutrients, they could be the most important players in shifting from conventional to sustainable land management practices. The aim of the present work was to study the N and P uptake of durum wheat grown in soil inoculated with PGPR, AMF, or both and grown under conditions of different nutrient availability. Durum wheat ( cv . Anco Marzio) was grown in the field, and the expression of key genes involved in the uptake of nitrate, ammonium, and Pi was evaluated.",
"discussion": "Discussion Root Mycorrhizal Colonization, Rhizoplane Colonization by Bacteria and Plant Growth Soil inoculation with plant growth promoting microbes, such as PGPR and AMF, is a promising tool of integrated management systems, and many efforts have been made to increase the efficiency of plants’ use of nutrients (from either soil or fertilizers) through microbial technology and the sustainability of the cropping systems. In the present work, the effects of soil inoculation with AMF and PGPR efficient at promoting plant growth were studied in durum wheat grown in an area characterized by poor N availability and soil organic carbon content. We found that inoculation with AMF, PGPR, or both increased rhizoplane colonization by bacteria, which is an important indicators of soil quality ( Schloter et al., 2003 ). And this occurred especially under unfertilized conditions. Root colonization by the natural AM consortium (NAT) was lower than that observed by other authors in the same species ( Gao et al., 2010 ). Soil inoculation with AMF spores markedly increased root AM colonization and rhizoplane colonization by bacteria. Teng et al. (2013) observed that natural AM colonization decreased with increasing P supply to the soil. In our experiment, both available and total soil P content were very high (92 ppm and 1370 ppm, respectively), and this, along with the huge amount of P fertilizer usually applied in the area, may have contributed to the selection of less beneficial AM species ( Ehinger et al., 2009 ). Nonetheless, the increase in root AM colonization after soil inoculation with AMF, as also observed elsewhere ( Al-Karaki et al., 2004 ), suggests that other factors could be detrimental to the colonization process by the NAT, including the effect of soil organic matter content on AMF growth ( Kohler et al., 2015 ) or continuous soil plowing. Indeed, soil inversion plowing disrupts the AM hyphal net, which usually represents the most important source of inoculum, and displaces spores in the deep soil layer, where root growth is delayed in the growing season ( Kabir, 2005 ). In addition, plowing may select for sporulating AM fungal genotypes, which invest more resources in sporulation rather than symbiotic activity ( Jansa et al., 2003 ). Soil inoculation with AMF increased plant growth irrespective of fertilization, and this resulted in a higher aboveground biomass yield and N and P uptake in comparison with uninoculated treatments. These results agree with those obtained in other experiments carried out in both field and controlled (pot) conditions ( Adesemoye et al., 2008 ; Berta et al., 2014 ; Saia et al., 2014a , b ). As observed by Baris et al. (2014) in spring wheat and barley, in our experiment soil inoculation with PGPR increased the aboveground biomass and N and P uptake in comparison with uninoculated treatments, but only when organic fertilizer was applied. Several studies have shown that the advantages of PGPR can be attributed, among other factors, to a more rapid breakdown of organic matter, which enhances the availability of nutrients for plants ( Yildirim et al., 2011 ). The delay in the benefit of PGPR compared to AMF in terms of N uptake may be due to the time required by PGPR for the mineralization processes, the amount and quality of wheat root exudates and root biomass, or the reduced availability of carbon for bacteria ( Hu et al., 2009 ), as the effect of PGPR at tillering was evident only in the organic fertilized treatments. Pi and N Transporters Besides the adaptive strategies adopted by plants to increase P absorption, such as secreting phosphatases, organic acids, and protons ( Dunlop and Gardiner, 1993 ) or enhancing root growth and/or modifying root morphology ( Bates and Lynch, 1996 ), positive correlations between AMF symbiosis formation and shoot biomass, P uptake, and total P content have been reported ( Avio et al., 2006 ). In the present experiment, fertilization reduced all P transporters, although the effects of the inocula varied depending on the fertilization treatment: under uninoculated treatments, inoculation with AMF increased the expression of both Pht2.1 and Pht2 , the latter of which was also increased by PGPR in fertilized treatments. The effects of fertilization on total P uptake, but not those of soil inoculation with both microorganisms, complied with the expression of P transporters: indeed, total P uptake increased after fertilization, which suggests that fertilization resulted in an increase in the available P fraction in soil, and this may have been due to soil acidification by the soil bacteria when mineralizing the organic fertilizer ( Bertrand et al., 2007 ). Because inoculation with PGPR increased plant growth and total P uptake in fertilized treatments, we should have observed a reduction in the expression of P transporters compared to uninoculated treatments (NAT). Nonetheless, P transporters of wheat in plots inoculated with PGPR were higher than NAT. This implies that PGPR can stimulate P uptake through a direct effect on plant metabolism ( Richardson et al., 2009 ). The role and importance of AM and/or PGPR in plant N nutrition is uncertain, and it is not clear under which conditions AM is beneficial for N uptake. Consistent with their specific function, many members of the NRT1 and NRT2 families are involved in the uptake of nitrates from the soil into the root and their translocation to the shoots ( Fan et al., 2009 ). In particular, the dual-affinity NRT1.1 transporter is triggered by a wide range of soil nitrate concentrations, and its switching from LATS to HATS functionality is determined by a phosphorylation at Thr101 ( Ho et al., 2009 ). Here, NRT1.1 transcript abundance was influenced by both inoculation with AMF and fertilization, confirming its dual-affinity function. In contrast, the NRT2.1 member of the NRT2 family encodes a HATS of nitrate uptake ( Huang et al., 1999 ). The expression of NRT2 from Triticum aestivum with high homology with AtNRT2.1 under unfertilized conditions was significantly induced, in T. durum , by inoculation with AMF+PGPR compared to the uninoculated control. A less significant increase in NRT2 expression was also induced by inoculation with AMF. As expected, a downregulation in NRT2 was observed when N80 organic fertilizer was supplied. The upregulation of both NRT1.1 and NRT2 by inoculation with AMF and AMF+PGPR is consistent with the increased aboveground N compared to NAT. These results suggest that in unfertilized plots, the increased N accumulation in the AMF-inoculated plant biomass is mediated by the upregulation by AMF of nitrate transporter genes. In terms of the classification of nitrate transporters as constitutive, repressible, and inducible ( Wang et al., 2003 ), our results show that both NRT1.1 and NRT2 seem to be nitrate-repressible genes, although NRT2 was more downregulated than NRT1.1 under fertilized conditions, according to its nitrate dual affinity ( Ho et al., 2009 ). Moreover, NRT2.1 may interact with an NAR2-type protein for a functional HATS based on the essential role of NAR2.1 in Arabidopsis ( Orsel et al., 2006 ). Under unfertilized conditions, NAR2.2 was significantly induced by inoculation with AMF and AMF+PGPR compared to the uninoculated control. Thus, like NRT2 , its HATS partner NAR2.2 was highly inhibited by organic N fertilization. Given NRT2/NAR2.1 expression and the relative protein interaction, first reported in Arabidopsis ( Orsel et al., 2006 ), here we have shown an AMF can have a role in mediating the expression of NRT2/NAR2.1 in durum wheat. In particular, the two genes seemed to be upregulated by inoculation with AMF and AMF+PGPR, and this was probably mediated by a reduced availability of ammonium in AMF and AMF+PGPR than NAT ( Saia et al., 2015 ). In particular, the presence of AMF highly upregulated NAR2.2. In contrast, NRT2/NAR2.2 was strongly downregulated by N fertilization per HATS functionality but probably also through the increase in the availability of NH 4 + in fertilized soils. Such as observed in nitrate transporters, we also found that in unfertilized conditions, the expression of the HATS AMT1.2 was significantly increased when wheat was inoculated with AMF+PGPR compared to NAT; a positive, though not significant, effect was also observed with inoculation with AMF. These results do not completely agree with the AMT2 gene family low-affinity function, but previous findings showed that the regulation of both AMT family genes is controlled by a complex network of different N forms and concentrations ( Glass et al., 2002 )."
} | 4,471 |
31943579 | PMC7187462 | pmc | 8,105 | {
"abstract": "Abstract LuxR‐type transcriptional activator proteins frequently regulate the expression of biosynthetic gene clusters (BGCs). With only a fraction of bacterial BGCs being expressed under standard culturing conditions, modulation of LuxRs would provide a powerful approach to activate silent clusters. We show that by exploiting the modular nature of LuxR proteins, it is possible to construct functional chimeric LuxRs, which enables both the rewiring of quorum sensing systems and the activation of silent BGCs. Importantly, our strategy allowed us to identify the novel natural product pseudomonol from a bacterium of the genus Pseudomonas ."
} | 161 |
37273610 | PMC10233695 | pmc | 8,106 | {
"abstract": "Lignocellulosic agricultural waste is an abundant renewable\nfeedstock\nthat can be utilized as a sustainable source of biomass-based plastics.\nIdeally, it is used without discarding any components, including cellulose,\nhemicellulose, and lignin. However, their utilization as lignocellulose-based\nplastics has been limited because of the low compatibility between\nthe polysaccharides and lignin derivatives and the resulting poor\nmechanical properties of the final products. Here, we demonstrate\na facile but highly controllable conversion of sugarcane bagasse into\nvaluable thermoplastics by utilizing the excellent solubility and\nunique organocatalytic abilities of an ionic liquid, 1-ethyl-3-methylimidazolium\nacetate. In a homogeneous and one-pot chemical modification reaction\nsystem, the substitution ratio of an aromatic benzoyl group to an\naliphatic hexanoyl group in the bagasse derivative was adjusted by\nthe ratio of acyl reagents used. Moreover, the allocation of these\ntwo acyl groups to polysaccharide and lignin components in bagasse\nwas successfully controlled only by exchanging the order of the acyl\nreagents introduced into the reaction system. The controlled introduction\nof the acyl groups into bagasse achieved a homogeneous polymer phase\nin the resultant multicomponent hot-pressed film, resulting in enhanced\nmechanical properties such as sufficient tensile strength (∼20\nMPa) and excellent ductility with a high strain energy density (∼5\nMJ m –3 ).",
"conclusion": "4 Conclusions To improve the compatibility\nof polysaccharides (cellulose and\nhemicellulose) and lignin, bagasse was successively modified with\naromatic and aliphatic acyl groups in the desired ratio and allocation.\nThe combination of the acylsubstituents was optimized as benzoyl (Bz)\nand hexanoyl (He) groups through our systematic investigation (see\nthe Supporting Information ). Consequently,\nthe undesired phase separation in the internal structure of the only\naliphatic-acylated bagasse film was successfully prevented owing to\nthe enhanced π-electron interactions between the partially benzoylated\npolysaccharide and lignin derivatives in Bag-HeBz. However, excessive\nbenzoylation of the lignin led to the brittleness of Bag-HeBz. Thus,\nthe polysaccharides in bagasse were preferentially benzoylated, while\nlignin benzoylation was moderately suppressed by exploiting the unique\ncatalytic ability of EmimOAc, followed by hexanoylation of the residual\nOH groups in one-pot. By controlling the allocation and DS ratio of\nthe Bz/He groups, the acylated bagasse films exhibited the improved\ntensile strength (∼20 MPa) and/or excellent ductility, as indicated\nby their high strain energy density (∼5 MJ m –3 ). It should be noted that this is the first one-pot reaction system\nfor lignocellulose that can control the DS of the two acyl groups\nand their allocation to each polymeric component. This progress, including\nthe elucidation of the effects of aromatic/aliphatic-mixed acyl groups\non the material properties of acylated bagasse, provides a valuable\nsynthetic methodology, enabling more advanced material designs for\nlignocellulose-based thermoplastics.",
"introduction": "1 Introduction Lignocellulosic biomass\nis composed of polysaccharides (cellulose\nand hemicellulose) and an aromatic polymer (lignin). It has been expected\nas an abundant renewable feedstock for the production of goods and\ncommodities for our society toward switching off the current fossil-depended\nindustry. Among many lignocellulose species, agricultural waste such\nas sugarcane bagasse can be obtained at low cost in large quantities\nfrom the sugar and alcohol industries, 1 and has been strongly demanded for its high-value added utilization.\nHowever, there are still challenges and technical limitations that\nmust be overcome, particularly on an efficient and sustainable conversion\nof its major components. Moreover, the technology development for\nvalorization of lignocellulosic waste must follow green chemistry\npractices toward eco-friendly processes; otherwise, no environmental\nleverage over traditional petrochemical technologies will be acquired. 2 In this context, ionic liquids (ILs) are\npromising media for lignocellulose\nprocessing owing to their excellent solubility 2 − 6 and organocatalytic abilities for various chemical\nmodification reactions. 7 − 9 Recently, our group has demonstrated direct conversion\nof bagasse into lignocellulose-based thermoplastics via homogeneous\ntransesterification using an IL, 1-ethyl-3-methylimidazolium acetate\n(EmimOAc), as both a solvent and catalyst. 10 , 11 Two kinds of vinyl esters were successively added to the homogeneous\nreaction system, and all the hydroxy (OH) groups in bagasse were substituted\nwith long/short chain-mixed aliphatic acyl groups in the desired ratios.\nIn particular, decanoylated and per-acetylated bagasse exhibited excellent\nthermal moldability; there was a sufficient gap between the temperatures\nof thermal decomposition and melt flow, and it was readily applied\nto hot pressing and injection molding. However, this aliphatic-acylated\nbagasse was fragile owing to its poor ductility, which has remained\nan issue in the material design. 11 The bagasse derivative is a composite material in which polysaccharide\nand lignin derivatives are naturally blended. Thus, the brittleness\nof the aliphatic-acylated bagasse might be attributed to the poor\ncompatibility between its constituents, 12 as implied by the “sea-island” internal structure\nformed in the hot-pressed film ( Figure S1 ). Introducing an aromatic group into the polysaccharide-OH groups\ncan improve the compatibility with lignin, 13 , 14 which was preliminary verified by our investigation of decanoylated\nand per-benzoylated bagasse ( Figure S2 ).\nHowever, the homogeneous reaction of bagasse concurrently involved\nthe modification of lignin-OH groups with the aromatic substituent,\nwhich caused embrittlement of the product ( Figure S3 ), perhaps owing to the excessively enhanced π–π\ninteractions between the lignin derivatives. 15 − 17 Thus, we propose\na new synthetic strategy for the homogeneous reaction of bagasse,\noffering preferential modification of polysaccharides with an aromatic\nacyl group while minimizing the substitution of lignin. EmimOAc\nhas a unique catalytic ability in transesterification of\nlignin-OH groups with vinyl esters as acyl donors. In presice, it\ncan catalyze acylation of both aliphatic OH (R-OH) and aromatic OH\n(Ar-OH) groups and also catalyze selective deacylation of the aromatic\nmoiety. 18 In this dual catalytic system,\nselective acylation of the R-OH group in lignin while leaving the\nAr-OH group intact was achieved by a one-pot process 19 , 20 without any requirement for conventional multistep protection and\ndeprotection processes. 21 Applying this\nsynthetic strategy to the homogeneous reaction of bagasse, it is predicted\nthat an aromatic acyl group, derived from an initially added vinyl\nester, will preferentially substitute the R-OH groups of polysaccharides\nand lignin. The residual OH groups, including the Ar-OH group of lignin,\ncan be per-acylated with another vinyl ester that is subsequently\nadded to the reaction system. Consequently, these successive reactions\nin one-pot can control the molar ratio of the two acyl substituents\nand their allocation to the polysaccharides and lignin in bagasse. This study demonstrated the direct chemical modification of bagasse\nwith the desired ratio and allocation of aromatic/aliphatic-mixed\nacyl groups, producing a lignocellulose-based thermoplastic with improved\ncompatibility among its polymeric components and enhanced mechanical\nproperties. First, the reactivities of the R-OH and Ar-OH groups in\nEmimOAc-catalyzed transesterification with aromatic/aliphatic-type\nvinyl esters were elucidated using a model reaction system. Then,\nthe allocation of the aromatic/aliphatic-mixed acyl groups to each\nlignocellulose component was controlled in a one-pot homogeneous transesterification\nof bagasse using EmimOAc. Furthermore, the effects of the molar ratio\nand distribution of the two acyl groups on the material properties\nof the products were investigated.",
"discussion": "3 Results and Discussion 3.1 Synthetic Strategy of Aromatic/Aliphatic-Mixed\nAcylated Bagasse The washed and dried bagasse consisted of\n66.4 wt % of polysaccharides and 27.9 wt % of lignin ( Scheme 1 A). 24 The polysaccharides in bagasse consist of cellulose and xylan-based\nhemicellulose, 25 , 26 and their total R-OH content\nincluding primary and secondary alcohols was estimated as 68.2 mmol\nper 6.0 g of bagasse. Meanwhile, the lignin contained approximately\n5.6 mmol of R-OH and 3.4 mmol of Ar-OH groups ( Scheme 1 B), based on our previous report ([R-OH]\n= 3.32 mmol g –1 and [Ar-OH] = 2.02 mmol g –1 ). 18 These compositional results indicate\nthat the bagasse is rich in R-OH groups, mainly derived from the polysaccharides. Scheme 1 Schematic Representation of the Synthetic Strategy in This Study (A) Composition of\nwashed and\ndried bagasse; (B) the estimated R-OH and Ar-OH contents of cellulose,\nhemicellulose, and lignin in 6.0 g of bagasse, based on the hypothesis\nthat the hemicellulose was only composed of xylan; 11 (C) two types of procedures with different orders of addition\nof vinyl esters in the EmimOAc-catalyzed one-pot, two-step transesterification\nreactions (process I and process II); and (D) expected reaction mechanism\nin process II for the preferential benzoylation of R-OH groups of\npolysaccharides in bagasse. In our previous\nstudies, 10 , 11 the DS of two acyl\ngroups in the bagasse derivative was controlled by a one-pot, two-step\nhomogeneous reaction system using EmimOAc, where the two acyl reagents\nwere successively fed. In presice, the DS of the two acyl groups depended\non the amount of the first acyl reagent added, and the residual OH\ngroups were subsequently per-acylated with a second acyl reagent.\nIn this study, it was assumed that by changing the order of addition\nof the two acyl reagents, allocation of the substituents to polysaccharides\nand lignin in bagasse could be controlled. When an aromatic\nacyl donor (i.e., VBz) is added in the first step,\nas shown in process I ( Scheme 1 C), EmimOAc catalyzes the acylation of both R-OH and Ar-OH\ngroups. Subsequently, it also catalyzes selective transesterification\nof the resultant Ar-OH-substituted benzoyl (Bz) groups with the available\nproton donors remained in the reaction system. 18 − 20 Therefore,\nthe Ar-OH group in lignin can be regenerated via intra- and inter-molecular\ntransfer of the Bz group to the residual R-OH groups ( Scheme 1 D). As a result, the abundant\nR-OH groups in the polysaccharides should be preferentially benzoylated\nin the first step. Subsequently, the residual R-OH groups in the resultant\nBz-rich polysaccharide derivative and lignin containing the free Ar-OH\ngroups can be per-acylated by the addition of another aliphatic acyl\ndonor (i.e., VHe), resulting in the hexanoyl (He)-rich lignin derivative.\nIn contrast, by changing the order of addition of these vinyl esters,\nas shown in process II ( Scheme 1 C), He-rich polysaccharide\nand Bz-rich lignin derivatives can be obtained. In the above\nsynthetic strategy, He group was selected as the\naliphatic acyl group in combination with Bz group because the benzoylated\nand per-hexanoyl bagasse showed superior tensile strength to that\nof benzoylated and per-decanoylated bagasse in our preliminary study\n( Figure S4 ). Although benzoylated and per-acetylated\nbagasse was also prepared, the tensile testing was not performed because\nit could not be thermally molded ( Figure S5 and Table S2 ). 3.2 Verification of Preferential Acylation of\nR–OH by Model Experiments The strategy described in Section 3.1 was verified\nby in situ 1 H NMR analysis of transesterification reactions\nusing a molar equivalent mixture of phenol and 2-PA as the model substrates\nfor Ar-OH and R-OH groups, respectively. As shown in Figure 1 , approximately 60 and 40%\nof phenol were initially acylated by VHe and VBz, respectively, but\nalmost all the generated phenyl esters were deacylated within 10 h.\nMeanwhile, 2-PA was gradually acylated, and the conversion reached\nalmost 100% in both cases using VHe and VBz. Since the molarity of\nVHe and VBz added into each reaction system was equivalent to that\nof either phenol or 2-PA, it was stoichiometrically demonstrated that\nthe intermolecular transfer of the acyl groups to 2-PA via phenol\noccurred under the EmimOAc catalysis. These results indicate that\nthe transesterification reactions of (1) vinyl ester and phenol (or\n2-PA) and (2) the resultant phenyl ester and 2-PA successively occurred,\nregardless of the types of vinyl esters used. More importantly, the\ngenerated 2-phenylethyl ester is resistant to the EmimOAc-catalyzed\ndeacylation, 18 − 20 and thus, the acyl groups are only transferred from\nthe Ar-OH to R-OH groups. Figure 1 In situ 1 H NMR analysis for successive\ntransesterification\nreactions of the mixture of phenol (0.64 mmol) and 2-phenylethyl alcohol\n(2-PA, 0.64 mmol) with a molar equivalent of (a) VHe or (b) VBz (each\n0.64 mmol) catalyzed by a molar equivalent of EmimOAc (0.64 mmol)\nin 1.5 mL of DMSO- d 6 at 80 °C for\n10 h. To enable real-time monitoring of the reactions\nby 1 H NMR, the concentrations of the substrates and EmimOAc\ncatalyst\nin these model experiments were set to be much lower than those applied\nin the bagasse reaction . In particular, for the dissolution of bagasse,\nEmimOAc should be used in excess as the solvent; 27 , 28 thus, the acylation and subsequent acyl transfer from Ar-OH to R-OH\ngroups in the bagasse reaction are expected to proceed much faster\nthan in the model reactions ( Figure 1 ). 3.3 Investigation of Controlled Allocation of\nBz/He Groups on Polysaccharides and Lignin First, bagasse\nwas benzoylated with 0.5 equiv/[OH] of VBz and successively per-acylated\nwith excess VHe (3.0 equiv/[OH]) to obtain Bag-BzHe. For comparison,\nBag-HeBz was prepared in the opposite manner with 0.5 equiv/[OH] of\nVHe and excess VBz. The polysaccharide and lignin components of each\nacylated bagasse were further separated as the MeOH-insoluble and\nMeOH-soluble fractions, respectively. Their molar mass distributions\nwere distinct ( Figure 2 ), and no clear difference was observed between the fractions derived\nfrom Bag-BzHe and Bag-HeBz. Figure 2 Molar mass distributions of the bagasse-derived\npolysaccharide\n(PS-) and lignin (Lig-) derivatives substituted with Bz and He groups,\ndetermined by SEC measurements in 0.01 M LiBr/DMF as an eluent using\npolystyrene standards. The molar ratio of the Bz to He groups in each\nderivative was\nestimated by 1 H NMR analysis ( Figure 3 ), and is summarized in Table 1 . In the spectra of the polysaccharide\nderivatives (PS-BzHe and PS-HeBz), there were broad chemical shifts\nderived from protons of the sugar backbone in the range of 3–5.5\nppm 10 , 24 and the distinctive signals of the Bz and\nHe groups at 7.2–8.2 and 0.5–2.3 ppm, respectively.\nConversely, the spectra of the lignin derivatives (Lig-BzHe and Lig-HeBz)\nshowed a variety of signals due to the many aromatic and aliphatic\nprotons in lignin structures, and their assignments, annotated on\nthe spectra ( Figure 3 ), were predicted based on β-O-4-linked artificial lignin measured\nin CDCl 3 . 29 Comparing the spectra\nof the two lignin derivatives, the signal intensity of the Bz group\nof Lig-BzHe was lower than that of Lig-HeBz, while the intensity of\nthe multiple signals derived from the He group of Lig-BzHe was greater\nthan that of Lig-HeBz. In particular, the intensity of a signal at\n2.2–2.4 ppm, attributed to the proton (*) in the He group substituted\non Ar-OH groups, was higher for Lig-BzHe than Lig-HeBz. These results\nsuggest that the benzoylation of the Ar-OH groups in lignin was suppressed\nby the initial addition of VBz to the reaction system, and the degree\nof per-hexanoylation consequently increased. Figure 3 1 H NMR spectra\nof the bagasse-derived polysaccharide\nand lignin derivatives substituted with Bz and He groups, which were\nfractionated from Bag-BzHe and Bag-HeBz. The concentration of the\nproduct in CDCl 3 used for the measurements was consistent\nwith the displayed scale of the obtained spectra. Table 1 Molar Ratios of Bz/He Groups in the\nPolysaccharide and Lignin Derivatives Fractionated from Bag-BzHe and\nBag-HeBz entry origin fraction Bz/He ratio PS-BzHe Bag-BzHe MeOH-insoluble 1.1 Lig-BzHe MeOH-soluble 0.3 PS-HeBz Bag-HeBz MeOH-insoluble 0.9 Lig-HeBz MeOH-soluble 1.9 As shown in Table 1 , the Bz/He ratio of Lig-BzHe was 0.3, whereas that\nof PS-BzHe was\n1.1. In contrast, Lig-HeBz showed a much higher Bz/He ratio (1.9)\nthan Lig-BzHe, suggesting that the acyl group derived from the vinyl\nester added in the second step predominantly reacted at the lignin-OH\ngroups. In contrast, PS-HeBz showed a slightly lower Bz/He ratio of\n0.9 than PS-BzHe, and thus, the allocation of the two acyl groups\non the polysaccharides was found to be hardly affected by the addition\norder of the vinyl esters. This might be owing to the much larger\nR-OH content of the polysaccharides, compared to the total OH content\nof lignin. 3.4 Effects of Allocation and DS Ratio of Bz/He\nGroups on Thermal and Mechanical Properties As discussed\nin Sections 3.2 and 3.3 , the benzoylation of the lignin-OH groups\nin bagasse was moderately suppressed by the initial addition of VBz\ninto the reaction system. Then, several kinds of Bag-BzHe with different\nDS ratios of Bz/He groups were prepared by changing the amount of\nVBz added. The chemical structures of the Bag-BzHe series and Bag-HeBz\nas a reference were confirmed by ATR-mode FT-IR and 1 H\nqNMR ( Figures S6 and S7 ), and the DS of\nthe Bz/He groups and the residual OH content were determined using 31 P qNMR analysis after per-phosphitylation of the acylated\nbagasse ( Figure S8 ). As summarized in Table 2 , all the acylated\nbagasse contained less than 5% unreacted OH groups. The DS of the\nBz group varied from 5 to 48, while that of the He group ranged from\n94 to 51. In each abbreviation for the acylated bagasse, Bag-R1R2(X),\nthe number X in the parentheses corresponds to the DS (mol %) of the\nacyl group of R2, introduced in the second step. Table 2 Thermal Properties of Bagasse Derivatives\nwith Different DS Ratios of Bz/He Groups DS/mol % thermal property/°C entry Bz He OH T d-5% T flow T offset Δ T d - 5% – T flow Bag-HeBz(53) 53 42 5 251 136 173 115 Bag-BzHe(51) 48 51 1 234 122 157 112 Bag-BzHe(74) 22 74 4 250 143 181 107 Bag-BzHe(82) 14 82 4 242 133 179 109 Bag-BzHe(90) 9 90 1 239 126 164 113 Bag-BzHe(94) 5 94 1 234 138 182 96 The effects of the allocation and DS ratio of Bz/He\ngroups on the\nthermal processability of the acylated bagasse were investigated by\nTG and melt-flow measurements ( Figure 4 ). The Bag-BzHe series and Bag-HeBz exhibited similar\nTG curves, and the T d-5% was in\nthe range of 234–251 °C, suggesting that the thermal stability\nmight not depend on the Bz/He ratio and their allocation. Although\nany clear correlation with the different Bz/He ratios was not observed\nfor both T flow and T offset , the Bag-BzHe series was found to start melt-flowing\nat a much lower temperatures range of 122–143 °C than\nthose for Bag-DeAc series and Bag-BzAc(71) ( Figure S5 ). In precise, the thermal processability of thermoplastics\ncan be evaluated from the gap between the decomposition temperature\nand melting/thermal-flowing temperature. 30 , 31 For instance, cellulose, featuring an intensive hydrogen-bonded\nstructure, has a much higher melting temperature than its decomposition\ntemperature, resulting in its significantlly poor thermal processability.\nSimilarly, lignocellulosic biomass, including bagasse, cannot be melted\nand is not suitable for thermal molding. However, the Bag-BzHe series\ncan be considered to have excellent thermal processability because\nthere is a sufficient gap over 100 °C between their T d-5% and T flow ( Table 2 ). Figure 4 (a) TG and (b) melt-flow\ncurves of Bag-BzHe series and Bag-HeBz.\nIn the melt-flow curves, the symbol ◯ indicates the T flow , while the symbol △ indicates the T offset . The hot-pressed films of Bag-BzHe series and Bag-HeBz(53)\nwere\nsubjected to tensile testing ( Figure 5 ). Bag-HeBz(53) containing the Bz-rich lignin derivative,\nas demonstrated in Section 3.3 , showed the highest tensile strength (20 MPa) and elastic\nmodulus (1.4 GPa) but the lowest elongation at break of only 2% that\nresulted in its poor strain energy density (0.17 MJ m –3 ). The rigid and brittle properties of the Bag-HeBz(53) might be\nattributed to the enhanced π–π interactions between\nthe benzoylated lignin moieties. 16 , 32 , 33 On the other hand, Bag-BzHe(51) showed a comparably\nhigh tensile strength (18 MPa) and a 5-fold higher elongation at break\n(10%), which contributed to a 10 times higher strain energy density\n(1.6 MJ m –3 ) than that of Bag-HeBz(53). This drastic\nimprovement in ductility of the acylated bagasse should result from\nour synthetic strategy that appropriately suppresses the benzoylation\nof lignin, while polysaccharides are sufficiently benzoylated. Figure 5 (a) Stress–strain\ncurves obtained in tensile testing of\nthe hot-pressed films of Bag-BzHe series and Bag-HeBz(53) and (b)\nthe average strain energy density and elastic modulus. With increasing the DS of the flexible He group, 34 , 35 the elongation at break of the Bag-BzHe series was further increased\nto 60%, and Bag-BzHe(90) showed the highest strain energy density\nof 4.8 MJ m –3 , which is 3 times higher than that\nof Bag-BzHe(51) and 28 times higher than that of Bag-HeBz(53). These\nresults indicate that the mechanical properties of the acylated bagasse\ncan be controlled by adjusting the molar ratio and also the allocation\nof the aromatic/aliphatic-mixed acyl groups. Although the tensile\nstrengths of the Bag-BzHe series were inferior to those of the previously\nreported bagasse benzoate, 36 the ductility\nof the Bag-BzHe series exceeds that of the bagasse benzoate because\nof its poor elongation at break (∼2%). Moreover, the stiffness\nof the bagasse benzoate can be attributed to the relatively abundant\nresidual OH groups and the resulting hydrogen bonding. 37 Hence, the OH content in the Bag-BzHe series\nshould be further considered as an important factor for the material\ndesign to improve their tensile strengths. Using other thermal molding\nprocesses, such as melt spinning, 38 , 39 can also be\neffective for the Ba-BzHe series, which may lead to highly orientated\npolymer chains by exploiting their excellent melt-flow characteristics."
} | 5,663 |
35542361 | PMC9080799 | pmc | 8,109 | {
"abstract": "Bio-electrochemical degradation of pentachlorophenol was carried out in single as well as dual chambered microbial fuel cell (MFC) with simultaneous production of electricity. The maximum cell potential was recorded to be 787 and 1021 mV in single and dual chambered systems respectively. The results presented nearly 66 and 89% COD removal in single and dual chambered systems with corresponding power densities of 872.7 and 1468.85 mW m −2 respectively. The highest coulombic efficiency for single and dual chambered counterparts was found to be 33.9% and 58.55%. GC-MS data revealed that pentachlorophenol was more effectively degraded under aerobic conditions in dual-chambered MFC. Real-time polymerase chain reaction showed the dominance of exoelectrogenic Geobacter in the two reactor systems with a slightly higher concentration in the dual-chambered system. The findings of this work suggested that the aerobic treatment of pentachlorophenol in cathodic compartment of dual chambered MFC is better than its anaerobic treatment in single chambered MFC in terms of chemical oxygen demand (COD) removal and output power density.",
"conclusion": "4. Conclusions The study demonstrates that PCP could be effectively treated as a co-metabolite in single as well as dual chambered MFC along with the production of electricity. The maximum value of cell potential for SCMFC and DCMFC were 787 mV and 1021 mV respectively. The significant reduction in COD values with corresponding high CE demonstrated the effectiveness of the system in removing PCP and its metabolites by the action of microorganisms. SEM and RTPCR results suggested that the nature of microbial community was influenced by the different operating conditions of SCMFC and DCMFC. In addition, the PCP removal was more pronounced under aerobic conditions in DCMFC than in the anaerobic chamber of SCMFC due to the presence of oxygen. The metabolite accumulation was reduced due to which better degradation was achieved. Therefore, the toxic chemicals can be treated in a bio-electrochemical system efficiently accompanied by the generation of electricity, however further studies are critical for scaling up of this technology.",
"introduction": "1. Introduction Chlorophenols (CPs) are a group of weakly acidic organic compounds which are used in herbicides, fungicides, pesticides, and disinfectants. 1,2 Pentachlorophenol (PCP), the most toxic of all the CPs, is used as a pesticide and wood preservative in the industries. 3 The United States Environment Protection Agency (USEPA) considers PCP as a probable carcinogen with severe health hazards. 4 In recent years, the dechlorination of PCP has gained significant attention, and various technologies have been developed to treat PCP, including zero-valent metal based degradation, 5 biological methods like biosorption and bioremediation, 6 enzyme-catalyzed oxidation, 7,8 photocatalytic degradation, 9 and electrochemical processes. 10 The sorption methods have the disadvantage of only transferring PCP from waste to adsorbent without its actual treatment. Similarly, the conventional techniques available to treat waste electrochemically are highly energy intensive. 1,11 Moreover, some bacteria can degrade PCP, but these biological methods result in excessive sludge production. 12 However, a combination of the two techniques for electrochemical bioremediation of wastewater can serve the better purpose and has been considered as a promising alternative for the treatment of PCP and other toxic organics along with energy generation. 13–15 Today, the modern world is dependent mainly on the electrical energy for most of its functioning, and yet the primary sources of this energy are fossil fuels. 16 The contribution of fossil fuels to the total global electricity demand in the year 2014 was 66% with the share of renewable sources limited to only 11%. 17 Therefore, with the inevitable crisis of fossil fuel exhaustion and deteriorating environmental conditions, there is an urgent need to shift the focus of energy supply for wastewater treatment from non-renewable to renewable sources. 18,19 Recently, the microbial fuel cell (MFC) has emerged as an efficient technology for the treatment of wide range of pollutants with a very little expenditure of external energy. 20,21 One of the most promising advantages is that energy recovered from MFC as a by-product can offset the treatment cost if the technology is properly scaled up. A MFC converts the stored chemical energy in organic compounds into electrical energy by using microorganisms. 15,22 MFC function on the principle of simultaneous reduction and oxidation where substrate in the anodic chamber is oxidized to release electrons. An electron acceptor consumes these released electrons in the cathodic chamber separated from the anodic chamber by a membrane. 23,24 The flow of electrons from the anode to the cathode in the process generates electric current. 20 This whole process is catalyzed by microorganisms that use part of the substrate for their growth while converting the other part into energy. 22 The reaction is complicated, and the performance of MFC is influenced by several factors including pH, conductivity, temperature, types of the substrates and electron losses. 25,26 Some studies have presented the treatment of PCP bio-electrochemically using MFCs, but the reports are limited to the lower concentrations of PCP (usually up to 50 ppm) with correspondingly lower power densities (PD). 12,27 Moreover, the degradation of PCP with simultaneous electricity production in single and dual chambered microbial fuel cell (SCMFC and DCMFC) are rarely compared in the scientific literature which is the primary focus of this study. In addition, attempts have been made to link the output PD with the chemical oxygen demand (COD) of the synthetic wastewater containing PCP. The bio-electrochemical behavior of the system was studied using cyclic voltammetry (CV), and the performance evaluation was carried out by estimating the cell potential, PD, coulombic efficiency (CE) and the COD removal efficiency of the two MFC systems. GC-MS technique further examined the quality of the treated water and fate of PCP metabolites. The findings of this work on the bio-electrochemical degradation of PCP would help to design new strategies for large-scale wastewater treatment plants along with energy production.",
"discussion": "3. Results and discussion 3.1. Bioelectricity generation The bioenergy recovered during the degradation of PCP in SCMFC, DCMFC, and control was monitored during the test period in terms of cell potential (mV), and the results are presented in Fig. 2 . It was observed that the current production was low initially with the addition of PCP in both the MFC systems. This could be due to the fact that the biological system was not much stable to tolerate the toxic effects of higher concentrations of PCP. However, the sludge became more acclimated with time, and as a result, the current production has been increased. In the case of SCMFC, the potential was observed to reach its peak value of 787 mV at 200 ppm of PCP and showed a diminishing trend with a further increase in PCP concentration ( Fig. 2a ). Conversely, in DCMFC, the cell potential increased as the concentration was increased from 50 to 100 ppm reaching the peak value of 1021 mV and decreased with further increase in PCP concentration ( Fig. 2b ). This occurrence of peak voltage at 200 ppm in case of SCMFC (instead of 100 ppm) could be due to the longer time taken by microbes to build a sustainable biofilm and promote current production. 36 However, as the concentration was further increased, voltage output dropped because of increased toxicity. Other researchers have reported similar trends of the current generation in the treatment of toxic compounds by MFC. 3,30 The system was fed with glucose twice a week to support the microbial activity and growth. For a particular cycle, the concentration of added substrate was decreased with time, and as a result, the current was dropped to the minimum value due to substrate limitations. The peaks in the graph represent the fresh addition of glucose. The falling trend of current with the increasing concentration of PCP could be due to the toxic effect of PCP on the microbial community, 15 which led to poor microbial activity and consequently decreased the production of current. This suggests that for continuous energy production, the substrate should be added at regular intervals to maintain the requisite feast to famine ratio. The maximum voltage output recorded for control (with only glucose) was 1076 mV. The lower output voltage recorded on the addition of PCP also suggests the inhibitory effect of PCP on microbes and ultimately the performance of MFC. Fig. 2 Variation of cell potential over the test duration for (a) SCMFC and (b) DCMFC. 3.2. Power density (PD), chemical oxygen demand (COD) removal and coulombic efficiency (CE) The performance of the reactors was also assessed in terms of PD (mW m −2 ), COD removal (%), and CE (%). The energy recovered in the form of electricity was directly proportional to the amount of organic carbon which in turn is related to the COD removed from the system suggesting that the energy in MFC is produced at the expense of COD. The initial COD of the system containing 100 ppm of PCP and 1 g L −1 glucose was 1410 mg L −1 , and the COD was dropped to 480 mg L −1 and 150 mg L −1 for SCMFC and DCMFC respectively during the course of 10 days of degradation. The COD removal efficiency was found to be highest for 100 ppm of PCP for both the reactor systems (65.9% for SCMFC and 89.6% for DCMFC). The PD, on the other hand, was highest (872.7 mW m −2 ) at 200 ppm for SCMFC. However, the PD for DCMFC was found to be highest at 100 ppm (1468.85 mW m −2 ). The peaks in PD curve correspond to fresh addition of glucose. The PD peaked every time the co-substrate was added to the medium. The highest PD recorded for control was 1631.36 mW m −2 . The lower PD in the case of SCMFC could be due to alternate pathways like methanogenesis, which might have taken place and as a result, the electrons produced were lost and could not be recovered as energy output. Although the COD removal was maximum at 100 ppm in case of SCMFC, but the maximum PD was recorded at 200 ppm. This phenomenon could be attributed to two reasons; either the electrons were lost in alternate pathways taking place in SCMFC or the biofilm took longer to become sustainable in case of SCMFC, and consequently, the power production was less at 100 ppm. As the PCP concentration was increased, PD decreased indicating the inhibitory effect of PCP on microbes leading to lower power output. 1,15 Fig. 3(a and b) linked the COD removal with PD curves during the course of the experiment. Fig. 3 COD and power density (PD) curve for (a) SCMFC and (b) DCMFC respectively. The DCMFC consistently produced higher power and showed high COD removal as compared to SCMFC even at higher PCP concentration. The CE was calculated by using the method suggested by Patil et al. 37 and presented in Fig. 4(a and b) . The CE for SCMFC was ranged from 7.8–33.9% with the highest CE of 33.9% for 200 ppm concentration of PCP ( Fig. 4a ). Similarly, the CE in the case of DCMFC was ranged from 9.3–58.55% with the highest CE of 58.55% at 100 ppm concentration of PCP ( Fig. 4b ). The lower CE corresponding to the higher concentrations of PCP was again attributed to the toxic effect of PCP on bacterial community thereby lowering the CE. Therefore, higher COD removal with correspondingly high PD suggests a better performance of DCMFC in terms of energy recovery as compared to SCMFC. The better performance of DCMFC could be due to more porous sludge with uniform channels, active and sustainable bacterial community growing in this system. For PCP-glucose fed MFC batch of 72 h, the coulombic balance of nearly 10% has been reported by Huang et al. 3 which is much lower than the values reported in the present work. Fig. 4 Oxygen based coulombic efficiency (CE) for (a) SCMFC and (b) DCMFC and (c) formation of chloride ion (Cl − ) during the experimental phase for SCMFC and DCMFC. 3.3. Degradation of PCP The first step of PCP degradation under anaerobic as well as aerobic conditions was dehalogenation that resulted in the stoichiometric rise of the chloride ion in the systems. The change in the chloride ion concentration over time was studied at 100 ppm PCP concentration for both SCMFC and DCMFC. As shown in the Fig. 4c , the chloride ion concentration increased with the passage of time for both the reactors implying that dehalogenation was the first step in PCP degradation. This agrees with GC-MS results (Fig. S3(a and b) † ). From the plots in Fig. 4c , it is clear that the chloride ion concentration of DCMFC increased at a faster rate than SCMFC, which further support the claim of faster dehalogenation and effective degradation of PCP in DCMFC. In order to ensure the degradation of PCP in both bioreactors, the effluents samples were scanned at wavelength range of 200–700 nm using UV-Vis spectrophotometer. The UV-Visible spectra of pure PCP samples show characteristic bands near 220, 250 and 320 nm as have also been reported by Gunlazuardi and Lindu, 38 and Murialdo et al. 39 Fig. 5(a and b) showed the UV-Visible spectra of effluents samples collected from SCMFC and DCMFC respectively along with spectra for pure PCP. The diminishing peaks observed in the samples collected after 10 days indicated the treatment and subsequent removal of PCP through the bio-electrochemical system. Fig. 5 UV/Visible spectra of PCP effluent collected from (a) SCMFC and (b) DCMFC. Studies on degradation pathways have become critical to track the fate of contaminants, intermediate metabolites, and final products. Both aerobic and anaerobic degradation of CPs have been reported earlier. 2,40,41 However, aerobic degradation of CPs has been studied extensively. 42 Different mechanisms proposed for CPs degradation suggests the initial monooxygenases attack followed by dehalogenases forming chloromaleyl acetic acid and maleyl acetic acid depending upon dehalogenation before or after ring cleavage via ortho or meta cleavage. 43,44 The degradation pathways as observed in this study (Fig. S3(a and b) † ) were in good agreement with those reported by Arora and Bae 41 and Louie et al. 45 The GC-MS spectra of the products extracted in ethyl acetate solvents are presented in Fig. S1 and S2 (ESI † ). Based on GC-MS results, degradation pathways of PCP in two MFC systems have been proposed in Fig. S3(a and b). † The anaerobic degradation of PCP ( m / z 266.34) in SCMFC was initiated by the reductive dehalogenation forming 2,3,4,5-tetrachlorophenol ( m / z 131), which was further converted to 3-chlorophenol ( m / z 126.5) with the stoichiometric rise in Cl − ions ( Fig. 4c ) following the conventional anaerobic pathway. The intermediate formed was finally converted to 4-hydroxy benzoic acid ( m / z 139) by the carboxylation of phenol. 46 Unlike anaerobic degradation, in the cathodic compartment of DCMFC under the oxygen supply, the PCP ( m / z 266.34) was initially transformed into 2,3,6-trichlorohydroquinone ( m / z 213.45) by the action of monooxygenases enzyme. This metabolite (2,3,6-trichlorohydroquinone) undergoes reductive transformation to give 2,3,6-trichlorophenol ( m / z 190.54). Dichlorohydroquinone products might have also formed during PCP degradation but remain undetected due to its instantaneous conversion into 2-chloromaleyl acetate and maleyl acetate ( m / z 156.09). The better degradation of PCP in DCMFC can be explained as the lack of oxygen leads to the accumulation of reduced moieties that tends to inhibit further treatment in SCMFC. Whereas in the presence of oxygen, these moieties are removed leading to better treatment of the substrate in the given system as reported by Huang et al. 47 3.4. Characteristics of sludge The surface morphologies and elemental compositions of the sludge obtained from the anodic compartment of the reactors were analyzed using SEM coupled with EDX. Fig. 6(a, b and c, d) showed the SEM images of sludge obtained from SCMFC and DCMFC at different magnifications (3000× and 7000×) respectively. The microscopic images of the sludge obtained from both the reactors showed the presence of a large number of mixed bacterial communities such as cocci and diatoms. A significant difference was seen in the sludge obtained from SCMFC and DCMFC due to the different operating conditions. The sludge from DCMFC was appeared to be quite porous as compared to the very dense sludge collected from SCMFC. Compact nature of anaerobic sludge from SCMFC resulted in to lower removal rates due to mass transfer limitations. 40 The porous anaerobic sludge from DCMFC showed better mass transfer whereby electrons could be transferred easily leading to its superior performance. Fig. 6(e and f) show the SEM images of the electrode surface before and after the biofilm formation. The EDX plot showed the elemental composition of the sludge from both studied reactors (Fig. S4(a and b) † ). In the case of sludge collected from SCMFC, the elements such as N, O, C, and Fe were present. Whereas in the case of DCMFC, the elements like C, N, O, Si, Al, P, and S were present. The micronutrients added (through nutrient broth) during the experiment resulted in some of the elemental peaks. The different composition observed in EDX could be due to the different operating conditions in SCMFC and DCMFC. Fig. 6 SEM images of SCMFC (a and b) and DCMFC (c and d) sludge at 3000× and 7000× (e and f) electrode with and without biofilm. 3.5. Electrochemical behavior and performance of MFCs The electrochemical behavior of anolyte present in both MFC systems was studied using CV. A three-electrode system was used to perform CV at a scan rate of 10 mV s −1 . A very good redox loop was obtained for both MFC systems confirming that the active microbial communities performed the electron transfer. Fig. 7a shows the voltammograms at 10 mV s −1 for SCMFC, wherein a perfect redox loop with a forward peak was obtained at 0.298 V. Two reverse peaks were obtained at −0.117 V respectively. In the case of DCMFC, a forward peak at 0.334 V was obtained using a scan rate of 10 mV s −1 indicating a clear oxidizing activity of microbes in the anodic chamber, while the reverse peak was obtained at the potential of −0.076 V ( Fig. 7b ). The broader voltammogram in case of DCMFC could indicate better performance of DCMFC as compared to SCMFC in terms of stability as well as capacitance. 48 The voltammograms obtained for SCMFC and DCMFC were entirely different in nature as compared to the control run that contains no PCP ( Fig. 7c ). Performance evaluation of the two MFC systems is given in Table 1 . Fig. 7 Cyclic voltammograms of (a) SCMFC (b) DCMFC and (c) control reactors. Performance evaluation of the two reactor systems – single and dual chambered MFC systems Parameters Range SC DC pH 4.9–7.2 7.0–8.1 Conductivity 0.5–1.4 mS cm −1 0.5–1.8 mS cm −1 Temperature 30.1–35.7 °C 30.1–35.7 °C Optical density 1.4–2.1 1.7–2.4 MLVSS 0.5–5 g L −1 3.5–6.5 g L −1 Cl − ion 70.9–425.4 mg L −1 70.9–567.2 mg L −1 Cell potential 61–787 mV 63–1118 mV PD 5.2–872.7 mW m −2 5.6–1761.2 mW m −2 3.6. Molecular biology of microbial communities The RTPCR technique was used to quantify few major genera of microbial communities present in the anodic compartments of MFC systems. The RTPCR is a powerful technique used for the estimation of real-time abundance of different microbial communities in terms of log gene copy number per mL. The absolute abundance of five major classes of methanogens namely MSC, MST, MCC, MBT, and MMB was estimated along with SRB and exoelectrogenic Geobacter and presented in Fig. 8a . Among the different classes of methanogens, MCC showed the highest abundance whereas MBT showed the least. The population of MMB was increased significantly as compared to other methanogens during the experiment. The presence of excess hydrogen utilizing bacteria indicated a part of the energy that might have been lost in the form of methane through hydrogen pathway by hydrogenotrophic bacteria. It was observed that the Geobacter population that was primarily responsible for the electricity generation in MFC was enhanced during the course of study. 22 From Fig. 8a , it was also evident that Geobacter was more dominant in DCMFC than SCMFC indicating better electron transfer and higher PD in the former. Fig. 8b presented the relative abundance of SRB, methanogens, and Geobacter with respect to total universal bacteria. It can be observed from the Fig. 8b that the population of SRBs responsible for inhibiting methanogenesis in the MFCs was significantly lesser than that of methanogenic population indicating the energy loss by methanogenesis ( Table 2 ). Fig. 8 Quantification of the microbial communities present in SCMFC and DCMFC by qPCR (a) absolute abundance and (b) relative abundance. Recent works on the degradation of PCP in MFC MFC setup Co-substrate Output Reference DCMFC with PCP (5–30 mg L −1 ) Glucose Acetate 1.7 W m −3 2.0 W m −3 Huang et al. 3 DCMFC with PCP (upto 30 mg L −1 ) Glucose Acetate 1.3 W m −3 2.0 W m −3 Wang et al. 12 DCMFC with PCP (5–40 mg L −1 ) Acetate 2.5 W m −3 Londry and Fedorak 46 SCMFC with PCP (5–15 mg L −1 ) Glucose Acetate 1.1 W m −3 7.7 W m −3 \n Huang et al. \n \n 27 \n \n SCMFC with glucose-PCP (500–1500 mg L −1 ) Glucose 7.8 W m −3 Alshehri 49 SCMFC and DCMFC with PCP (50–500 mg L −1 ) Glucose 0.047 W m −3 0.788 W m −3 Present work 3.7. Future outlook MFC has recently gained immense interest around the globe due to its characteristic property of driving direct electrical output from the wastewater. Different types of substrates have been utilized in MFC for electricity generation like dyes, domestic wastewater besides others. The results of the present study depicted that MFC could effectively treat the toxic compounds to generate electricity while converting it to simpler less toxic counterparts. The work compared the anaerobic and aerobic treatment of PCP and suggested that the treatment of xenobiotic PCP could better achieve in aerobic conditions of DCMFC than SCMFC. However, to scale up the system, studies are required to lower the process and capital costs without compromising its performance. The lower PD could be improved by increasing the surface area and using the better material of the electrodes. Future research should be focused on less costly membranes and materials like ceramics in order to implement the technology at the commercial scale in treating toxic compounds like PCP. Moreover, the cascade of MFC arranged in parallel and series should be compared for better treatment and higher sustainable electrical output. Methanogenesis was found to be one of the main reasons for energy loss which could be decreased by maintaining proper pH and adding chemicals to suppress the growth of methanogens in the system. In developing countries like India, PCP is mainly used in wood preservation from where it finds its way into the water bodies. Scaling up this technology could benefit in treating the effluent PCP wastewater before discharging to the water bodies and supporting the electrical need of the industry. The results of the present study suggest that the effective biodegradation of xenobiotic PCP could be achieved in aerobic conditions of DCMFC. Furthermore, the results could help design reactors to scale up the technology in future."
} | 5,927 |
30401769 | PMC6222129 | pmc | 8,111 | {
"abstract": "Bacteria in natural and engineered environments form biofilms that include many different species. Microorganisms rely on a number of different strategies to manage social interactions with other species and to access resources, build biofilm consortia, and optimize growth. For example, Pseudomonas aeruginosa and Staphylococcus aureus are biofilm-forming bacteria that coinfect the lungs of cystic fibrosis patients and diabetic and chronic wounds. P. aeruginosa is known to antagonize S. aureus growth. However, many of the factors responsible for mixed-species interactions and outcomes such as infections are poorly understood. Biofilm bacteria are encased in a self-produced extracellular matrix that facilitates interspecies behavior and biofilm development. In this study, we examined the poorly understood roles of the major matrix biopolymers and their regulators in mixed-species biofilm interactions and development.",
"introduction": "INTRODUCTION Bacteria exist predominantly as dense, self-organized communities encased in self-produced matrices known as biofilms ( 1 , 2 ). They exhibit emergent properties that are not found in their single-cell planktonic counterparts, such as altered and enhanced metabolic efficiency ( 3 – 5 ), increased robustness and resistance to antimicrobial attack ( 6 , 7 ), altered virulence ( 8 , 9 ), and enhanced horizontal gene transfer ( 10 , 11 ). These emergent properties contribute to their roles in the Earth’s natural cycling of nitrogen and sulfur and of many metals ( 12 – 14 ) as well as in survival in host organisms, where they can live as commensals or as pathogens ( 14 ). While biofilms usually encompass a large diversity of bacterial species that have synergistic, mutualistic, competitive, or antagonistic relationships, the fundamental mechanisms that drive mixed-species biofilm development and the associated emergent properties remain poorly understood. Pseudomonas aeruginosa and Staphylococcus aureus are opportunistic pathogens found in infections of cystic fibrosis (CF) lungs and in diabetic and chronic wounds ( 14 , 15 ). Such mixed-species infections are correlated with poor clinical outcomes ( 16 ); hence, the two organisms serve as a model dual-species community to represent polymicrobial infections ( 17 , 18 ). The two bacterial species are known to have an antagonistic relationship, where P. aeruginosa produces heptyl-4-hydroxyquinoline N-oxide (HQNO), a potent inhibitor of respiratory electron transfer and a component of its Pseudomonas quinolone signal (PQS) system, to kill S. aureus ( 19 ). However, this also selects for S. aureus small-colony variants (SCVs) that have mutations in the electron transport chain and increased resistance to P. aeruginosa killing ( 20 ). This has an impact on disease prognosis, as the prevalence of S. aureus SCVs is correlated with a more severe disease state ( 16 ). P. aeruginosa also induces the production of the host enzyme sPLA2-IIA to kill S. aureus ( 21 ). While these two species serve as a model system for polymicrobial infections, the mechanisms of interaction during dual-species biofilm formation has been less extensively explored. P. aeruginosa is known to express three polysaccharides, alginate, Pel, and Psl, as the major matrix components ( 22 ). P. aeruginosa isolates from the cystic fibrosis (CF) lung environment tend to become mucoid through overexpression of alginate ( 23 ). However, only Pel and Psl have been shown to be required for biofilm formation ( 24 , 25 ). Psl is important for surface attachment ( 24 , 26 , 27 ), autoaggregative phenotypes in batch cultures ( 28 – 30 ), and activation of specific enzymes (diguanylate cyclases [DGCs]) to increase intracellular levels of cyclic-di-GMP, triggering P. aeruginosa to enter the biofilm mode of life ( 31 , 32 ). Thus, the loss of Psl results in delayed biofilm development and either a delay in or loss of microcolony formation ( 25 , 26 , 33 ). Pel is often associated with the formation of floating biofilms (pellicles) and plays a role in biofilm maturation ( 24 , 26 , 33 ). Pel and Psl have different mechanical properties and resistances to flow that result in differences in biofilm structure and development ( 33 ). In mucoid P. aeruginosa - S. aureus biofilms, Psl expression led to P. aeruginosa exclusively occupying the upper layer of biofilms, whereas Pel expression appeared to increase colocalization of P. aeruginosa and S. aureus ( 33 ). Recently, it was found that protein A, a cell wall protein of S. aureus , binds to the Psl polysaccharide and type IV pili in P. aeruginosa to inhibit biofilm formation ( 34 ). The Psl polysaccharide is also known to affect the community structure and stress resistance, where it confers antibiotic protection to the Escherichia coli - S. aureus biofilm community ( 35 ), as well as increased P. aeruginosa abundance and SDS tolerance of three-species biofilms of P. aeruginosa , Pseudomonas protegens , and Klebsiella pneumoniae ( 36 ). Thus, the composition of the biofilm matrix represents an important and yet largely underexplored mediator of interspecies interactions and confers emergent properties to the community. To address how Pel and Psl affect P. aeruginosa competitiveness, biofilm structure, and rheology in mixed-species biofilm communities, we established dual-species biofilms of P. aeruginosa and S. aureus . We explored the importance of the structural role of Psl in the biofilm matrix through analysis of the adhesin CdrA, which physically binds P. aeruginosa cells to the Psl matrix ( 28 ), and the regulatory role of Psl in biofilm formation through analysis of the diguanylate cyclases SadC and SiaD, which are activated by Psl to increase c-di-GMP levels ( 31 , 32 ). In this study, we demonstrate that Psl enables wild-type P. aeruginosa to outcompete S. aureus in early biofilm development and that SiaD is necessary for P. aeruginosa to outcompete S. aureus in a pyoverdine- and PQS-independent manner. In late-stage biofilm development, the production of Pel is required to reduce the effective cross-linking of the matrix to increase the spreading surface coverage of P. aeruginosa in dual-species biofilms.",
"discussion": "DISCUSSION Coinfections of P. aeruginosa and S. aureus are often found in patients with cystic fibrosis (CF) and with diabetic and chronic wounds. Such mixed-species infections are correlated with poor clinical outcomes ( 16 ); hence, these two organisms serve as a model, dual-species community to represent polymicrobial infections ( 18 , 43 , 46 ). The interactions between the two organisms affect the efficacy of antimicrobial treatments ( 46 ). P. aeruginosa has been found to compete with S. aureus for oxygen and to induce the bacterium to shift to fermentative metabolism to produce lactate, which P. aeruginosa consumes ( 18 ). P. aeruginosa can also lyse S. aureus to obtain iron. This is mediated through induction of PQS-dependent virulence genes as well as the production of siderophores ( 43 ). However, detailed investigation of interspecies interactions during dual-species biofilm formation and the role of the biofilm matrix in enabling interspecies interactions and determining community structure have been less extensively explored. In this study, P. aeruginosa restricted S. aureus growth and biofilm formation, whereas in the presence of S. aureus , P. aeruginosa showed an increased surface coverage and number of microcolonies. Further, P. aeruginosa microcolonies were larger and the overall biovolume was higher when S. aureus was present. Similar observations were previously reported for these dual-species combinations, where it was suggested that P. aeruginosa lysed S. aureus to be used as a nutrient source ( 18 , 43 ). Pel and Psl polysaccharides were not required for P. aeruginosa to outcompete S. aureus , which was similar to the result seen with mucoid P. aeruginosa - S. aureus biofilms ( 33 ). Nevertheless, distinct effects contributed by the polysaccharides, such as reduced formation of S. aureus microcolonies during early biofilm development (mediated by Psl) and increased biofilm biovolumes of P. aeruginosa during mid- to late-stage biofilm development by Pel, were observed. These findings are consistent with a shift in production with time of biofilm formation, from Psl to Pel, similar to that documented for monospecies biofilms ( 33 ). In addition, the data indicate that Pel increases surface coverage throughout biofilm development and expands the microcolony size in mature biofilms. This finding aligns with that of our previous study, i.e., that Pel enhances spreading in monospecies biofilms ( 33 ). The latter study also attributed the differences in biofilm structures to Psl generating a more elastic and cross-linked matrix and Pel contributing a loose and viscoelastic matrix. Indeed, in agreement with the results obtained for monospecies biofilms, we found that Psl increased the effective cross-linking of the microcolonies in dual-species biofilms ( Fig. 4 ), making them less compliant ( Table 5 ) and more compact ( Fig. 1 ). Psl was the major contributor of effective cross-linking in the biofilm, while the CdrA adhesin and biofilm regulatory components SadC and SiaD played less of a role ( Fig. 6 ) (see also Table S1 in the supplemental material). Interestingly, the microcolonies that expressed only Pel were more elastic than the microcolonies that expressed only Psl, and the microcolonies that expressed both Pel and Psl were the most viscous. This indicated that the rheological contributions of the polysaccharides were not simply additive and that the physical structure changed in the absence of one of these polysaccharides. In addition to changes in the mechanical properties of the biofilm in the presence of S. aureus , it is possible that the Psl matrix is more viscous when it is produced under static versus flow conditions. This may reflect observations of biofilms on rocks beneath waterfalls that are constantly exposed to high shear ( 47 , 48 ). The expression levels of both Pel and Psl were associated with superdiffusion of particles and with a more compliant biofilm matrix ( Fig. 4 ) ( Table 5 ). The superdiffusion of particles could be the result of fast movement of cells. P. aeruginosa is known to be motile, mediated by swimming, swarming, and twitching based processes. Superdiffusion could also be the result of particles travelling directionally through biofilm channels. For example, Birjiniuk et al. (2014) observed particle trajectories that indicated that the particles were travelling from top to the bottom of the biofilm through interconnected fluid-filled microscale channels ( 49 ). The ability of Psl to initiate P. aeruginosa biofilm formation and mediate competitive fitness may be linked to its ability to facilitate biofilm formation through activating DGCs, leading to c-di-GMP production. Indeed, the SiaD DGC, activated by Psl ( 31 ), was critical for P. aeruginosa competitiveness in the dual-species biofilms ( Fig. 5 ). Without SiaD, P. aeruginosa and S. aureus were equally competitive, with r ij = 0.01 ± 0.04 at 19 h, with S. aureus establishing many microcolonies in the dual-species biofilm ( Fig. 5 ). Moreover, SiaD induces autoaggregation in P. aeruginosa when exposed to SDS stress ( 50 ) and /tellurite (TeO 3 2– ) ( 32 ). In a previous study ( 50 ), Psl was found to be essential for autoaggregation. Hence, it is possible that SiaD is activated by exoproducts from S. aureus , providing a mechanism by which P. aeruginosa can sense S. aureus to induce autoaggregation and biofilm formation. P. aeruginosa is known to outcompete S. aureus using the siderophore pyoverdine and downstream products of the PQS biosynthetic pathway in planktonic cultures ( 18 , 43 ). In monospecies P. aeruginosa biofilms, SiaD has been found to negatively control pyoverdine production ( 51 ). Similarly, high c-di-GMP concentrations reduce PQS production ( 52 ). Thus, it was unexpected that the production levels of pyoverdine and PQS in the Δ siaD mutant were not increased but rather were similar to those seen with wild-type P. aeruginosa biofilm cocultures ( Fig. 7 ). Complementation of the siaD mutant resulted in pyoverdine and PQS levels similar to the levels seen with wild-type P. aeruginosa monospecies biofilms but not dual-species wild-type biofilms ( Fig. 7 ). This indicated that the overproduction of PQS in the siaD mutant does not play a significant role in the competitive phenotype here and that the impact of overproducing SiaD and, hence, of elevated c-di-GMP levels drives competition through another factor that is siderophore and PQS independent. Further investigation is required to understand the underlying mechanism of how SiaD activity increases the competitiveness of P. aeruginosa . The findings presented here provide novel information on the mechanisms by which the P. aeruginosa - S. aureus dual-species biofilms are established and how P. aeruginosa dominates the community during biofilm development. We summarize the findings in Fig. 8 , where we show that the Psl polysaccharide is required for initial competition whereas the Pel polysaccharide enables the predominance of P. aeruginosa in mature, dual-species biofilms ( Fig. 8A ). It is also clear that the SiaD cyclase is important for P. aeruginosa competitiveness, which occurs in a pyoverdine- and PQS-independent fashion, with the siaD mutant producing amounts similar to those produced by the wild-type strain and the complemented siaD mutant producing less than the wild-type, dual-species biofilms ( Fig. 8B ). This highlights the fact that the regulatory mechanisms governing competition between P. aeruginosa and S. aureus are likely to be complex, incorporating recognition of a competitor and temporal regulation of different factors that impact the dual-species interactions. These results help to increase understanding of the mechanisms by which these two opportunistic pathogens interact during biofilm formation and could suggest strategies for the control of dual-species infections. FIG 8 Schematic showing how matrix polysaccharides and SiaD contribute to P. aeruginosa predominance in dual-species P. aeruginosa - S. aureus communities. (A) Psl enhances P. aeruginosa competitiveness in early stages, possibly via SiaD activation, whereas Pel enables biofim expansion to increase P. aeruginosa predominance in the later stages. (B) Dominance of wild-type P. aeruginosa and SiaD and SiaD complement mutant over S. aureus , with their corresponding PQS/pyoverdine (PVD) levels."
} | 3,698 |
24504095 | PMC3913579 | pmc | 8,112 | {
"abstract": "Due to impressive achievements in genomic research, the number of genome sequences has risen quickly, followed by an increasing number of genes with unknown or hypothetical function. This strongly calls for development of high-throughput methods in the fields of transcriptomics, proteomics and metabolomics. Of these platforms, metabolic profiling has the strongest correlation with the phenotype. We previously published a high-throughput metabolic profiling method for C. glutamicum as well as the automatic GC/MS processing software MetaboliteDetector. Here, we added a high-throughput transposon insertion determination for our C. glutamicum mutant library. The combination of these methods allows the parallel analysis of genotype/phenotype correlations for a large number of mutants. In a pilot project we analyzed the insertion points of 722 transposon mutants and found that 36% of the affected genes have unknown functions. This underlines the need for further information gathered by high-throughput techniques. We therefore measured the metabolic profiles of 258 randomly chosen mutants. The MetaboliteDetector software processed this large amount of GC/MS data within a few hours with a low relative error of 11.5% for technical replicates. Pairwise correlation analysis of metabolites over all genotypes showed dependencies of known and unknown metabolites. For a first insight into this large data set, a screening for interesting mutants was done by a pattern search, focusing on mutants with changes in specific pathways. We show that our transposon mutant library is not biased with respect to insertion points. A comparison of the results for specific mutants with previously published metabolic results on a deletion mutant of the same gene confirmed the concept of high-throughput metabolic profiling. Altogether the described method could be applied to whole mutant libraries and thereby help to gain comprehensive information about genes with unknown, hypothetical and known functions.",
"conclusion": "Conclusion Taken together the described combination of high-throughput transposon insertion site determination and metabolome analysis allows to investigate many gene functions at once. The here described first analysis of selected mutants shows the confirmation of already known gene functions and indicates potential functions for genes with unknown function. In many cases metabolic profiling alone is not able to prove a gene function and therefore, additional information has to be gathered. The integration of systems biology data from different levels would greatly complement the collected data and together this would build up a highly promising source of knowledge about microorganisms.",
"introduction": "Introduction The technological progress in genomic research led to a dramatic increase of knowledge of whole genome sequences, opening the demand of understanding the complex and dynamic processes of gene expression, proteomics and metabolic pathways. While a rapid development in multiparallel analytical methods for transcriptomics and proteomics has already taken place [1] the field of metabolomics still lacks appropriate techniques. Only in recent years first metabolic high-throughput methods were published [2] – [5] . Compared to the other Omics-platforms, metabolomics closely reflects cell activity at the functional level and therefore is often directly correlated with the cellular phenotype. Observed changes in transcriptome and proteome level do not always correspond to phenotypic alterations [6] . Even the interpretation of metabolic data is often not straightforward. Due to the convoluted state of cell metabolism, where many metabolites are involved in different pathways, it is difficult and sometimes even impossible to establish a direct link between genes and metabolites [6] . The Gram-positive soil bacterium Corynebacterium glutamicum is widely used in the industrial production of amino acids such as L-glutamate and L-lysine [7] . Two independent groups published the genome of C. glutamicum, containing approximately 3000 genes [8] , [9] . Applying homology studies, functions could be assigned to around 83% of the protein-coding genes, many of them putative or even highly speculative [8] . Nowadays large transposon mutant libraries are available for defined organisms, applying random transposon mutation [10] – [12] . For example, C. glutamicum was used to generate over 10,000 [13] or even 18,000 [14] mutants. Moreover, Suzuki et al. [14] added a high-throughput transposon insertion location method, working with a thermal asymmetric interlaced PCR (TAIL-PCR) [15] to amplify transposon border regions. Using the sequenced TAIL-PCR products with BLAST, 18,000 mutants were identified. Such a library of identified mutants offers a valuable source for research in systems biology. We [3] developed a high-throughput method for the analysis of metabolic profiles of C. glutamicum mutants and showed, that it is possible to measure 72 samples per day, assuring high sensitivity as well as good reproducibility of the analysis. Nevertheless, our method revealed two small bottlenecks in throughput: insertion site determination and data processing. While the measurement of hundreds of mutants could be carried out within days, processing of the corresponding GC/MS data took weeks because of the absence of appropriate software. Secondly, the determination of the insertion sites was missing a high-throughput method and therefore only single mutants were identified. In recent years, several automatic GC/MS processing software packages have been developed amongst others: TagFinder [16] , MetaboliteDetector [17] , MetAlign [18] , Mzmine 2 [19] , which all reduce the processing time significantly. In our study we used a further developed version of our in-house developed software MetaboliteDetector to process 861 samples automatically, comprising 774 mutant, 45 wild type and 42 quality standard samples within a few hours. Together with the here-described adapted high-throughput insertion point determination for the C. glutamicum transposon mutant library, we were able to study changes in the metabolic phenotype and combine these with data of the genomic background for every single mutant of this random transposon mutant library.",
"discussion": "Discussion As shown by Choorapoikayil et al. [40] , the analysis of metabolite levels permits to clarify predicted gene functions. To analyze not only single, but many mutants in parallel, we established a method for the high-throughput analysis of a transposon mutant library of C. glutamicum . We divided the method into two parts: first, investigation of the genomic background and, second, the analysis of the metabolic profiles of the mutants. We were able to identify the accurate position of the transposon in 722 mutants within a short time. Beside the identification of disrupted genes in mutants, we were interested in the distribution of the insertion sites in the genome. We could confirm the random integration of the vector pAT6100 into the genome of C. glutamicum , without any site preference ( figure 1 ). A review of the insertion points revealed that for more than a third of the genes of the identified mutants no or only a hypothetical function could be assigned by bioinformatic methods. Analysis of the growth distribution of 258 randomly chosen mutants showed, that the analyzed mutants can be divided into four groups, from no growth (<40%) over reduced growth (40–80%) up to similar (80–120%) and even enhanced growth (>120%) compared to the wild type on glucose minimal medium. The majority of the mutants (80%) showed a comparable growth to the wild type. The growth behavior of the mutants together with the identified insertion points provide important information suitable for the detailed understanding of C. glutamicum . Only 22 of the 258 investigated mutants were not able to grow on minimal medium, whereas five mutants showed an increased growth compared to the wild type. For a detailed discussion of the growth of single mutants further experiments need to be done. Nevertheless, our current findings demonstrate the possibilities, which a transposon mutant library with identified mutations presents. We applied our in-house developed software MetaboliteDetector to process the huge amount of GC/MS data. With the aid of this tool we obtained a very low overall relative error of 11.5% for the metabolome samples of the quality standard. In total, almost 300 substances with biological response were detected, which is a very good coverage for the detailed analysis of the metabolism. A pairwise correlation of the metabolites of all analyzed mutants was performed to get a cross section of the dependencies of the metabolites in C. glutamicum ( figure 3 ). These correlations reflect many known dependencies like the correlation of the metabolites of the TCA cycle, the correlation of the fatty acids or the correlation of the amino acids glycine and serine. The reduction of the complexity in a dendrogram ( figure 4 ) showed interesting clusters of the metabolites. Besides already known dependencies of metabolites, this view enabled the allocation of so far non identified metabolites to groups of known metabolites. This provides the opportunity to gather further information about the identity of these metabolites. Since a metabolite interacts with many other metabolites, the complexity of the metabolism is very high. Additionally, only parts of the metabolic pathways can be investigated with the present analytical methods as the metabolite classes are chemically too diverse to be detected by one method. But still, for limited parts of the metabolism like the TCA cycle, dependencies are well represented by the pairwise correlations. To get a first inside into the large amount of data we filtered the data for interesting mutants by searching for specific patterns of closely related metabolites, as shown in figure 5 . For the TCA cycle, changes in the metabolite level reflect the position of the metabolites in the pathway relatively well. While citrate and α-ketoglutarate seem to be regulated independently of the other intermediates, succinate, fumarate and malate are mostly co-regulated. Further, fumarate and malate often share the same fold change which underlines the close connection of the two metabolites. Compared to the TCA cycle, the picture drawn by the ratios of glutamate associated metabolites in figure 5B is more complex. Because the metabolites are not part of a linear pathway, changes do not necessarily affect the other metabolites. But still, there are visible patterns and connections between mutants, as for P7E1 and P7A10, both showing an increased concentration of glutamine and proline. The mutant P7A10 which is mutated in the gene glnE ( NCgl2147 ) encoding the glutamate-ammonia-ligase adenylyltransferase (EC 2.7.7.42) offers a good opportunity to prove the high-throughput metabolic profiling method, as well as the phenotype of the mutant, as Rehm et al. [31] already analyzed a glnE deletion mutant in detail. A comparison of our results with the published results showed a high degree of accordance in the measured metabolite levels, which confirms the stability of the transposon and proves the comparable phenotypes resulting from a transposon mutant and a deletion mutant of the same gene. Additionally, increased levels of 2,6-diaminopimelate and decreased levels of aspartate in the glnE mutant indicate a connection of the 2,6-diaminopimelate synthesis to the regulation of the GS/GOGAT system. As the 2,6-diaminopimelate production involving tetrahydrodipicolinate succinylase (DapD, EC 2.3.1.117) is regulated dependent on the nitrogen supply ( figure 6B ), it seems that the inactivation of the glutamate-ammonia ligase adenylyltransferase or the resulting increased activity of the glutamate-ammonia ligase are inducing an increased flux through the tetrahydrodipicolinate succinylase involving synthesis of 2,6-diaminopimelate in C. glutamicum . The increased level of proline and glutamine in the mutant P7A10 were found with an even stronger response in the so far not identified mutant P7E1 ( figure 5B ). Glutamine and proline are relatively closely related in the metabolism and together they are part of the response to osmotic stress in C. glutamicum \n [36] . Since the regulation of the proline synthesis via proA , proB, proC is still unknown [41] we suspect that in the mutant P7A10 the inactivation of the glutamate-ammonia ligase adenylyltransferase or the resulting increased activity of the glutamate-ammonia ligase induces the synthesis of proline. Altogether, the observations made for the mutant P7A10 indicate a central role of the glutamate-ammonia ligase adenylyltransferase in several nitrogen dependent reactions in C. glutamicum , which is supported by the speculations made by Rehm et al. [31] that this enzyme possesses a moonlighting function. Raamsdonk et al. [42] have shown that it is possible to reveal gene functions by comparing metabolic responses of mutations in unknown genes with the response of mutations in genes with known function. The mutants P7A10 and P7E1 showed a high degree of accordance in their metabolic profiles, which indicates a possible gene function for the mutant P7E1 in the GS/GOGAT system as well. As the insertion point in this mutant could not be determined so far, any gene function prediction at this point is impossible and further analysis have to be done. Another mutant, which showed an increased amount of proline (10 fold), is P8F12 ( NCgl1051 ). For this mutant, a strongly decreased N-acetyl-glutamate pool (0.07 fold) was detected. For these extreme values two explanations are possible. At first, according to Lee et al. [37] proline reduces the binding of the ArgR regulator upstream of argB , which is encoding for the N-acetylglutamate kinase (EC 2.7.2.8). In consequence, the transcription of this enzyme is enhanced, which leads to a reduced intracellular concentration of its substrate N-acetyl-glutamate. The second explanation implies that the affected gene is involved in arginine biosynthesis. This hypothesis is supported by the reduced transcription of the gene NCgl1051 under nitrogen limitation, which was found by Silberbach et al. [38] and correlates with the reduced transcription of the genes responsible for arginine biosynthesis. Contrary to the first explanation, a similar high concentration of proline in the mutant P7E1 showed only a slightly decreased N-acetyl-glutamate concentration (0.72 fold). The mutation of the gene gltB ( NCgl0181) , encoding for the glutamine 2-oxoglutarate aminotransferase large subunit (EC 1.4.1.13) in the mutant P21G11 affirms the subordinated role of the GOGAT part of the GS/GOGAT system during sufficient nitrogen supply. The mutant showed no significant changes in the glutamate associated metabolites. Furthermore the mutant showed good growth (119%) and a high correlation coefficient to the wild type (0.98). Although this indicates only a minor influence of the mutation, for a small number of metabolites significant changes were observed. These changes affect the TCA cycle intermediates succinate (1.4 fold), malate (1.7 fold) and fumarate (1.4 fold), as well as serine (2.4 fold) and glycine (2.0 fold), which all showed increased concentration compared to the wild type. The increased growth together with the increased concentration of the TCA cycle intermediates indicate an increased energy metabolism in the mutant. Based on the findings made by Beckers et al. [43] the gene gltB ( NCgl0181) was expected to be repressed by AmtR during sufficient nitrogen supply. Therefore, the origin of the observed changes in the metabolism as a response to the introduced transposon in this gene remains to be elucidated."
} | 3,981 |
35112906 | PMC8812319 | pmc | 8,114 | {
"abstract": "ABSTRACT We report the complete genome sequence of Acidithiobacillus ferriphilus GT2, an acidophile isolated from gold mill tailings. The circular genome of GT2 contains 2,489 predicted protein-coding units and a single plasmid. Functional analysis indicates the metabolic potential to oxidize iron and reduced sulfur compounds and to fix N 2 and CO 2 ."
} | 89 |
19458652 | null | s2 | 8,115 | {
"abstract": "Earlier, we discovered that the global regulator, Hha, is related to cell death in biofilms and regulates cryptic prophage genes. Here, we show that Hha induces excision of prophages, CP4-57 and DLP12, by inducing excision genes and by reducing SsrA synthesis. SsrA is a tmRNA that is important for rescuing stalled ribosomes, contains an attachment site for CP4-57 and is shown here to be required for CP4-57 excision. These prophages impact biofilm development, as the deletion of 35 genes individually of prophages, CP4-57 and DLP12, increase biofilm formation up to 17-fold, and five genes decrease biofilm formation up to sixfold. In addition, CP4-57 excises during early biofilm development but not in planktonic cells, whereas DLP12 excision was detected at all the developmental stages for both biofilm and planktonic cells. CP4-57 excision leads to a chromosome region devoid of prophage and to the formation of a phage circle (which is lost). These results were corroborated by a whole-transcriptome analysis that showed that complete loss of CP4-57 activated the expression of the flg, flh and fli motility operons and repressed expression of key enzymes in the tricarboxylic acid cycle and of enzymes for lactate utilization. Prophage excision also results in the expression of cell lysis genes that reduce cell viability (for example, alpA, intA and intD). Hence, defective prophages are involved in host physiology through Hha and in biofilm formation by generating a diversified population with specialized functions in terms of motility and nutrient metabolism."
} | 394 |
25368869 | PMC4202804 | pmc | 8,117 | {
"abstract": "Chemical conversions mediated by microorganisms, otherwise known as microbial biotransformations, are playing an increasingly important role within the biotechnology industry. Unfortunately, the growth and production of microorganisms are often hampered by a number of stressful conditions emanating from environment fluctuations and/or metabolic imbalances such as high temperature, high salt condition, strongly acidic solution, and presence of toxic metabolites. Therefore, exploring methods to improve the stress tolerance of host organisms could significantly improve the biotransformation process. With the help of synthetic biology, it is now becoming feasible to implement strategies to improve the stress-resistance of the existing hosts. This review summarizes synthetic biology efforts to enhance the efficiency of biotransformations by improving the robustness of microbes. Particular attention will be given to strategies at the cellular and the microbial community levels.",
"conclusion": "Concluding Remarks Biotransformations permit the production of chemicals in an economic and environment-friendly way. Despite its versatility, such processes have still not yet fulfilled their potential. This is due in part to the vulnerability of host organisms to fluctuating environmental conditions. Synthetic biology offers scientists tremendous opportunities to engineer microbial strains with desired properties to tolerate these conditions. Implementation of stress-resistant traits leading toward increased robustness is an attractive strategy for improving the efficiencies of biotransformations. More efforts are still required to increase understanding of the stress-resistant mechanisms exhibited in nature. In addition, future attention needs to be given to the screening and engineering of natural plug-and-play stress-resistant modules and development of more feasible methods for the re-design of the host chassis. Overall, the development of highly robust microbial hosts systems will require an in-depth understanding of stress-resistant mechanisms operating at both the cellular and community levels.",
"introduction": "Introduction In the biotechnology industry, chemicals required for a wide variety of sectors including food, medicine, and energy can be obtained through microbe-mediated chemical conversions, alternatively known as “microbial biotransformations.” Despite the versatile applications, the full potential of microbial biotransformations has not been fulfilled yet due to several unsolved problems (Woodley, 2013 ). One critical problem is that the growth and productivity of host organisms are often severely constrained by multiple adverse conditions, which lead to stress. Therefore, exploring methods to improve the stress tolerance of organisms within the fermentation industry, could significantly improve the productivity, shrink production costs, reduce energy consumption, increase substrate utilization, mitigate the risk of contamination, and so on. Synthetic biology, defined as the application of engineering principles to biology, aims to make the process of designing genetically encoded biological systems more systematic, predictable, robust, scalable, and efficient (Wang et al., 2013 ). Consequently, by supplying cells with devices and parts that confer resistance to stress, synthetic biology therefore offers a powerful approach for improving the properties of existing microbial biotransformation systems. In this review, we will describe recent synthetic biology efforts to improve the robustness of microbes for the purpose of increasing biotransformational efficiencies. Particular focus will be given to improvements made on the cellular and the microbial community levels."
} | 925 |
33826904 | null | s2 | 8,118 | {
"abstract": "The bacterium Bdellovibrio bacteriovorus attaches to the exterior of a Gram-negative prey cell, enters the periplasm, and harvests resources to replicate before lysing the host to find new prey."
} | 48 |
30007313 | PMC6158489 | pmc | 8,120 | {
"abstract": "Abstract The small molecule cyclic di-GMP (c-di-GMP) is known to affect bacterial gene expression in myriad ways. In Vibrio cholerae in vivo , the presence of c-di-GMP together with the response regulator VpsR results in transcription from P vpsL , a promoter of biofilm biosynthesis genes. VpsR shares homology with enhancer binding proteins that activate σ54-RNA polymerase (RNAP), but it lacks conserved residues needed to bind to σ54-RNAP and to hydrolyze adenosine triphosphate, and P vpsL transcription does not require σ54 in vivo . Consequently, the mechanism of this activation has not been clear. Using an in vitro transcription system, we demonstrate activation of P vspL in the presence of VpsR, c-di-GMP and σ70-RNAP. c-di-GMP does not significantly change the affinity of VpsR for P vpsL DNA or the DNase I footprint of VpsR on the DNA, and it is not required for VpsR to dimerize. However, DNase I and KMnO 4 footprints reveal that the σ70-RNAP/VpsR/c-di-GMP complex on P vpsL adopts a different conformation from that formed by σ70-RNAP alone, with c-di-GMP or with VpsR. Our results suggest that c-di-GMP is required for VpsR to generate the specific protein–DNA architecture needed for activated transcription, a previously unrecognized role for c-di-GMP in gene expression.",
"introduction": "INTRODUCTION Biofilm formation and its persistence on catheters, pacemakers, sutures and other indwelling medical devices account for the vast majority of the two million healthcare-associated annual infections and approximately 100 000 deaths per year in the USA ( 1 ). These biofilm-based infections impose an estimated annual $94 billion in excess medical costs ( 2 ). Forming on both biotic and abiotic surfaces, biofilms are aggregates of microbial communities encased by a matrix of extracellular polymeric substances ( 3 ). Biofilms, which are formed by almost all bacteria, play a significant role in environmental persistence, dissemination and transmission as well as protection from environmental stressors such as nutrient limitation, predation and bacteriophages ( 4–8 ). However, most concerning of all, biofilms dramatically decrease susceptibility to antimicrobial agents, posing a serious threat to public health. Because biofilms are recalcitrant to conventional antibiotic therapies and represent a major clinical obstacle, it is essential to understand the molecular mechanisms responsible for biofilm gene expression. A central regulator of biofilm formation is the second messenger cyclic dimeric guanosine monophosphate (c-di-GMP). Present in about 85% of bacteria, c-di-GMP is synthesized by diguanylate cyclases (DGCs), which typically contain a conserved GGDEF motif, and is degraded by phosphodiesterases, which contain a conserved EAL or HD-GYP motif ( 9 ). Generally, high levels of c-di-GMP increase biofilm formation and decrease motility, while low levels of c-di-GMP exert the opposite effect ( 10 ). Along with biofilm formation and motility, c-di-GMP also regulates a diverse array of phenotypes including quorum sensing, virulence, cell-cycle control, secretion, bacterial predation and stress responses ( 10 ). Although c-di-GMP has been extensively studied since its discovery in 1987 ( 11 ) and many groups have studied the mechanisms by which c-di-GMP interacts with effectors ( 12–19 ), mechanism(s) by which c-di-GMP might be needed to directly modulate RNA polymerase (RNAP) in transcription have not been elucidated. Catalyzing transcription is the multi-subunit enzyme RNAP. Bacterial RNAP is an ∼500 kDa enzyme comprised of two large subunits (beta and beta’), two alpha subunits, one omega subunit and a promoter specificity factor, σ ( 20 ). Although the primary σ, such as σ70 in Escherichia coli , is used for the expression of most genes during exponential growth, alternate σ factors, which are either related to σ70 or belong to the σ54 family, are used under other growth conditions or times of stress ( 20 ). The first step in transcription is initiation, a multi-step process that can be controlled by various regulators. During transcription initiation with σ70-RNAP, polymerase first binds to double-stranded DNA elements in the −10 and −35 regions, forming closed complex that is typically unstable ( 21–23 ). Isomerization to the open complex proceeds rapidly and requires unwinding and bending of the DNA, major conformational changes within RNAP, and formation of the transcription bubble from −11 to ∼+3 ( 21 ). Upon addition of ribonucleoside triphosphates (rNTPs), the complex transitions to the initiating complex where small abortive RNAs are synthesized and released prior to promoter clearance ( 21 ). While RNAP catalyzes transcription efficiently at promoters with optimal −35 and −10 consensus sequences, activators are typically needed to regulate promoters with suboptimal sequences. Some activators additionally use second messenger molecules such as cyclic adenosine monophosphate, guanosine pentaphosphate or c-di-GMP to modulate gene expression ( 24 ). In Vibrio cholerae , an important pathogen that causes the acute diarrhea disease cholera and uses biofilms to aid in environmental transmission, survival and pathogenesis, VpsR is the master regulator that activates biofilm gene transcription in vivo in the presence of high levels of c-di-GMP and also binds c-di-GMP with a K d(app) of 1.6 μM in vitro ( 25–31 ). VpsR is known to activate promoters for vpsL and vpsT , genes within the biofilm biosynthesis operons. Furthermore, VpsR also directly activates expression of other phenotypes in response to c-di-GMP such as acetoin biosynthesis, the transcription factor tfoY and the eps operon encoding the type II secretion system ( 28 , 32 , 33 ), suggesting that this transcription factor is the hub for a central network of c-di-GMP transcriptional control in V. cholerae . However, despite the abundance of evidence showing the positive regulatory role of VpsR and c-di-GMP in activating gene expression in vivo , previous work has not recapitulated this result in vitro . Based on amino acid sequence homology, VpsR has been classified as an atypical enhancer binding protein (EBP) ( 28 , 31 ). Classic EBPs utilize σ54 to activate transcription and are comprised of three conserved domains: an N-terminal receiver (REC) domain, a central AAA+ domain (Adenosine triphosphatase (ATPase) associated with diverse cellular activities) involved in ATP hydrolysis and binding to σ54 and a C-terminal helix-turn-helix DNA-binding domain ( 34 ). Although VpsR has overall homology to EBPs, several residues known to be required for specific EBP functions are not conserved. Not only does VpsR lack the GAFTGA motif involved in binding to σ54, but the highly conserved aspartate (D) and glutamate (E) residues in the Walker B domain involved in ATP hydrolysis are asparagine (N) and aspartate (D) residues in VpsR ( Supplementary Figure S1 ). Furthermore, microarray analyses demonstrate that transcription from promoters known to be regulated by VpsR does not change in a σ54 ( rpoN-) mutant ( 30 ), and sequence analyses indicate that the VpsR-activated promoters do not contain the well-conserved −24 GG and −12 GC consensus sequences utilized by σ54-RNAP. Instead, some of these promoters have reasonable matches to the consensus −10 element of promoters dependent on a primary sigma factor, such as σ70. Here we have developed an in vitro transcription system demonstrating activated transcription from the VpsR-activated promoter for the vpsL gene (P vpsL ) in the presence of VpsR, c-di-GMP and σ70-RNAP. We have used DNase I and KMnO 4 footprinting to characterize the protein–DNA complex made by σ70-RNAP alone with P vpsL versus complexes made by σ70-RNAP with VpsR and/or c-di-GMP. Surprisingly, we find that c-di-GMP together with VpsR is needed to generate the correct protein–DNA interactions required for an active transcription complex with σ70-RNAP. Our results provide a new paradigm in c-di-GMP-dependent transcription activation.",
"discussion": "DISCUSSION Biofilm formation by bacteria imposes an enormous medical cost, both in suffering and in the price of treatment. Consequently, understanding the regulation of biofilm formation is crucial to the prevention and treatment of bacterial disease. A central player in biofilm formation is the second messenger c-di-GMP, which has previously been shown to be required for the activity of several transcriptional activators including VpsR, the master regulator of biofilm formation in V. cholerae . By developing the first in vitro transcription assay with c-di-GMP, we have demonstrated that c-di-GMP works with VpsR in a novel way to stimulate transcription by RNAP at P vpsL , a promoter for biofilm biogenesis genes. Surprisingly, unlike other characterized regulators that use c-di-GMP, such as Klebsiella pneumoniae MrkH, Mycobacterium smegmatis LtmA, Streptomyces coelicolor BldD, V. cholerae VpsT and Pseudomonas aeruginosa FleQ and BrlR ( 12–19 ), VpsR does not require c-di-GMP to oligomerize or bind to the DNA. VpsR dimers form with or without c-di-GMP, and the presence of the second messenger does not substantially affect the affinity of VpsR for the DNA or the protein–DNA contacts made by VpsR alone at P vpsL . Instead, c-di-GMP is needed to observe distinct protein–DNA contacts within the activated transcription complex of σ70-RNAP/VpsR/c-di-GMP. How the presence of c-di-GMP results in these contacts is not clear. However, it could be needed to generate a particular VpsR conformation that is active for transcription and/or by promoting needed contacts between VpsR and σ70-RNAP. In fact, the position of the VpsR binding site immediately upstream of the −35 region suggests that VpsR should function as a Class II activator that can interact with σ70 region 4 and/or alpha CTDs. Besides the novelty of activation, VpsR is also unusual as an atypical EBP. Classic EBPs interact with σ54-RNAP at a promoter, utilizing ATPase to form homomeric hexamers to generate the energy needed to form a stable open complex ( 47 , 48 ). However, VpsR, like other atypical EBPs, lacks the GAFTGA motif needed for interaction with σ54-RNAP and has non-conserved amino acids in the Walker B motif involved in ATP hydrolysis. Atypical EBPs that utilize σ70 rather than σ54 may represent an evolutionary link between these two very different σ class families. To date, five atypical EBPs have been characterized: E. coli TyrR, Rhodobacter capsulatus HupR, Myxococcus xanthus HsfA, Pseudomonas putida PhhR and Brucella abortus NtrX ( 49–54 ). While all five atypical EBPs contain variations in the GAFTGA motif responsible for binding to σ54, some contain non-consensus Walker A or Walker B motifs involved in ATP binding and hydrolysis ( 55 ). Recently, the crystal structure of B. abortus NtrX was solved, representing the first full-length crystal structure of a NtrC-like response regulator as well as the first full-length crystal structure of an atypical EBP. However, unlike VpsR, NtrX functions as a repressor at the pYX promoter and does not bind c-di-GMP ( 54 ). Thus, it appears that atypical EBPs may function by varied mechanisms. Nevertheless, the remaining four atypical EBPs work with σ70-RNAP in the absence of c-di-GMP to activate transcription. How the activity of these non-canonical EBPs is regulated remains to be determined for most of these transcription factors, but we show here that VpsR represents the first EBP and first atypical EBP that is dependent on a second messenger to directly activate transcription with RNAP. In addition to VpsR, two other EBPs, FlrA in V. cholerae and FleQ from P. aeruginosa , are also directly controlled by c-di-GMP. However, unlike VpsR, these regulators are typical EBPs and contain conserved elements needed for σ54-dependent transcription. While binding of c-di-GMP to FlrA inhibits its ability to bind to the flrBC promoter to promote transcription activation ( 56 ), binding of c-di-GMP to FleQ has more complex effects. FleQ can regulate transcription at promoters containing σ54 or σ70 elements in P. aeruginosa , but it is unclear whether FleQ directly activates transcription with these sigma factors in vitro . Like FlrA, binding of c-di-GMP to FleQ represses flagellar genes in P. aeruginosa , but also derepresses and activates the pel biofilm extracellular polysaccharide gene cluster in vivo ( 14 , 57 , 58 ). Thus, VpsR, FlrA and FleQ appear to function on a continuum with each transcription factor having different dependencies on σ54 or σ70 as well as different responses to c-di-GMP. While FlrA and FleQ bind c-di-GMP via conserved arginine residues that flank a central cavity between the N-terminal receiver domain and central AAA+ domain ( 14 ), VpsR lacks these arginines, instead having a methionine and glutamate at those positions. The mechanism by which VpsR binds to c-di-GMP is therefore unknown. Along with the proximal VpsR binding site from −31 to −53 at P vpsL , interestingly, a second VpsR binding site lies far upstream of P vpsL at −297 to −336. These binding sites differ in both sequence, length and protection intensities. Using DNase I footprinting with VpsR alone in the absence of c-di-GMP, the protection pattern was stronger at the distal site versus the proximal site ( 31 ). While VpsR protected the sequence TTTCTCAAAAATAATTCAATGTAAATCCAAAATGTAATAC at the distal site, VpsR protected the sequence AGTCTTAGAATTGATGCAGATA at the proximal site ( 31 ). Although this distal site has no effect in our in vitro transcription assays with purified proteins as well as no effect in transcriptional fusion studies when truncated, it appears that VpsR binding here is needed to relieve H-NS repression in vivo ( 31 ). The downstream portion of the distal VpsR binding site overlaps the first distal H-NS binding site ( 45 ). Thus, we speculate that at P vpsL , VpsR acts as an anti-H-NS repressor, blocking H-NS binding at the distal promoter site. In between the proximal and distal VpsR binding sites, a VpsT binding site is present from −238 to −192. Previous work demonstrates that VpsT acts solely as an antirepressor of H-NS at P vpsL and in vitro transcription studies in our laboratory show that VpsT does not directly activate transcription at P vpsL (data not shown). This allows for additional H-NS regulation in which both VpsR-binding to the distal promoter site and VpsT-binding downstream together help prevent H-NS from first binding the site overlapping the distal VpsR binding site. Upon freeing the DNA from H-NS binding, VpsR/c-di-GMP may then bind to the proximal binding site to directly activate transcription with RNAP. Other VpsR sites appear at various locations relative to the TSS of various genes. VpsR binds and regulates vpsT with a site at −149 to −119, aphA with a site at −88 to −70, and epsC with a site from −50 to −33 ( 28 , 32 , 59 ), and in silico analyses have identified conserved VpsR boxes present at other locations, including promoters for rbmA, rbmB, rbmC, rbmE, vpsU, vpsR, cdgC and bap1 ( 31 ). H-NS sites have also been identified at some of these promoters ( vpsL, vpsT, rbmA, rbmB and rbmC ( 45 , 60 , 61 )). Thus, we speculate that in general, promoter distal VpsR binding sites may correlate with a role in relieving H-NS repression, while promoter proximal sites may correlate with VpsR/c-di-GMP activation with RNAP. Such a mechanism may be similar to that used by Salmonella typhimurium SsrB. During biofilm formation, SsrB binds the DNA and displaces H-NS to relieve H-NS silencing and enable transcription activation of csgD , the master regulator of biofilms ( 62 ). However, at promoters of Salmonella Pathogenicity Island-2 SPI-2 genes, SsrB interacts with RNAP to activate transcription ( 63 ). The role of VpsR’s diverse and numerous binding sites remain unclear and future studies in determining the differing roles of VpsR in transcriptional activation versus relieving H-NS repression are in progress."
} | 4,022 |
31101818 | PMC6525182 | pmc | 8,121 | {
"abstract": "The root economics spectrum (RES), a common hypothesis postulating a tradeoff between resource acquisition and conservation traits, is being challenged by conflicting relationships between root diameter, tissue density (RTD) and root nitrogen concentration (RN). Here, we analyze a global trait dataset of absorptive roots for over 800 plant species. For woody species (but not for non-woody species), we find nonlinear relationships between root diameter and RTD and RN, which stem from the allometric relationship between stele and cortical tissues. These nonlinear relationships explain how sampling bias from different ends of the nonlinear curves can result in conflicting trait relationships. Further, the shape of the relationships varies depending on evolutionary context and mycorrhizal affiliation. Importantly, the observed nonlinear trait relationships do not support the RES predictions. Allometry-based nonlinearity of root trait relationships improves our understanding of the ecology, physiology and evolution of absorptive roots.",
"introduction": "Introduction Root foraging is essential for plant growth and ecosystem functioning. In most plants, the most distal and ephemeral portion of the root systems, referred to as absorptive roots, undertake this function 1 , 2 . Substantial interspecific trait variation among these absorptive roots has been reported for a variety of ecosystems and plant species pools 3 . One common hypothesis explaining this variation is that roots follow a leading dimension which reflects the acquisition-conservation tradeoff, i.e., the root economics spectrum (RES) 4 , 5 . Under the RES hypothesis, roots should follow a gradient in trait syndromes from fast foraging and short lifespan (i.e., acquisitive strategy) to slow foraging and long lifespan (i.e., conservative strategy). At global scales, the RES gradient has been used to understand root tissue function and in explaining responses of ecosystem carbon and nutrient cycling to climate change 6 , 7 . However, recent studies have found mixed support for some of the relationships predicted by the RES hypothesis. For instance, root tissue density (RTD), a trait frequently used as a key RES trait, should be positively correlated with root lifespan 8 , 9 and negatively correlated with root nitrogen concentration (RN), a proxy for nutrient acquisition rate 10 . Root diameter is another key trait depicting resource conservation and consistently shows a positive correlation with root lifespan 11 , 12 . Then, under the RES hypothesis, we would expect a positive correlation between root diameter and RTD and a negative correlation between root diameter and RN 11 , 13 . However, several studies have reported either no or a rather weak relationship (i.e., uncorrelated traits) 14 – 16 , or even a significant negative relationship between root diameter and RTD and/or a positive relationship between root diameter and RN (i.e., correlated trait relationships) 17 , 18 . Both of these cases contradict predictions under the RES hypothesis. The relatively small species pools and/or the restricted geographic ranges considered in most previous studies limit the range of trait variation included, which could mask more universal trends. It is therefore important to test these trait relationships using a larger and global dataset 19 , 20 . Another possible reason for the contrasting findings may be that the trait relationships depart from the expected linear relationships assumed for the RES. Although nonlinear relationships prevail in biological processes due to the relationship between surface area and volume in functional organs 21 , 22 , they have not been well recognized in plant roots. The two anatomical components of absorptive roots, namely, the stele tissue and the tissues outside the stele (ToS, including the epidermis, exodermis, and cortex), follow an allometric relationship; i.e., the thickness of the ToS (tToS) increases at a faster rate than the stele radius does from thin to thick absorptive roots 18 , 23 , 24 . As such, a nonlinear relationship exists between the proportion of root cross-sectional area occupied by the stele (PRS) and root diameter ( x ): PRS = (1–2k-2c x −1 ) 2 , where k and c are parameters for the relationship between tToS and root diameter (i.e., tToS = k x + c, c < 0) 18 . Because the stele consists of lignified vascular tissue, it should be denser and have lower N-concentrations than the ToS; as such, the PRS should theoretically be positively correlated with RTD and negatively with RN 25 , 26 . Therefore, based on the above allometric relationship, we would expect a nonlinear negative relationship between RTD and root diameter, and a nonlinear positive relationship between RN and root diameter. In addition to the RES, mycorrhizal affiliation is also an important factor shaping root systems and hence affecting root trait relationships. This is because different mycorrhizas (e.g., arbuscular (AM) versus ectomycorrhizal (EM) fungi) are typically associated with particular root morphologies and nutrient contents that are adapted to specific environmental conditions 14 , 15 , 27 – 29 . The mantle hyphae in EM species usually have low tissue density and have little correlation with RTD 16 , and therefore cannot explain the observed differences between EM and AM species. Instead, EM species typically dominate in nutrient-poor soils 28 , which may lead to thicker and/or more intensely lignified root cell walls 30 . This, in turn, could potentially explain the higher RTD and lower RN in EM than in AM species 15 , 17 , 31 , 32 . In addition, we predict that the morphological modifications in cortex and/or stele tissues associated with the switch in mycorrhizal partnership would make inter-trait relationships for EM roots deviate from those predicted by the above-mentioned allometric relationship, and by that contribute to the observed variation in RES trait relationships. Additionally, studies on non-woody species tend to report stronger RES tradeoffs between root traits than studies on woody plants (e.g., Roumet et al. 33 for non-woody plants; Holdaway et al 17 . and Kong et al 18 . for woody plants). However, few studies have compared the two groups of species in the same context 30 with the same suit of root traits, making generalizations about the RES difficult. Testing relationships among RES traits across mycorrhizal types and between growth forms (i.e., woody and non-woody species) is thus instrumental for understanding plant strategies in resource acquisition and conservation as well as plant adaptation to different environments. Here, we test the following two hypotheses: (1) Based on the allometric relationship between stele and cortical tissue in roots, relationships between RTD and RN, and root diameter should be nonlinear, and consequently do not follow the predictions based on the RES. More specifically, we expect similar nonlinear root trait relationships between woody and non-woody species as they both follow an allometric relationship between root stele and cortex 23 . (2) Nonlinear root trait relationships are weaker for EM than for AM plants as the harsher environments where EM plants grow would cause greater variation of RTD and RN by thickening and/or lignification of root cell walls. Testing nonlinear root trait relationships advances our understanding of the hypothesized RES, and could potentially reconcile the debate on this topic. Here, using a global root trait dataset over 800 species, we find significant nonlinear relationships in woody but not in non-woody species between root diameter, and RTD and RN. Nonlinearity of the root trait relationships is attributed to the allometric relationship between root stele and cortical tissues and can explain how sampling bias from different ends of the nonlinear curves results in conflicting trait relationships observed in previous studies. Furthermore, the nonlinear relationships vary depending on evolutionary context and mycorrhizal affiliation, and do not support the RES predictions. Together, the allometry-based nonlinearity of root trait relationships greatly advances our understanding of the ecology, physiology and evolution of absorptive roots.",
"discussion": "Discussion Our global analysis of key root traits partially supports our first hypothesis of nonlinear relationships of RTD and RN with root diameter in woody (but not non-woody) species (Fig. 2 , Supplementary Fig. 2 ). In woody species, the nonlinear relationships were similar or stronger in EM and ERM species that often exist in harsher environments than AM species; 28 , 34 this is inconsistent with our second hypothesis. This suggests that harsh environments may not necessarily exert a strong influence on cell wall thickening for EM and ERM roots in woody species. It is possible that the reduction of cortical tissue and evolutionary divergence of EM and ERM from their AM ancestors 27 , 35 – 37 (e.g., enzymes associated with these mycorrhizas for decomposition of plant litter or soil organic matter; the efficiency of carbon and nutrient interchange between fungi and roots in the symbioses) may enable EM and ERM species to adapt to harsher environments and conserve nonlinear trait relationships in EM and ERM roots. This, however, warrants further investigation. Interestingly, for woody species we found a negative relationship between RN and root diameter in EM species, while the relationship was positive in AM and ERM species (Fig. 2d ). The negative relationship in EM species could possibly be explained by two typical features of nutrient acquisition in EM species. First, for EM species, thin absorptive roots are covered by a relatively thick EM fungal mantle 16 , which is relatively rich in N; 38 this thus enhances the root N concentration of thin roots compared to thick roots. This is notably different from AM species where thicker absorptive roots are usually associated with greater mycorrhizal colonization 18 , 24 , 39 . Second, EM species with thicker absorptive roots usually have less hyphal foraging precision (i.e., proliferation of extraradical hyphae in resource-rich patches) 40 , which can reduce nutrient uptake and hence lower RN in thicker EM roots. The nonlinear relationships in woody species can reconcile the current debate on the relationship between RTD and root diameter. We found weaker correlations of RTD and RN with root diameter for studies reporting no relationship between RTD and root diameter than for studies reporting negative relationships between RTD and root diameter (Fig. 4 ). The studies reporting negative relationships also included a higher proportion of species with thin roots and high RTD than studies reporting no relationships. Together, this demonstrates that those studies reporting no relationships focus on the region of slow decrease of RTD with increasing root diameter (Fig. 2c , Supplementary Fig. 2a ). On the other hand, the negative relationship between RTD and root diameter in studies reporting negative relationships may apply only to the part of the curve with a steep decrease. Therefore, nonlinearity of the root trait relationships could underpin how sampling bias from different parts of the nonlinear curves produces contradicting results as shown in recent studies. To gain a global picture of root trait relationships, it is therefore crucial to consider the full global range of trait variation across different lineages of woody species. Recognition of the nonlinear relationship between RTD and root diameter could substantially improve our understanding of the tradeoffs among root functional traits. Theoretically, for an individual absorptive root (e.g., a single 1st order root), greater investment in dry mass could result in longer root lifespan following the cost-benefit theory 41 , 42 as observed for aboveground plant organs 19 , 22 . If we consider a plant root a cylinder formed by concentrically arranged tissues, dry mass of a single 1 st order root must be a function of the total diameter as root volume increases exponentially with diameter (Supplementary Fig. 4 ). For the nonlinear relationship between RTD and root diameter (Fig. 2a , Supplementary 2c), if the increase of the root dry mass with increasing root diameter cannot be offset by the simultaneous decrease of tissue density, then root dry mass will always increase with root diameter. A modeling simulation based on the allometric relationship between root conductive and cortical tissue shows a monotonical increase of the root dry mass with increasing root diameter (Supplementary Fig. 4 ), suggesting a predominant role of root diameter rather than RTD in determining the root dry mass and hence root lifespan 22 . This is also supported by the consistent positive relationship between root lifespan and root diameter 12 , 43 and the lack of a relationship between root lifespan and RTD in woody species (Supplementary Fig. 5 ). Furthermore, for AM species, root nutrient foraging activity may increase with increasing root diameter because of more resource allocation to non-cell wall fractions in the cortex (Supplementary Fig. 6 ), offsetting the relatively small changes in diameter of the lignified tissue in the stele (Fig. 1a ) 18 , 24 , and greater mycorrhizal colonization for thicker roots 12 , 27 . The higher nutrient foraging activity with increasing root diameter may have evolved to compensate for inefficient proliferation of thicker AM roots in resource rich patches 40 , 44 – 46 . Together, except for the negative relationship between root diameter and RN in EM species, the nonlinear trait relationships as revealed here suggest that root trait relationships do not necessarily align with the RES hypothesis. Therefore, the relative independence between changes in cortical and stele tissues in roots 24 indicates alternative acquisition strategies in plants mediated by their interaction with symbiotic fungi and further supports the multiple dimensionality in root trait syndromes proposed elsewhere 11 . Furthermore, the nonlinear relationship between root diameter and RTD advances our understanding of another key trait underlying the RES, i.e., specific root length (SRL, root length per unit root mass) 11 , 47 . Assuming that roots are cylindrically shaped, SRL can be expressed as: SRL = 4/(π × RTD × root diameter 2 ) 17 , 48 . If RTD is positively correlated with root diameter, as predicted by the RES, SRL then mathematically scales negatively with RTD. However, for the region of the nonlinear curve where RTD slowly decreases with root diameter (Fig. 2c ), the negative effect of root diameter on SRL could counteract a potential positive effect of RTD on SRL, which, in turn, would lead to a positive relationship of SRL with RTD. In contrast, for the region of the nonlinear curve with fast decrease of RTD (Fig. 2c ), SRL may show no relationship with RTD. This is because with increasing root diameter, the negative effect of root diameter on SRL could be offset by the potential positive effect of RTD on SRL. Together, the nonlinear relationship between RTD and root diameter could explain an overall weak correlation of SRL with RTD, and also with RN (Supplementary Fig. 7a, b ) 11 , 14 , 15 , 49 across the whole region of the nonlinear curve. Moreover, the weak correlation between SRL and RN and the strong coupling of SRL with root diameter 12 , 14 , 15 , 50 (also see Supplementary Fig. 7c ) could also explain the relative weak correlation between root diameter and RN (Fig. 2 ). Together, these results illustrate how nonlinear root trait relationships can explain why SRL does not necessarily conform with the RTD-related plant economics spectrum in woody species 15 , 49 . Our results also suggest a phylogenetic component in the nonlinear root trait relationships, at least for woody species. Compared with the leveling off of RTD for thick roots in the above nonlinear relationships (Fig. 2 ), RTD decreases and RN increases continuously for thick roots even when excluding the influence of plant phylogeny (Supplementary Fig. 1c, d ). The thick roots belong to early-derived angiosperms (e.g., Magnoliids, Fig. 3 ) associated with phosphorus-limited tropical soils, which suggests specialization of this root group to high dependence on AM fungi for nutrient foraging 12 , 25 , 29 , 51 . The weaker phylogenetic conservatism of RTD than root diameter (Table 1 ) 18 , 52 could probably be explained by specialization of early-derived angiosperm trees to phosphorus-limited soils by maximizing the cortex area for AM colonization, which would lead to low RTD and high RN. Later, during the evolution of novel angiosperm groups, natural selection promoted finer roots, either to constrain mycorrhizal colonization 12 , 18 or to optimize water conductivity and plant photosynthetic efficiency 23 , 29 . However, more research is needed to better understanding the different evolutionary mechanisms driving the transformation in root systems. Different from woody species, we find no or rather weak nonlinear relationships between RTD, RN and root diameter in non-woody species, although both groups follow the same allometric relationships between stele and cortical tissue in absorptive roots. The allometric relationship has been proposed to optimize the balance between nutrient absorption via the cortex and transportation via conduits of the steles 23 . Compared with absorptive roots of woody species at a given diameter, non-woody species are reported to have about 30% less mycorrhizal colonization 12 while having a higher proportion of root cortex ( t -test, p < 0.01) and thus lower RTD. This higher proportion of cortex in non-woody species might be associated with foraging strategies other than mycorrhizal colonization (e.g., metabolic activity). Therefore, in fertile soils, absorptive roots of non-woody species may be less dense and more active than absorptive roots of woody species 53 (Supplementary Fig. 6 ), and have more root hairs 54 and/or root branching 55 . Together, this might offset the lower nutrient acquisition through mycorrhizal associations in non-woody species. In contrast, in infertile soils, roots of woody species may not be much denser than non-woody species because higher RTD would reduce mycorrhizal colonization 15 , 16 , 18 , 27 , 56 . However, in infertile soils, roots of non-woody species could be denser 53 relative to woody species because of lower dependence on mycorrhizal colonization for non-woody than for woody species 12 . These speculations could partially explain why roots of non-woody species show greater variation of RTD and RN (and hence weak nonlinear root trait relationships) compared to woody species. Another reason for lack of nonlinear trait relationships in non-woody species may be that roots <2 mm in diameter include some non-absorptive roots 57 which typically have larger proportion of stele than absorptive roots 2 , and as such, confound root trait relationships. In contrast, absorptive roots of woody species in previous studies (Supplementary Data 1 ) are sampled based on root branching order which can track the absorptive roots more precisely than the diameter-based method 1 . We therefore recommend for future studies, when possible, to select absorptive roots based on branching order 1 rather than on root diameter. In conclusion, our study demonstrates global nonlinear relationships of RTD and RN with root diameter among different mycorrhizal types of woody species but not for non-woody species. The differences between woody and non-woody species reveal insights into the ecological and evolutionary drivers of root structure in different plant life forms 58 . The nonlinear root trait relationships, a likely outcome of evolutionary constraints, could explain conflicting results among recent studies on the relationships of root diameter with RTD and RN. Interestingly, EM species show a different RN-root diameter relationship from that found in AM and ERM species, probably because EM species have a thinner fungal mantle and less hyphal foraging precision in thicker absorptive roots. Furthermore, our analyses show that the hypothesized RES 11 is not supported for absorptive roots of woody species, except for EM trees showing partial support of the RES. We advocate that the paradigm of nonlinearity for relationships between root diameter, RTD and RN provides a more rhizocentric way of viewing absorptive root ecological and physiological strategies."
} | 5,144 |
24372841 | null | s2 | 8,122 | {
"abstract": "Quorum sensing (QS) is a process of bacterial cell-cell communication that relies on the production, detection and population-wide response to extracellular signal molecules called autoinducers. The QS system commonly found in vibrios and photobacteria consists of the CqsA synthase/CqsS receptor pair. Vibrio cholerae CqsA/S synthesizes and detects (S)-3-hydroxytridecan-4-one (C10-CAI-1), whereas Vibrio harveyi produces and detects a distinct but similar molecule, (Z)-3-aminoundec-2-en-4-one (Ea-C8-CAI-1). To understand the signalling properties of the larger family of CqsA-CqsS pairs, here, we characterize the Photobacterium angustum CqsA/S system. Many photobacterial cqsA genes harbour a conserved frameshift mutation that abolishes CAI-1 production. By contrast, their cqsS genes are intact. Correcting the P. angustum cqsA reading frame restores production of a mixture of CAI-1 moieties, including C8-CAI-1, C10-CAI-1, Ea-C8-CAI-1 and Ea-C10-CAI-1. This signal production profile matches the P. angustum CqsS receptor ligand-detection capability. The receptor exhibits a preference for molecules with 10-carbon tails, and the CqsS Ser(168) residue governs this preference. P. angustum can overcome the cqsA frameshift to produce CAI-1 under particular limiting growth conditions presumably through a ribosome slippage mechanism. Thus, we propose that P. angustum uses CAI-1 signalling for adaptation to stressful environments."
} | 359 |
28872878 | null | s2 | 8,125 | {
"abstract": "Iron-sulfur proteins play essential roles in various biological processes. Their electronic structure and vibrational dynamics are key to their rich chemistry but nontrivial to unravel. Here, the first ultrafast transient absorption and impulsive coherent vibrational spectroscopic (ICVS) studies on 2Fe-2S clusters in Rhodobacter capsulatus ferreodoxin VI are characterized. Photoexcitation initiated populations on multiple excited electronic states that evolve into each other in a long-lived charge-transfer state. This suggests a potential light-induced electron-transfer pathway as well as the possibility of using iron-sulfur proteins as photosensitizers for light-dependent enzymes. A tyrosine chain near the active site suggests potential hole-transfer pathways and affirms this electron-transfer pathway. The ICVS data revealed vibrational bands at 417 and 484 cm"
} | 218 |
31520074 | PMC6744558 | pmc | 8,126 | {
"abstract": "Diazotrophic bacteria are an attractive biological alternative to synthetic nitrogen fertilizers due to their remarkable capacity to fix atmospheric nitrogen gas to ammonium via nitrogenase enzymes. However, how diazotrophic bacteria tailor central carbon catabolism to accommodate the energy requirement for nitrogenase activity is largely unknown. In this study, we used Azotobacter vinelandii DJ and an ammonium excreting mutant, AV3 (ΔNifL), to investigate central carbon metabolism fluxes and central cell bioenergetics in response to ammonium availability and nitrogenase activity. Enabled by the powerful and reliable methodology of 13 C-metabolic flux analysis, we show that the respiratory TCA cycle is upregulated in association with increased nitrogenase activity and causes a monotonic decrease in specific growth rate. Whereas the activity of the glycolytic Entner–Doudoroff pathway is positively correlated with the cell growth rate. These new observations are formulated into a 13 C-metabolic flux model which further improves the understanding and interpretation of intracellular bioenergetics. This analysis leads to the conclusion that, under aerobic conditions, respiratory TCA metabolism is responsible for the supply of additional ATP and reducing equivalents required for elevated nitrogenase activity. This study provides a quantitative relationship between central carbon and nitrogen metabolism in an aerobic diazotroph for the first time.",
"introduction": "Introduction Reduced forms of nitrogen are required by every living organism and are used to make many important biological components including nucleic acids, proteins, pigments, energy carrier molecules, etc. In nature, a diverse group of bacteria known as diazotrophs have a remarkable capacity to fix atmospheric nitrogen to ammonium under ambient conditions. This capacity is catalyzed by the nitrogenase metalloenzyme complexed with accessory proteins for proper cofactor biosynthesis and can be exploited for biological fertilizer production. This process is accomplished on an industrial scale by the chemical process (Haber-Bosch) that requires elevated temperature, high pressure and special catalysts and is considered an energy intensive and major greenhouse gas emitting approach 1 . The ability of diazotrophs to use dinitrogen gas as the sole nitrogen source confers many ecological merits, but also incurs physiological constraints resulting from the high energy requirements of biological nitrogen fixation. The function of the nitrogenase enzyme requires not only reducing equivalents but also the supply of a minimum of 16 ATP per N 2 fixed. Substantial energetic equivalents require a coordinated central carbon metabolism which uses a series of enzymatic pathways ( i.e . the Embden-Meyerhof-Parnas (EMP) pathway, the Entner-Doudoroff (ED) pathway, pentose phosphate pathway, tricarboxylic acid (TCA) cycle etc.) to convert organic carbohydrates into metabolic precursors and release electrons and ATP. However, to date, there is little understanding of how diazotrophic bacteria quantitatively tailor central carbon catabolism to nitrogen availability and vice versa. In addition to its substantial energy cost, biological nitrogen fixation is also highly oxygen sensitive. To protect the nitrogenase complex from damage, some aerobic diazotrophs have evolved the ability to form specialized cells that create a microanaerobic environment for nitrogen fixation to occur ( e.g . heterocysts in nitrogen-fixing filamentous cyanobacteria). Alternatively, the non-compartmentalized diazotroph, Azotobacter vinelandii , is believed to have a different protection mechanism 2 – 4 that exhibits high respiratory activity, especially when exposed to high oxygen concentrations. In addition, in environments where a high rate of respiration does not prevail ( e.g. A. vinelandii grown in phosphate-limited nitrogen-free chemostat culture), cells produce extracellular alginate, a viscous polysaccharide that leads to the formation of a capsule surrounding the cell that prevents oxygen diffusion into the cell 5 . In order to adapt to different environmental conditions while accommodating nitrogenase activity and ensuring ammonium availability, intracellular carbon flux may need to be directed toward either respiratory metabolism or alginate biosynthesis. Azotobacter is an attractive organism for biofertilizer applications because this species is capable of fixing atmospheric nitrogen under ambient conditions, is genetically tractable, and has been shown to excrete excess fixed ammonium 6 – 10 . For example, mutations in the nifL regulatory domain of the nitrogen fixation operon in A. vinelandii has yielded a mutant strain (AV3) that exhibits constant expression of nitrogenase, and thus increased ammonium production and excretion into the surrounding media 8 . However, this mutant exhibits metabolic mechanisms of nutrient balancing that could favor biomass production and may thus oppose the metabolic engineer’s goal of maximizing ammonia yield. Therefore, understanding how A. vinelandii coordinates the utilization of carbon with the rate of nitrogen fixation is critical for the successful reprogramming of this microbe’s metabolism. Therefore, we aim here to understand how ammonium excretion is adding a metabolic energetic burden to the cells’ metabolism. Using 13 C-metabolic flux analysis, by coupling chromatography to mass spectrometry we are able to quantify the isotopomer patterns of metabolites throughout the metabolic network. This method has emerged as a powerful tool for generating the quantitative data needed to probe and model central carbon metabolism and is uniquely applicable to provide novel bioenergetic insights into carbon and nitrogen metabolism 11 , 12 . The primary goal of this work is to understand quantitative carbon catabolism tailored to nitrogen availability and in particular in relation to mutations that yield high levels of nitrogen excretion. In this work, we present a quantitative fluxome analysis showing how central carbon metabolism is reprogramed in relation to nitrogen perturbation in diazotroph A. vinelandii DJ wild type (wt) and its ammonium-excreting strain, AV3 (ΔNifL) 8 . To our knowledge, this is the first study to quantify the relationship between central carbon and nitrogen metabolism in this model aerobic diazotroph.",
"discussion": "Discussion Using 13 C-tracer studies, we developed a fluxomic model to formulate the quantitative relationship between central carbon fluxes and nitrogen metabolism in A. vinelandii and elucidated the integrated responses of metabolic networks to nitrogen perturbation. Using this fluxomic model framework we were able to probe the bioenergetic basis of a diazotrophic phenotype in the ammonium-excreting AV3 mutant, which allows further refinement of the model to guide strategies toward metabolic engineering goals. Our study sheds light on the glycolytic strategy used by diazotroph A. vinelandii , which carries complete gene sets for two critical glycolytic options, the EMP and ED pathways. This work shows that A. vinelandii predominantly utilizes the ED pathway, while the EMP pathway has very low activity. Similar glycolytic flux partitioning is also observed in Pseudomonas 17 , 18 , a genus phylogenetically close to Azotobacter , in which the ED pathway accounts for over 90% of utilized glucose 19 , 20 . These two glycolytic pathways vary in reaction schemes and in how much ATP they produce for each glucose molecule metabolized 21 . Given the substantial energetic requirements for diazotrophic growth, why A. vinelandii prioritizes the ED pathway for glycolysis represents an intriguing open question. Compared with the EMP pathway, the most energetically efficient glycolytic pathway, the ED pathway oxidizes phosphorylated glucose to 2-keto-3-deoxy-6-phosphogluconate (KDPG), which is cleaved into one pyruvate and one glyceraldehyde-3-phosphate (G3P). Only the latter product supports substrate-level phosphorylation and can be used to produce ATP through subsequent glycolysis. Despite reduced ATP production, the ED pathway contains more exergonic reactions 22 and is less thermodynamically constrained. This feature leads to tremendous benefit in enzyme kinetics as a stronger thermodynamic driving force will result in forward reactions being favored, which accordingly requires reduced amounts of catalytic enzymes to generate identical net flux. Indeed, the ED pathway could reduce by several-fold the enzymatic protein synthesis burden but still achieve the same glucose conversion rate as the EMP pathway 21 . It should be noted that in diazotrophic growth, the cost for protein synthesis can be considerable as it is largely based on the energetically expensive nitrogen-fixing process. From this perspective, natural selection of the ED pathway represents an energy balance consideration geared towards higher conversion rates of carbon substrates per N 2 fixed and constrained by protein synthesis demands. The trade-off of this strategy is the decreased production of ATP from glycolysis, which must be replenished through another oxidative pathway as discussed below. Interestingly, our data also showed that the flux ratio of the ED pathway is positively correlated with the cell growth rate constraints by either ammonium availability or nitrogenase activity. The biological mechanism behind this correlation is still unknown. One hypothesis is that the activities of the ED pathway enzymes could be regulated by altered intracellular ammonium levels regardless of transcriptomic, proteomic, or metabolomic levels. Further research in systems biology is required to address this question comprehensively. In addition, our 13 C-fluxomic study also provides new evidence to better understand the role of respiratory metabolism in diazotrophs. Respiratory metabolism was proposed to protect the active nitrogenase against oxygen because the respiratory electron transport system bound to the peripheral cytoplasmic membrane can scavenge O 2 and prevent the diffusion of O 2 into the cells. This mechanism is believed to explain how nitrogenase can function when cells grow diazotrophically in the presence of O 2 . Although the respiration-protection hypothesis is widely accepted, it was recently challenged when it was reported that A. vinelandii had almost constant respiration rates and nitrogenase activity at O 2 concentrations ranging from 30 to 100% air saturation 23 , 24 . These results hardly support the concept of respiratory protection. As a complementary hypothesis, Oelze suggested that nitrogenase protection also depends on the maintenance of a sufficiently low redox state 25 . This hypothesis assumes that oxidation of the substrate can warrant the proper supply of reducing equivalents and ATP to maintain nitrogenase in a reduced state. Indeed, our data strongly supports this hypothesis in that the increased fluxes through respiratory TCA cycle and OPP pathway positively correlated with enhanced nitrogenase activity. As shown in Fig. 2 , the AV3 mutant exhibited remarkably higher metabolic activity in TCA cycle than wt strain in both media with and without supplemented ammonium, which suggests that sufficient ATP and reducing equivalents are produced when there is strong N 2 fixation activity. It also supports the notion that respiratory protection arises from stringently coupled respiratory electron transport with the TCA metabolism. Although the way in which diazotrophs increase TCA cycle flux in response to enhanced nitrogenase expression is still a mystery, knowledge of this correlation could lead to lead to new strategies to maximize nitrogenase activity for engineering increased ammonium release by alleviating apparent metabolic bottlenecks. One solution could be the use of alternative carbon substrates (e.g. citrate and acetate) that can increase the activity of the TCA cycle locally, and accordingly increase the supply of energy and reducing equivalents. Previous studies on diazotrophically growing A. vinelandii showed that growth rates obtained on acetate achieved 0.35 h −1 , higher than those grown on glucose (0.15 h −1 ) 26 . Therefore, addition of direct precursors of TCA cycle will not only supply ATP and reducing power for the highly active nitrogen fixation in the AV3 mutant, but also compensate for the carbon loss in TCA cycle which promises an enhanced biomass accumulation. It is noteworthy that the AV3 mutant showed a higher metabolic flux through the OPP pathway than wt in different ammonium availabilities which also supports the hypothesis in that extra reducing equivalents produced from an enhanced OPP pathway could be used to stabilize the enhanced nitrogenase activity in an AV3 mutant background. Overall, by deciphering the glucose metabolism of A. vinelandii , this work exemplifies novel insights into a general strategy that diazotrophs adopt for oxidizing carbon substrates under different conditions. It is our expectation that this quantitative knowledge of central carbon metabolism in terms of environmentally or genetically altered N-status can guide the reprogramming of diazotrophic metabolism geared toward increased technical feasibility of biologically produced ammonium fertilizers for industrial applications."
} | 3,339 |
38567970 | PMC11036807 | pmc | 8,127 | {
"abstract": "ABSTRACT Archaea, bacteria, and fungi in the soil are increasingly recognized as determinants of agricultural productivity and sustainability. A crucial step for exploring soil microbiomes with important ecosystem functions is to perform statistical analyses on the potential relationship between microbiome structure and functions based on comparisons of hundreds or thousands of environmental samples collected across broad geographic ranges. In this study, we integrated agricultural field metadata with microbial community analyses by targeting 2,903 bulk soil samples collected along a latitudinal gradient from cool-temperate to subtropical regions in Japan (26.1–42.8 °N). The data involving 632 archaeal, 26,868 bacterial, and 4,889 fungal operational taxonomic units detected across the fields of 19 crop plant species allowed us to conduct statistical analyses (permutational analyses of variance, generalized linear mixed models, randomization analyses, and network analyses) on the relationship among edaphic factors, microbiome compositions, and crop disease prevalence. We then examined whether the diverse microbes form species sets varying in potential ecological impacts on crop plants. A network analysis suggested that the observed prokaryotes and fungi were classified into several species sets (network modules), which differed substantially in association with crop disease prevalence. Within the network of microbe-to-microbe coexistence, ecologically diverse microbes, such as an ammonium-oxidizing archaeon, an antibiotics-producing bacterium, and a potentially mycoparasitic fungus, were inferred to play key roles in shifts between crop-disease-promotive and crop-disease-suppressive states of soil microbiomes. The bird’s-eye view of soil microbiome structure will provide a basis for designing and managing agroecosystems with high disease-suppressive functions. IMPORTANCE Understanding how microbiome structure and functions are organized in soil ecosystems is one of the major challenges in both basic ecology and applied microbiology. Given the ongoing worldwide degradation of agroecosystems, building frameworks for exploring structural diversity and functional profiles of soil microbiomes is an essential task. Our study provides an overview of cropland microbiome states in light of potential crop-disease-suppressive functions. The large data set allowed us to explore highly functional species sets that may be stably managed in agroecosystems. Furthermore, an analysis of network architecture highlighted species that are potentially used to cause shifts from disease-prevalent states of agroecosystems to disease-suppressive states. By extending the approach of comparative analyses toward broader geographic ranges and diverse agricultural practices, agroecosystem with maximized biological functions will be further explored.",
"introduction": "INTRODUCTION The ongoing global-scale degradation of agroecosystems is threatening food production ( 1 , 2 ). Maximizing the functions of microbial communities (microbiomes) is a prerequisite for building bases of sustainable agriculture ( 3 – 7 ). Archaea, bacteria, and fungi in the soil drive cycles of carbon, nitrogen, and phosphorus within agroecosystems ( 8 – 12 ). Many of those microbes also work to promote crop plant’s tolerance to drought and high temperature stresses as well as resistance to pests and pathogens ( 13 – 18 ). Importantly, those microbes vary greatly in their physiological impacts on crop plants ( 19 – 21 ). Therefore, gaining insights into soil microbiome compositions and functions is an essential starting point for managing resource-use efficient and disease-tolerant agroecosystems. Since the emergence of high-throughput DNA sequencing, a number of studies have revealed taxonomic compositions of prokaryotes and/or fungi in agroecosystem soil ( 22 – 24 ). Those studies have explored microbial species that potentially support crop plant growth and/or prevent crop plant disease ( 9 , 16 , 25 , 26 ). Meanwhile, each of the previous studies has tended to focus on specific crop plant species in specific farm fields ( 27 ), although there are some exceptionally comprehensive studies comparing multiple research sites ( 15 , 22 , 28 ). Therefore, generality in relationship between microbiome structure and functions remains to be examined in broader contexts (cf. global-scale analyses of soil microbiomes in natural ecosystems [ 29 – 32 ]). In other words, we still have limited knowledge of general patterns and features common to soil microbiomes with high crop plant yield or those with least crop disease risk. Thus, statistical analyses comparing microbiome structure among diverse crop plants across broad geographic ranges ( 15 , 22 ) are expected to deepen our understanding of microbial functions in agroecosystems. In particular, comparative studies of thousands of soil samples covering a wide range of latitudes will provide opportunities for finding general properties common to microbial communities with plant-growth-promoting or crop-disease-suppressive functions across diverse climatic conditions. Large data sets of soil microbiomes will also allow us to estimate interspecific interactions between microbial species ( 3 , 33 , 34 ). Archaea, bacteria, and fungi in soil ecosystems potentially form entangled webs of facilitative or competitive interactions, collectively determining ecosystem-level functions such as the efficiency of nutrient cycles and the prevalence of plant pathogens ( 35 , 36 ). In fact, ecological network studies have inferred how sets of microbial species could respond to the outbreaks or experimental introductions of crop plant pathogens ( 37 – 39 ). Although various statistical platforms for deciphering the architecture of such microbial interaction networks have been proposed ( 33 , 40 ), hundreds or more of microbial community samples are required to gain reliable inferences on interactions that reproducibly occur in real ecosystems ( 41 ). Thus, data sets consisting of thousands of soil samples collected across a number of local ecosystems will provide fundamental insights into how soil ecological processes are driven by cross-kingdom interactions involving archaea, bacteria, and fungi. In this study, we conducted a comparative analysis of agroecosystem soil microbiomes based on 2,903 bulk soil samples collected from subtropical to cool-temperate regions across the Japan Archipelago. Based on the amplicon sequencing data set representing farm fields of 19 crop plant species, we profiled prokaryotic and fungal community compositions in conventional agricultural fields in Japan. By compiling the metadata of the soil samples, we examined the potential relationship between soil microbiome structure and the prevalence of crop disease. The microbiome data set was then used to infer the structure of a microbe-to-microbe coexistence network consisting of diverse archaea, bacteria, and fungi. Specifically, we examined whether the network architecture was partitioned into compartments (modules) of closely interacting microbial species. In addition, we tested the hypothesis that such network modules could differ in their positive/negative associations with crop plant disease/health status. To explore prokaryotic and fungal species keys to manage agroecosystem structure and functions, we further explored “core” or “hub” species that were placed at the central positions within the inferred microbial interaction network. Overall, this study provides an overview of soil microbial diversity of cropland soil across a latitudinal gradient, setting a basis for diagnosing soil ecosystem status and identifying sets of microbes to be controlled in sustainable crop production.",
"discussion": "DISCUSSION We here profiled the diversity of agroecosystem microbiome structure across a latitudinal gradient from cool-temperate to subtropical regions based on the analysis of >2,000 soil samples. As partially reported in previous studies comparing microbiome compositions across broad geographic ranges ( 15 , 22 ), prokaryotic and fungal community structure varied depending on season, crop plant species, former crop identity, and background soil categories ( Fig. 2A ; Fig. S2; Table 1 ). In addition, soil chemical properties such as pH, electrical conductivity, and C/N ratio as well as the prokaryote/fungus abundance ratio significantly explained variation in microbiome structure (Fig. S3; Table 1 ). In contrast, available phosphorus concentrations had significant effects on neither prokaryotic nor fungal communities in the multivariate model ( Table 1 ), suggesting that nitrogen cycles rather than phosphorous ones are more tightly linked with microbiome structure. The integration of the microbiome data sets with agricultural field metadata allowed us to perform statistical tests of potential relationships between microbiome structure and agroecosystem performance ( Fig. 2 ; Table 2 ). A series of OTU-level analyses further highlighted taxonomically diverse prokaryotes and fungi showing strong positive or negative associations with crop health status ( Fig. 3 ; Fig. S5; Table 3 ). We then examined how these microbes differing in association with crop disease/health status form a network of coexistence. The architecture of the network involving diverse archaeal, bacterial, and fungal OTUs was highly structured, being partitioned into 11 modules ( Fig. 4A ). Intriguingly, the network modules varied considerably in constituent microbes’ association with crop disease levels ( Fig. 4B ). This result suggests that sets of microbes can be used to design soil microbiomes with crop-disease-suppressive functions. Among the detected modules, modules 2, 6, and 8 were of particular interest with regard to the assembly of microbial OTUs positively associated with crop health status ( Fig. 4 and 5 ). In contrast, modules 1 and 7 were constituted mainly by microbial OTUs negatively associated with plant health ( Fig. 4B ). In particular, module 7 was characterized by the presence of a notorious plant pathogenic fungus, Fusarium oxysporum ( 43 , 44 ; but see reference 45 for diversity of their impacts on plants). All these modules included both prokaryotes and fungi (Fig. S9; Data S3), illuminating the importance of inter-kingdom interactions ( 3 , 34 ). The presence of microbial species sets differing in plant-associated ecological properties suggests that keeping specific sets of compatible prokaryotes and fungi is essential for maximizing the stability of agricultural production ( 3 ). The analysis of network architecture further allowed us to explore core or hub species within the microbial network ( Fig. 6 ). Because the microbes highlighted with the examined network indices occupy key positions interconnecting many other microbes ( 46 ), their increase/decrease is expected to have profound impacts on whole community processes ( 3 , 33 , 34 ). In particular, control or manipulation of microbes located at the central positions interlinking different network modules ( 41 ) (i.e., microbes with high among-module connectivity; Fig. 6B ) may trigger drastic shifts in microbial community structure between disease-promotive and disease-suppressive states ( 3 ). The candidate list of such core species involved an ammonium-oxidizing archaeon ( Nitrosotenuis ) ( 47 ), an antibiotics-producing bacterium ( Streptomyces ) ( 48 ), a prevalent soil fungus ( Mortierella ) ( 49 , 50 ), a potentially mycoparasitic fungus ( Trichoderma ) ( 51 , 52 ), and fungi allied to plant pathogenic clades ( Curvularia and Plectosphaerella [anamorph = Fusarium ]) ( 53 , 54 ) ( Table 5 ). Given that many of the bacterial and fungal taxa listed above are culturable, experimental studies examining their ecological roles are awaited. Specifically, it would be intriguing to test whether substantial shifts in soil microbiome structure and functions can be caused by the introduction of those among-module hub microbes. Although the data set across a latitudinal gradient provided an opportunity for gaining bird’s-eye insights into the structure and potential functions of soil microbiomes, the results should be interpreted carefully with the recognition of potential methodological shortcomings and pitfalls. First, the approach of geographic comparison per se does not give a firm basis for deciphering microbial community dynamics. To gain fundamental insights into microbiome dynamics, we need to perform time-series monitoring ( 42 , 55 , 56 ) of soil prokaryotic and fungal community compositions. Second, information of microbial communities alone does not provide comprehensive insights into agroecosystem soil states. Given that soil ecosystem processes are driven not only by microbes but also by nematodes, arthropods, earthworms, and protists ( 57 – 60 ), simultaneous analyses of all prokaryotic and eukaryotic taxa ( 61 , 62 ) will help us infer whole webs of biological processes. Third, meta-analyses of agroecosystem performance across diverse crop fields require utmost care because there is no firm criterion commonly applicable to different crop plant species or different pest/pathogen species. As implemented in this study, effects of such difference may be partially controlled by including them as random variables in generalized linear mixed models (GLMMs; Table 2 ). Nonetheless, local-scale analyses targeting specific crop plant species and disease symptoms ( Fig. 3 ; Table 3 ; Data S2) are necessary to gain reliable inferences of potential microbial functions. Fourth, along with the potential pitfall discussed above, network modules can differ not only in properties related to crop disease/health status but also in those associated with crop plant identity or cropland management (Fig. S6 to S7). Again, findings in broad-geographic-scale analyses need to be supplemented by insights from local-scale observations ( Fig. 3 ). Fifth, amplicon sequencing approaches provide only indirect inference of biological functions. With the current capacity of sequencing and bioinformatic technologies, it is hard to assemble tens of thousands of microbial genomes based on the analysis of thousands of environmental samples. Furthermore, due to the paucity of the information of fungal ecology and physiology, it remains difficult to annotate high proportions of genes within fungal genomic data. Nonetheless, with the accumulation of methodological breakthroughs, shotgun sequencing of soil microbiomes will deepen our understanding of agroecosystem processes ( 63 – 65 ). Sixth, the cooccurrence network approach employed in this study did not allow us to separate direct and indirect interactions between microbes. Shotgun metagenomic sequencing analyses will provide detailed insights into the structure of metabolic interdependence among microbial species ( 66 , 67 ). Seventh, in this study, full sets of metadata were not available for all the sequenced samples, inevitably decreasing the number of samples examined in some statistical modeling. Although substantial efforts had been made to profile cropland soils in the national projects in which the soil samples were collected, continuous efforts are required to gain further comprehensive insights into agroecosystem structure and functions. Expanding the comparative microbiome analysis to different geographic regions and agroecosystem management practices will contribute to a more comprehensive understanding of microbiome structure and function. For example, comparison with soil agroecosystems in lower-latitudinal or higher-latitudinal regions or meta-analyses covering multiple continents will provide further comprehensive knowledge of the diversity of microbiome structure. In addition to extensions toward broader geographic ranges, those toward diverse agroecosystem management are of particular importance. Given that our samples were collected mainly from croplands managed with conventional agricultural practices, involvement of soil samples from regenerative or conservation agricultural fields ( 68 – 71 ) will reorganize our understanding of the relationship between microbiome compositions and functions. In conclusion, this data-driven research lays the groundwork for understanding fundamental mechanisms in soil ecosystems, offering innovative strategies for the design of sustainable agriculture."
} | 4,108 |
29125597 | PMC5776469 | pmc | 8,131 | {
"abstract": "Many bacteria are adapted for attaching to surfaces and for building complex\ncommunities, termed biofilms. The biofilm mode of life is predominant in\nbacterial ecology. So too is the exposure of bacteria to ubiquitous viral\npathogens, termed bacteriophages. Although biofilm–phage encounters are\nlikely to be common in nature, little is known about how phages might interact\nwith biofilm-dwelling bacteria. It is also unclear how the ecological dynamics\nof phages and their hosts depend on the biological and physical properties of\nthe biofilm environment. To make headway in this area, we develop a biofilm\nsimulation framework that captures key mechanistic features of biofilm growth\nand phage infection. Using these simulations, we find that the equilibrium state\nof interaction between biofilms and phages is governed largely by nutrient\navailability to biofilms, infection likelihood per host encounter and the\nability of phages to diffuse through biofilm populations. Interactions between\nthe biofilm matrix and phage particles are thus likely to be of fundamental\nimportance, controlling the extent to which bacteria and phages can coexist in\nnatural contexts. Our results open avenues to new questions of\nhost–parasite coevolution and horizontal gene transfer in spatially\nstructured biofilm contexts.",
"introduction": "Introduction Bacteriophages, the viral parasites of bacteria, are predominant agents of bacterial\ndeath and horizontal gene transfer in nature ( Thomas and Nielsen, 2005 ; Suttle,\n2007 ). Their ecological importance and relative ease of culture in the\nlaboratory have made bacteria and their phages a centerpiece of classical and recent\nstudies of molecular genetics ( Susskind and\nBotstein, 1978 ; Cairns et\nal. , 2007 ; Labrie\n et al. , 2010 ; Samson et al. , 2013 ; Salmond and Fineran, 2015 ) and host–parasite interaction ( Chao et al. , 1977 ; Levin et al. , 1977 ; Lenski and Levin, 1985 ; Bohannan and Lenski, 2000 ; Forde et al. , 2004 ; Brockhurst et al. , 2005 ; Kerr et al. , 2006 ; Vos et al. , 2009 ; Gómez and Buckling, 2011 , 2013 ; Koskella and\nBrockhurst, 2014 ). This is a venerable literature with many landmark\ndiscoveries, most of which have focused on liquid culture conditions. In addition to\nliving in the planktonic phase, many microbes are adapted for interacting with\nsurfaces, attaching to them and forming multicellular communities ( Weitz et al. , 2005 ; Meyer et al. , 2012 ; Persat et al. , 2015 ; Teschler et al. , 2015 ; van Vliet and Ackermann, 2015 ; Nadell et al. , 2016 ; O’Toole and Wong, 2016 ). These\ncommunities, termed biofilms, are characteristically embedded in an extracellular\nmatrix of proteins, DNA and sugar polymers that have a large role in how the\ncommunity interacts with the surrounding environment ( Flemming and Wingender, 2010 ; Dragoš and Kovács, 2017 ). As growth in biofilms and exposure to phages are common features of bacterial life,\nwe can expect biofilm–phage encounters to be fundamental to microbial\nnatural history ( Abedon, 2008 , 2012 ; Koskella et al. , 2011 ; Koskella, 2013 ; Díaz-Muñoz and Koskella, 2014 ; Nanda et al. , 2015 ). Furthermore, using\nphages to kill unwanted bacteria—which was eclipsed in 1940 by the advent of\nantibiotics in Western medicine—has experienced a revival in recent years as\nan alternative antimicrobial strategy ( Levin and\nBull, 2004 ; Azeredo and Sutherland,\n2008 ; Sillankorva et\nal. , 2010 ; Pires\n et al. , 2011 ; Chan\n et al. , 2013 ; Melo\n et al. , 2014 ). Understanding biofilm–phage\ninteractions is thus an important new direction for molecular, ecological and\napplied microbiology. Existing work suggests that phage particles may be trapped in\nthe extracellular matrix of biofilms ( Doolittle\n et al. , 1996 ; Lacroix-Gueu et al. , 2005 ; Briandet et al. , 2008 ); other studies have\nused macroscopic staining assays to measure changes in biofilm size before and after\nphage exposure, with results ranging from biofilm death, to no effect, to biofilm\naugmentation (reviewed by Chan and Abedon,\n2015 ). There is currently only a limited understanding of the mechanisms\nresponsible for this observed variation in outcome, and there has been little\nexploration of how phage infections spread within living biofilms on the length\nscales of bacterial cells. Biofilms, even when derived from a single clone, are heterogeneous in space and time\n( Stewart and Franklin, 2008 ; Ackermann, 2015 ). The extracellular matrix can\nimmobilize a large fraction of cells, constraining their movement and the mass\ntransport of soluble nutrients and wastes ( Flemming and Wingender, 2010 ; Teschler\n et al. , 2015 ). Population spatial structure, in\nturn, has a fundamental impact on intraspecific and interspecific interaction\npatterns ( Durrett and Levin, 1994 ; Kovács, 2014 ; Nadell et al. , 2016 ). Theory predicts\nqualitative changes in population dynamics when host–parasite contact rate\nis not a simple linear function of host and parasite abundance ( Liu et al. , 1986 ), which is\nalmost certainly the case for phages and biofilm-dwelling bacteria under spatial\nconstraint. It is thus very likely that the interaction of bacteria and phages will\nbe altered in biofilms relative to mixed or stationary liquid environments.\nAvailable literature supports the possibility of altered phage population dynamics\nin biofilms ( Vos et al. ,\n2009 ; Gómez and Buckling,\n2011 ; Heilmann et al. ,\n2012 ; Scanlan and Buckling,\n2012 ; Ashby et al. ,\n2014 ), but the underlying details of the phage–bacterial\ninteractions have been difficult to access experimentally or theoretically. Spatial\nsimulations that capture core mechanistic features of biofilms are a promising\navenue to begin tackling this problem. Here we use a simulation approach to study\nhow the biofilm environment can influence micrometer-scale population dynamics of\nbacteria and phages, highlighting connections between this research area and\nclassical findings from spatial disease ecology. Existing biofilm simulation frameworks are flexible and have excellent experimental\nsupport ( Hellweger and Bucci, 2009 ; Bucci et al. , 2011 ; Lardon et al. , 2011 ; Estrela et al. , 2012 ; Estrela and Brown, 2013 ; Hellweger et al. , 2016 ;\n Nadell et al. , 2016 ;\n Naylor et al. , 2017 ),\nbut they become impractical when applied to the problem of phage infection. We\ntherefore developed a new simulation framework to study phage–biofilm\ninteractions. Using this approach, we find that nutrient availability and phage\ninfection rates are critical control parameters of phage spread; furthermore, modest\nchanges in the diffusivity of phages within biofilms can cause qualitative shifts\ntoward stable or unstable coexistence of phages and biofilm-dwelling bacteria. The\nlatter result implies a central role for the biofilm extracellular matrix in phage\necology.",
"discussion": "Discussion Biofilm–phage interactions are likely to be ubiquitous in the natural\nenvironment and, increasingly, phages are drawing attention as the basis for new\nantibacterial strategies ( Abedon, 2015 ).\nOwing to the complexity of the spatial interplay between bacteria and their phages\nin the biofilm context, simulations and mathematical modeling serve a critical role\nfor identifying and understanding important features of phage–biofilm\ninteractions. Across species and contexts, biofilms are defined by the spatial\nconstraint, altered diffusion environment and heterogeneous solute distribution\nconditions created by cells while embedded in an extracellular matrix. Here we\ndeveloped a new simulation framework that captures these essential processes and\nused it to study how they alter the population dynamics of susceptible bacteria and\nlytic phages. At the outset of this study, we hypothesized that bacteria might be able to survive\nphage attack when nutrients are abundant and bacterial growth rate is high. The\nunderlying rationale was that, if bacterial growth and biofilm erosion are fast\nenough relative to phage proliferation, then biofilms could simply shed phage\ninfections from their outer surface into the passing liquid. This result was not\nobtained, even when nutrient influx and thus bacterial growth were conservatively\nhigh. We speculate that, for biofilms to shed phage infections in this manner, phage\nincubation must be long relative to bacterial growth and/or biofilm erosion must be\nexceptionally strong, such that biomass on the biofilm exterior is rapidly and\ncontinuously lost into the liquid phase. Our results do not eliminate this\npossibility entirely, but they suggest that this kind of spatial escape from phage\ninfection does not occur under a broad range of conditions. Biofilms could repel phage attack in our simulations when nutrient availability was\nlow, resulting in slow bacterial growth and widely spaced biofilm clusters. When\nbiofilms are sparse, phage–bacteria encounters are less likely to occur, and\nthus a higher probability of infection per phage–host contact event is\nrequired to establish a phage epidemic. Even if phages do establish an infection,\nwhen bacterial growth rates are low, the nearest biofilm cluster may be far enough\naway from the infected cell group that phages simply are not able to spread from one\nbiofilm cluster to another before being swept away by fluid flow. Note that this\nobservation likely depends on the scale of observation ( Levin, 1992 ): in a meta-population context, phage\nproliferation and subsequent removal into the passing liquid may lead to an epidemic\non a larger spatial scale. This caveat aside, our findings are directly analogous to\nthe concept of threshold host density as it applies in wildlife disease ecology\n( Maynard-Smith, 1974 ; May and Anderson, 1979 ; Satō et al. , 1994 ; Rand et al. , 1995 ; Keeling, 1999 ; Boots and Sasaki, 2002 ; Holt et al. , 2003 ; Lloyd-Smith et al. , 2005 ; Webb et al. , 2007 ). If host organisms, or\nclusters of hosts, are not distributed densely enough relative to the production\nrate and dispersal of a parasite, then epidemics cannot be sustained. Our spatial\nsimulations, which implement the essential biofilm-specific mechanics of bacterial\ngrowth and phage infection, can thus recapitulate qualitative features of classical\nwork in spatial epidemiology. This outcome draws concrete links between the\nmicroscopic world of phage–host population dynamics and the macroscopic\nworld of disease spread, with results expressed in terms of parameters that are\nexperimentally accessible to microbiologists. We hope that these key concepts may be\nused in the future as a bridge between researchers studying spatial disease ecology,\nbacterial biofilms and bacteriophages. Our results suggest that coexistence of lytic phages and susceptible host bacteria\nwill occur more readily as phage diffusivity decreases within biofilms, but this\noutcome also depends strongly on phage infectivity and nutrient flux. In two\nimportant modeling studies on phage–bacteria interactions under spatial\nconstraint, ( Heilmann et al. \n2010 , 2012 ) concluded that\ncoexistence can occur under a broad array of conditions if bacteria are provided\nwith refuges, that is, areas in which phage infectivity is decreased. An important\ndistinction of our approach is that bacterial refuges against phage infection emerge\nspontaneously because of the interaction between spatial constraint, biofilm growth,\nphage proliferation/diffusion and erosion of bacterial biomass into the surrounding\nliquid phase. Coexistence of bacteria and phages can be rendered dynamically\nunstable by modest changes in nutrient availability, phage infectivity or phage\ndiffusion. In other words, spatial structure is not enough to guarantee\nphage/bacteria coexistence; rather, given that bacteria and phages are spatially\nconstrained, one must also understand the total balance of biofilm expansion,\nbiofilm erosion, phage infectivity and phage advection/diffusion in order to\nunderstand the system’s population dynamics. The extracellular matrix is central to the ecology and physiology of biofilms ( Branda et al. , 2005 ; Nadell et al. , 2009 , 2015 , 2016 ; Flemming and Wingender,\n2010 ; Teschler et al. ,\n2015 ; Flemming et al. ,\n2016 ; Dragoš and\nKovács, 2017 ). In the simulations explored here, biofilm matrix\nwas modeled implicitly and is assumed to cause changes in phage diffusivity; our\nresults support the intuition that, by altering phage mobility and phages’\nphysical access to new hosts, the biofilm matrix is likely to be important in the\necological interplay of bacteria and their phages ( Abedon, 2017 ). A crucial role for the matrix in phage–bacteria\ninteractions is also supported by the common observation that matrix-degrading\nenzymes are encoded on phage genomes, which indicates that reducing the matrix\ndiffusion barrier is an important fitness currency for phages in natural\nenvironments ( Chan and Abedon, 2015 ; Pires et al. , 2016 ). Experiments comparing population dynamics of lytic phages and bacteria in well-mixed\nversus standing liquid cultures indicate that spatial heterogeneity can promote\nhost–parasite coexistence ( Brockhurst\n et al. , 2006 ). The biofilm environment shares some\nconceptual similarity to standing liquid cultures but is qualitatively different in\nits details, including sharp gradients of nutrient availability and growth within\nbiofilms, removal of cells from the biofilm system by dispersal, strong diffusion\nattenuation and matrix-imposed spatial constraints. Our work lends support to an\nearly suggestion that wall populations on the inner surfaces of culture flasks can\npromote bacteria–phage coexistence ( Schrag\nand Mittler, 1996 ). The populations described in this work were, almost\ncertainly, biofilms of matrix-embedded cells bound to the flask walls. The details\nby which this coexistence result occurs have not been clear; there is very little\nexperimental work thus far on the spatial localization and diffusion of phages\ninside biofilms, but the limited available literature is consistent with the idea\nthat the matrix alters phage movement ( Doolittle\n et al. , 1996 ; Sutherland et al. , 2004 ; Briandet et al. , 2008 ). In biofilms of E. coli , the matrix does indeed appear to reduce\nphage infection ( May et al. ,\n2011 ), and recent work with Pseudomonas aeruginosa grown\nin artificial sputum further supports the idea that matrix reduces phage\nsusceptibility ( Darch et al. ,\n2017 ). Experimental evolution approaches have shown that bacteria and\ntheir phages follow different evolutionary trajectories in biofilms versus\nplanktonic culture ( Gómez and Buckling,\n2011 ; Scanlan and Buckling,\n2012 ; Davies et al. ,\n2016 ). Especially compelling in the context of this work, P.\nfluorescens evolves matrix hyperproduction in response to consistent\nphage attack ( Scanlan and Buckling, 2012 ).\nThinking about phage diffusion and biofilm population structuring will be important\nnot just to the ecological community but also to molecular microbiologists trying to\nunderstand the mechanisms underlying phage transport through bacterial populations\nthat are embedded in matrix material. Here we have identified key properties of phages and their host cells that\nfundamentally impact population dynamics in bacterial biofilms. To achieve this,\nsome elements of bacteria–phage interaction were not considered. For\ninstance, we have not implemented co-evolution, though phage and bacterial\npopulations can co-evolve rapidly ( Thompson,\n1994 ; Levin and Bull, 2004 ;\n Weitz et al. , 2005 ;\n Koskella and Brockhurst, 2014 ; Perry et al. , 2015 ).\nSelection imposed by phage-mediated killing is responsible for the evolution of\ndiverse host defenses, including altered cell exterior structure, restriction\nendonucleases, sacrificial auto-lysis and the CRISPR-Cas adaptive immune system\n( Labrie et al. , 2010 ).\nThese host defense innovations have, in turn, spurred the evolution of sophisticated\nattack strategies on the part of phages ( Samson\n et al. , 2013 ). To break ground on the topic of\nphage–host population dynamics in heterogeneous biofilms, we have set aside\nthe problem of coevolution here; coevolution is undoubtedly important, however, and\nwe expect that biofilm environments will influence it strongly. For example, the\ntypical population sizes of bacteria and phages, as well as their mutual encounter\nrates, may be dramatically different in biofilms containing tens of thousands of\nspatially constrained cells, relative to liquid cultures containing tens of billions\nof well-mixed cells. The timescales and spatial patterns of bacteria–phage\ncoevolution in biofilms may therefore differ substantially from those in liquid\nculture, which is an important area for future work. We have focused only on lytic\nphages, but understanding within-biofilm population dynamics of lysogenic phages,\nwhich integrate into the genome of infected hosts, often changing their phenotypes\nand mediating horizontal gene transfer, is also a crucial topic. Overall, we\nenvision that studying bacteria–phage interactions under the unique\nconstraints of biofilm environments will yield important extensions on many fronts\nof this classical area of microbial ecology."
} | 4,314 |
26213439 | null | s2 | 8,133 | {
"abstract": "Honey bees ("
} | 3 |
25602283 | PMC4300079 | pmc | 8,134 | {
"abstract": "The last decade has seen a staggering transformation in our knowledge of microbial communities. Here, seven short pieces speculate as to what the next ten years might hold in store."
} | 45 |
35420482 | PMC9239210 | pmc | 8,135 | {
"abstract": "ABSTRACT Land conversion for intensive agriculture produces unfavorable changes to soil ecosystems, causing global concern. Soil bacterial communities mediate essential terrestrial ecosystem processes, making it imperative to understand their responses to agricultural perturbations. Here, we used high-throughput sequencing coupled with a functional gene array to study temporal dynamics of soil bacterial communities over 1 year under different disturbance intensities across a U.S. Southern Plains agroecosystem, including tallgrass prairie, Old World bluestem pasture, no-tillage (NT) canola, and conventional tillage (CT) wheat. Land use had the greatest impact on bacterial taxonomic diversity, whereas sampling time and its interaction with land use were central to functional diversity differences. The main drivers of taxonomic diversity were tillage > sampling time > temperature, while all measured factors explained similar amounts of variations in functional diversity. Temporal differences had the strongest correlation with total nitrogen > rainfall > nitrate. Within land uses, community variations for CT wheat were attributed to nitrogen levels, whereas soil organic matter and soil water content explained community variations for NT canola. In comparison, all measured factors contributed almost equally to variations in grassland bacterial communities. Finally, functional diversity had a stronger relationship with taxonomic diversity for CT wheat compared to phylogenetic diversity in the prairie. These findings reinforce that tillage management has the greatest impact on bacterial community diversity, with sampling time also critical. Hence, our study highlights the importance of the interaction between temporal dynamics and land use in influencing soil microbiomes, providing support for reducing agricultural disturbance to conserve soil biodiversity.",
"conclusion": "Conclusions. Environments in agroecosystems are continually modified due to land use and management practices that can, directly and indirectly, influence soil bacterial communities. Soil communities are exposed to variability in space and time, making no single biotic or abiotic factor the sole reason for shifts in bacterial community composition, raising the need for continued research on a range of agricultural systems. In this study, we investigated the effects of land use and sampling time on the structural and functional diversity of bacterial communities as well as the interactions with soil and environmental factors in four land uses in the U.S. Southern Plains. First, our results indicated that land use, especially with intensive management, had the greatest impact on taxonomic diversity, while sampling time and time within a specific land use were more important for differences observed in functional diversity. Next, soil nutrients, particularly nitrogen, and soil water content were determined to be critical for variations in community taxonomic and functional diversity across land management and sampling time. Last, functional diversity was also reduced under intensive management, with species likely being more specialized in function due to fertilizer usage and more strongly linked to taxonomic diversity than phylogenetic diversity. Although the impacts on functional and structural diversity may have different relationships with land use and sampling time, it is clear that both types of diversity are important for structuring the interactions of edaphic properties, climatic factors, and bacterial communities. The results contribute to the idea that preserving microbial diversity should be one of the main focuses of sustainable agriculture. While these observations may be regionally specific, we recommend sampling around management practices (e.g., August) as sampling in relation to a specific management practice or environmental change likely provides the most insight when trying to determine the impact on soil health. This is one reason why microbes show great promise as a soil health indicator as they can respond to disturbance before plant communities and soil properties. Additionally, we further recommend the use of no tillage as it increased the total nitrogen, organic matter, and water content in the soil, in comparison to CT management, which increased the reliance on nitrogen inputs, generating a less diverse and likely more specialized bacterial community. Moving forward, continued monitoring of changes in bacterial communities within local land uses’ corresponding natural and anthropogenic disturbances will likely be most useful when trying to make informed decisions about managing soil health and ecosystem services.",
"introduction": "INTRODUCTION Rising human populations have resulted in the need for increased land conversion to heavily managed environments for greater food production. Yet, land use change represents one of the largest perturbations to soil ecosystems, significantly impacting both aboveground and belowground communities ( 1 , 2 ). Whole ecosystem diversity is generally diminished when natural land is converted to agricultural systems, with lasting negative effects on soil health ( 3 ). In general, agricultural land use type regulates microbial diversity, plant diversity, and soil physicochemical properties ( 4 – 7 ). The effect of land use on microbial communities has become increasingly important since microbes represent the bulk of biodiversity in terrestrial ecosystems, perform essential ecosystem functions, and are fundamental to ecosystem stability ( 8 – 10 ). While it has been established that changes in land use shift microbial community structure and diversity, there has been a renewed focus on observing these communities under a gradient of disturbance intensities due to the quickly growing need for sustainable agricultural practices. Different intensities of soil disturbance create unique environments that support microbes with those specific environmental requirements ( 11 ). Although terrestrial microbial studies over large spatial scales ( 6 , 7 , 12 , 13 ) have demonstrated which soil and environmental factors are important for shaping microbial distribution patterns, they are unable to pinpoint the dynamics required to manage microbial communities at the local level. Agricultural management practices also vary locally, with inputs such as tillage, pesticide and fertilizer use, crop rotation, and residue incorporation directly altering soil microbial biomass ( 14 , 15 ) and community composition ( 2 , 16 ). This is critical as there is no ideal community type ( 17 ), soil type, or set of soil characteristics ( 18 , 19 ) when trying to define a functional soil system. By directing attention to gradients of disturbance in a range of land uses commonly found in agroecosystems, local variation can be captured in soil and environmental properties, management type, and plant diversity, which may give insight into the complex dynamics shaping soil communities ( 11 ). Patterns of variability between land use with increasing management disturbance have been studied extensively at single time points, but much less is known about the extent to which land use under a gradient of disturbance intensities interacts with temporal dynamics in altering soil bacterial communities. As seasons transition, variations occur in environmental factors such as solar radiation, temperature, and precipitation, all of which can affect microbial community structure and functions ( 20 – 23 ). Several studies investigating soil microbial community changes in relation to temporal variability have observed community differences in a range of time scales, many of which are associated with shifting environmental conditions ( 21 , 22 , 24 ). These variations in environmental conditions and community structure are often related to land management practices ( 16 , 23 , 25 ) and temporal changes in plant growth and development ( 26 , 27 ). Specifically, plant growth alters rhizodeposition, promoting microbial activity ( 28 ) and modifying community composition by enriching specific microorganisms ( 29 ). Expanding on spatiotemporal studies that are specific to the local land use, plant community, and soil conditions are critically needed. Functional diversity of the soil microbial community is equally important as compositional diversity when examining overall ecosystem diversity. Typically, a high structural and functional microbial diversity is thought to be fundamental to soil health, function, and sustainability by providing functional redundancy critical for ecosystem stability in the presence of stress and disturbance ( 9 , 30 – 32 ). The use of functional gene arrays (FGAs) or GeoChip has provided a way to examine relationships between microbial community structure and function by focusing on genes important to microbial processes like biogeochemical cycling and stress responses ( 33 – 39 ). FGAs allow for a thorough analysis of essential ecological questions, especially those concerned with microbial community responses to disturbances ( 35 , 40 – 44 ), including soil microbial community responses to land use, land management, and temporal changes ( 45 – 47 ). However, it remains unclear how the functional capabilities of soil microbial communities change under a gradient of disturbance intensities and seasons. To investigate the effect of land use with increasing management disturbance and season on the temporal dynamics of soil bacterial communities and its underlying mechanisms, we conducted a 12-month field study in agroecosystem land uses with a gradient of disturbance within the U.S. Southern Plains agroecosystem. The agricultural sites included two perennial grasslands and two annual croplands: a native tallgrass prairie (TGP), Old World bluestem (OWB) pasture, no-tillage (NT) canola ( Brassica napus L.) field, and conventional tillage (CT) winter wheat ( Triticum aestivum L.) field. In this study, we focused on the following questions. (i) Do land use with various types of management disturbance and season shape soil properties? (ii) How do land use and seasonal temporal dynamics interact to influence bacterial community diversity? (iii) What roles do soil and environmental properties play in influencing bacterial community diversity between seasons and under increasing management disturbance? We predicted that soil bacterial diversity would decrease with increasing management disturbance, while seasonal differences would become more discernible with increasing management disturbance. Our results revealed that land use drove differences in taxonomic diversity, while sampling time and its interaction with land use influenced functional gene diversity, and that the biotic and abiotic factors shaping bacterial community diversity also differed spatiotemporally with importance varying with management intensity.",
"discussion": "DISCUSSION Impact of land use and seasonality on soil properties. Land use change, management intensification, and season have different effects on soil properties and thus impact microbial communities in different ways. In this study, we examined how the soil ecosystem was affected by an increasing amount of management disturbance across four land uses commonly found in the U.S. Southern Plains. Land use change and management intensification modify the soil environment and generally reduce soil quality ( 48 ), as illustrated by the decrease in OM, TN, and SWC under tillage management compared to other land uses ( 49 ). Reducing management disturbance resulted in several soil properties being indistinguishable between land uses, further signifying that removing intensive management improves vital soil properties ( 1 ). Meanwhile, it had been previously observed that land uses under comparable amounts of management resulted in similar edaphic properties when cropland and non-cropland soil properties were compared ( 3 , 50 ), which may explain parallels between properties in NT canola and OWB pasture, which received similar yearly management. Only soil properties related to climate and management significantly differed by season. Lower SWC was evident in times of low monthly rainfall or increased daily temperatures. For the croplands, soils exhibited highs of TopN during summer and fall due to fertilizer application, which is expected as management practices in agricultural fields are largely seasonally dependent ( 23 , 51 ). Overall, even though land use was the greatest determinant of soil properties, sampling time was also key for explaining differences in soil properties, especially as management disturbance increased. Impacts of land use and seasonality on soil bacterial diversity. Determining how soil microbial community diversity is impacted across time and space is crucial for preserving soil health against continued environmental changes. The α-diversity and β-diversity of bacterial communities were distinctively altered by land use and season. As has been observed in a similar study comparing land use types and temporal dynamics ( 21 ), season had the most significant impact on α-diversity, with different land uses having greater diversity at various times of the year. However, the interactive effect of season and land use on belowground diversity remains unclear as most studies emphasize spatial variability over temporal variability ( 52 ). On large spatial scales, variation in α-diversity is not significantly explained by land use but rather soil properties ( 7 ), with moisture and nutrient availability generally being the most notable factors ( 20 , 53 , 54 ). Increases in TopN in the croplands decreased α-diversity ( 55 , 56 ), while SWC influenced α-diversity in the TGP. Both properties generally vary over shorter periods of time, making them potentially better predictors of seasonal microbial community changes ( 6 ). Even with the documented impact of season on α-diversity, it is thought that the importance of temporal dynamics is underestimated due to the presence of relic DNA ( 57 ), the response of different taxa to environmental changes ( 52 ), and the lack of focus on living/active cells ( 58 , 59 ). Given that no land use had the greatest α-diversity throughout the whole 1-year period and α-diversities were influenced by soil properties that vary seasonally, it is important to assess temporal dynamics when trying to determine differences in the microbial community. The effects of land use were far more critical for regulating the β-diversity of the bacterial communities across the management gradient. The β-diversity of all land use types differed from that of the TGP ( Fig. 2 ), with tillage management having the most significant impact ( Fig. 3 ). Between land uses, several soil factors and air temperature were critical for differences in bacterial diversity ( Fig. 3 ), while the distance between sites had no significant effect on the smaller scale of our study. Within fields, as management decreased, less variation in β-diversity was explained by the measured properties, of which the relative importance became more evenly distributed ( Fig. 4 ). No group of variables was the most important to variations in TGP bacterial diversity. In comparison, slightly greater importance of nitrogen and other soil properties was found to be associated with variations in OWB pasture, possibly due to changes in microbial community composition and diversity from management disturbances in grasslands ( 60 , 61 ). More variation in bacterial diversity was explained in the croplands. While both croplands were fertilized, soil N content was far more important to bacterial diversity in CT wheat, presumably because fertilizer was applied with no residue cover and directly incorporated through tillage. Soil properties that increased under NT management like SWC and OM explained more variations in the NT canola, supporting that reduced management increases carbon storage and moisture availability ( 62 , 63 ). Sampling time was also a significant driver of diversity differences ( Fig. 3 ), with rainfall and soil nutrients again having considerable influence. This is consistent with previous studies where climate variables, soil moisture, and nutrient availability dictated temporal changes ( 6 ). Although several factors were exclusive to shaping bacterial diversity based on time or space, SWC, OM, and TN continually appeared to be notable factors impacting the bacterial communities ( 64 – 67 ), with land use type being critical to explain differences in diversity, especially compared to the native system. It should be noted, that this was the first time canola was planted on the NT cropland, which had previously been a long-term winter wheat system. While plant species can influence the microbial communities, many other factors in croplands likely outweigh the introduction of a new crop. In agricultural systems, crops are cultivated in various soils being impacted by the soil type, soil properties, and land management, often reducing the importance of the rhizosphere microbial community for plant growth compared to native ecosystems ( 28 ). Soil properties have also been shown to override the influences of crop type on soil bacterial communities ( 68 ), with land use and management strongly shaping soil properties ( 1 , 21 ). Additionally, a mesocosm experiment using soil collected from long-term monoculture cropping systems determined that the cropping history of the soil was the main factor determining the microbial community composition when a new crop was introduced ( 69 ). Together, these points help emphasize that the plant type during this single growing season was likely not responsible for the overall observed differences. While much is still unknown about the relationship between taxonomic/phylogenetic and functional diversity, it is widely believed that increased diversity, including functional diversity, sustains soil functions and creates greater resilience to disturbance and stress ( 70 , 71 ). Taxonomic/phylogenetic and functional diversity can also be differentially affected by soil and environmental properties. Based on results from the FGA analysis, land use and sampling time were both central in shaping the functional diversity of the CT wheat and TGP field, although land use alone had less of an effect than sampling time or the interaction of sampling time with land use. The reduced effect of land use on functional diversity is likely due to shared taxa between communities leading to more similar functional traits ( 72 , 73 ) and the redundancy of many biogeochemical gene families across microbial groups ( 74 ). TGP functional diversity was associated with greater SWC, OM, and air temperature, and CT wheat functional diversity was associated with higher N content. Available N has been shown to significantly impact the active bacterial community and increase the number of taxonomic and phylogenetic groups that specialize in using N compounds ( 58 ). We also attempted to uncover the correlations between taxonomic/phylogenetic diversity and functional diversity, although deciphering such correlations is not straightforward. Functional diversity had stronger correlations to taxonomic diversity than to phylogenetic diversity in the CT wheat field, whereas in the TGP, functional diversity had stronger relationships with phylogenetic diversity. It is possible that the CT wheat community remains more phylogenetically similar over time, while the taxonomic community changes more rapidly. These types of patterns have been previously observed and suggested as warning signs of biodiversity loss due to environmental changes ( 75 , 76 ) resulting from intensive management practices in agroecosystems. Impacts of land use and seasonality on soil bacterial community composition. Throughout our study, the greatest management disturbance resulted in the greatest impact on the bacterial community, as shown by the results of tillage treatment at both the phylum and OTU levels. The impact of land management, especially tillage, on bacterial community composition has been extensively documented ( 1 , 77 , 78 ), and although less studied, season has considerable influence on composition as well ( 21 , 23 , 79 ). For all land uses, the most unique OTUs were present during the spring season. During spring, air temperatures begin to rise and rain increases. Temperature and moisture not only impact the physiological activity of bacterial communities, but also regulate plant activity, including rapid growth and increasing root exudates ( 80 , 81 ). Such large seasonal changes are likely responsible for differences in community composition observed between land uses as well as the increase in bacterial richness during the spring season. Monitoring changes in microbial composition over time and in response to management is one of the best ways to determine sustainable agricultural practices as it can indicate early potential changes in soil functionality, although it is necessary to remember there is not one optimal microbial community composition. To examine the functional gene community composition, relative gene abundances of the whole communities were compared between CT wheat and the TGP. Between the two land uses, the abundances of all genes that significantly differed were always greater in the TGP. Such differences are believed to be reflective of microbial functional gene abundance and diversity ( 46 ), although gene presence does not necessarily mean the gene is being actively transcribed. More distinct differences in gene abundances between land uses were apparent when comparing specific sampling times ( Fig. 5 ; Fig. S4 ). In general, seasonal microbial community differences are usually more evident in agricultural soils compared to native soils ( 21 ) due to seasonal management practices and plant activity. The greatest differences occurred during January, when plants in both fields were generally not active, air temperatures reached yearly lows, and CT wheat had the lowest SWC. The importance of soil water content in regulating microbial activities is well known, with soil water content being a key abiotic factor linked to functional diversity ( 82 ). Furthermore, the greater ground cover (i.e., residues) during the winter in the TGP may help alleviate the stress of the colder temperature on the microbial community, with greater plant litter amounts also increasing water infiltration and reducing soil evaporation ( 83 ). Therefore, the effects of reduced SWC and reduced ground cover could lead to decreased microbial diversity and activity under CT wheat. The smallest number of differences in the functional gene community was observed in August. The tallgrass prairie mainly consists of warm-season grasses; therefore, the plant community is in peak growth during this time, likely releasing nutrients to support microbial activity. In comparison, the CT wheat field is tilled during the summer fallow season to incorporate residues for decomposition providing organic carbon and nitrogen, again likely resulting in increased microbial activity ( 84 , 85 ). Even though there were clear differences in the functional diversities of the microbial communities in relation to land use and sampling time, it is equally necessary to survey changes in functional gene abundance as shifts in diversity alone do not always result in differences in the biogeochemical functional ability of the soil microbial community ( 86 , 87 ). Conclusions. Environments in agroecosystems are continually modified due to land use and management practices that can, directly and indirectly, influence soil bacterial communities. Soil communities are exposed to variability in space and time, making no single biotic or abiotic factor the sole reason for shifts in bacterial community composition, raising the need for continued research on a range of agricultural systems. In this study, we investigated the effects of land use and sampling time on the structural and functional diversity of bacterial communities as well as the interactions with soil and environmental factors in four land uses in the U.S. Southern Plains. First, our results indicated that land use, especially with intensive management, had the greatest impact on taxonomic diversity, while sampling time and time within a specific land use were more important for differences observed in functional diversity. Next, soil nutrients, particularly nitrogen, and soil water content were determined to be critical for variations in community taxonomic and functional diversity across land management and sampling time. Last, functional diversity was also reduced under intensive management, with species likely being more specialized in function due to fertilizer usage and more strongly linked to taxonomic diversity than phylogenetic diversity. Although the impacts on functional and structural diversity may have different relationships with land use and sampling time, it is clear that both types of diversity are important for structuring the interactions of edaphic properties, climatic factors, and bacterial communities. The results contribute to the idea that preserving microbial diversity should be one of the main focuses of sustainable agriculture. While these observations may be regionally specific, we recommend sampling around management practices (e.g., August) as sampling in relation to a specific management practice or environmental change likely provides the most insight when trying to determine the impact on soil health. This is one reason why microbes show great promise as a soil health indicator as they can respond to disturbance before plant communities and soil properties. Additionally, we further recommend the use of no tillage as it increased the total nitrogen, organic matter, and water content in the soil, in comparison to CT management, which increased the reliance on nitrogen inputs, generating a less diverse and likely more specialized bacterial community. Moving forward, continued monitoring of changes in bacterial communities within local land uses’ corresponding natural and anthropogenic disturbances will likely be most useful when trying to make informed decisions about managing soil health and ecosystem services."
} | 6,585 |
34257872 | PMC8246076 | pmc | 8,136 | {
"abstract": "Biological electron transfer (ET) across proteins is ubiquitous, such as the notable photosynthesis example, where light-induced charge separation takes place within the reaction center, followed by sequential ET via intramolecular cofactors within the protein. Far from biology, carbon dots (C-Dots) with their unique optoelectronic properties can be considered as game-changers for next-generation advanced technologies. Here, we use C-Dots for making heterostructure (HS) configurations by conjugating them to a natural ET mediator, the hemin molecule, thus making an electron donor–acceptor system. We show by transient absorption and emission spectroscopy that the rapid intramolecular charge separation happens following light excitation, which can be ascribed to an ultrafast electron and hole transfer (HT) from the C-Dot donor to the hemin acceptor. Upon integrating the HS into a protein matrix, we show that this HT within the HS configuration is 3.3 times faster compared to the same process in solution, indicating the active role of the protein in supporting the rapid light-induced long-range intermolecular charge separation. We further use impedance, electrochemical, and transient photocurrent measurements to show that the light-induced transient charge separation results in an enhanced ET and HT efficiency across the protein biopolymer. The charge conduction across our protein biopolymers, reaching nearly 0.01 S cm −1 , along with the simplicity and low-cost of their formation promotes their use in a variety of optoelectronic devices, such as artificial photosynthesis, photo-responsive protonic–electronic transistors, and photodetectors.",
"conclusion": "Conclusions In summary, we explored here the light-induced rapid charge separation within the C-Dot–hemin HS, how the protein biopolymer environment influences this charge separation process, and how it can influence the long-range charge transport across the protein biopolymer. We used steady-state and ultrafast transient spectroscopy to show that upon excitation of the C-Dot, a rapid HT process takes place between the C-Dot and the hemin molecule within the HS configuration. Importantly, we found that the HT rate was more than 3.3 times faster when the HS was doped into the protein biopolymer compared to the rate of the solvated HS, suggesting a fundamental role of the protein biopolymers in the charge separation process. Since it is not possible to determine the exact protein structure within the biopolymer and the exact binding site configuration of the HS, we cannot reveal which amino acids residues are in close contact with the HS, and accordingly, what are the exact energy states allowing the rapid charge separation and HT from the HS. We further used EIS and light-modulated I – T and I – V measurements to explore the contribution of the HS to the long-range charge transport across the protein biopolymer. The EIS measurements showed that the HS-doped biopolymer exhibits a staggering high conductivity under ambient conditions (at room temperature) of 8.5 mS cm −1 , which is one of the highest measured conductivity across any biological material. Light-modulated I – T measurements showed a clear improved photocurrent for the HS-doped biopolymer, and the light-modulated I – V measurements showed a clear formation of a redox peak only upon light excitation, all ascribed to the improved HT in the HS-doped biopolymer. All in all, our new protein biopolymer exhibits a myriad of different charge transport properties: (1) PT due to the hydrogen bond network between the amino acid residues, functional groups of the C-Dots, and water molecules. (2) Enhanced ET due to the hemin moieties in it. (3) Light-modulated ET due to the charge separation state of the HS and the observed HT. The biopolymer that we have used here is based on electrospinning the BSA protein, which is one of the most affordable commercially available proteins. Furthermore, the molecular doping approach that we used here is based on the affinity of BSA to a variety of tightly bound ligands; hence no chemistry is needed in this process. Accordingly, our new material is a very promising one for a variety of optoelectronic research and application, from artificial photosynthesis to light-modulated sensors, transistors, and detectors.",
"introduction": "Introduction Electron transfer (ET) is a fundamental process of many biological metabolic cycles as well as optoelectronic devices. 1–3 Nature utilizes proteins to directly transport electrons, most often across a biological membrane, for example, the ET chain reaction in the mitochondria during aerobic respiration or the light-induced ET during photosynthesis. 4 The latter example consists of a light-induced formation of an exciton on the chromophore, followed by a rapid (few ps) charge separation process, whereas the excited electron undergoes a sequential ET process across several intramolecular cofactors within the photosystem protein. In the end, the hole is used for water oxidation and the formation of oxygen, while the electron reduces NADP + for the formation of NADPH. Far from biology, (light-induced) ET is important in various applications, such as solar energy conversion, biosensing, molecular electronics, and many more. 5–7 In addition to electrons as charge carriers, proton transport (PT) is also important in the above-mentioned biological processes, and this type of transport is being mediated by proteins as well. Recently, it has been established that biomaterials can act as good long-range proton conductors, e.g. polysaccharides, melanin pigments, and protein-based materials. 8–11 Here, we utilize a protein-based biopolymer having PT capabilities, 10,12 while acknowledging novel light-induced ET properties using a molecular doping approach, 9 hence creating a bioderived mixed (opto-)electronic-protonic conductor. 8,10 The protein that we used here was bovine serum albumin (BSA), which was shown to form various types of biopolymers, such as electrospun mats. 13,14 Due to the abundance of protonated amino acids of the BSA protein as well as the high water content in the BSA-based electrospun mats, they show a modest proton conductivity of ∼0.1 mS cm −1 . 10 In addition to the low cost and commercial availability of the BSA protein, it has one more important advantage where it can strongly bind to a wide array of molecules and even nanoparticles. 15,16 In this context, it was shown that the BSA mats can bind to electron mediating heme molecules resulting in a superior ET across the mats, 9,17 as well as C-Dots that were shown to induce superior PT across the mats. 18 In here, we combine similar molecular dopants to form a C-Dot–hemin heterostructure (HS) that is being integrated into the protein-based matrix. In this way, we acknowledge the new hybrid protein-based biopolymer’s unique optoelectronic properties are due to the formation of a long-lived charge-separated state via exciton–exciton coupling; 19 where the C-Dots act as the photosensitizer and a tethered hemin molecule (Fe-containing protoporphyrin) is the electron (hole) acceptor. The use of C-Dots is gaining high momentum in recent years, and it is considered a replacement for the traditional semiconductor quantum dot due to its high aqueous solubility, easy functionalization, low toxicity, and chemical inertness. 20–24 In terms of their ET properties, C-Dots have been used as both electron donors as well as electron acceptors. 20,25–29 While we mainly use the C-Dot here as a photosensitizer, i.e. , a light-induced electron donor, it is important to state that the type of C-Dots that we use here also acknowledges superior PT efficiency across the BSA mat. 16 Besides being the electron acceptor, hemin is used here also as a molecular dopant for the BSA mat due to its strong binding affinity as well as a charge mediator capable of supporting long-range ET, whereas holes are the charge carriers. 9,12 The BSA mat itself here is not just a passive polymeric matrix for the various charge transport processes, but it plays a crucial role in these processes. First, it supports the PT across the material, and second, it acts as an electronic passivation layer as well as a carrier transfer mediator to reduce the recombination between electrons and holes upon light illumination. 30 Overall, our new hybrid material here exhibits a myriad of charge transfer processes: a light-induced short-range ET between the C-Dot and tethered hemin, a long-range ET across the BSA mat supported by the hemin dopant, and a long-range PT across the mat supported by the C-Dots and the protein itself. We use here steady-state and ultrafast spectroscopy, AC electrochemical impedance spectroscopy (EIS) and DC current–voltage ( I – V ) measurements to explore all of these processes and the interplay between them either in the form of a solvated HS or upon inserting the HS into the BSA mats."
} | 2,237 |
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