Phylogeny of nitrogenase structural and assembly components reveals new insights into the origin and distribution of nitrogen fixation across bacteria and archaea

The phylogeny of nitrogenase has only been analyzed using the structural proteins NifHDK. As nifHDKENB has been established as the minimum number of genes necessary for in silico prediction of diazotrophy, we present an updated phylogeny of diazotrophs using both structural (NifHDK) and cofactor assembly proteins (NifENB). Annotated Nif sequences were obtained from InterPro from 963 culture-derived genomes. Nif sequences were aligned individually and concatenated to form one NifHDKENB sequence. Phylogenies obtained using PhyML, FastTree, RapidNJ, and ASTRAL from individuals and concatenated protein sequences were compared and analyzed. All six genes were found across the Actinobacteria, Aquificae, Bacteroidetes, Chlorobi, Chloroflexi, Cyanobacteria, Deferribacteres, Firmicutes, Fusobacteria, Nitrospira, Proteobacteria, PVC group, and Spirochaetes, as well as the Euryarchaeota. The phylogenies of individual Nif proteins were very similar to the overall NifHDKENB phylogeny, indicating the assembly proteins have evolved together. Our higher resolution database upheld the three cluster phylogeny, but revealed undocumented horizontal gene transfers across phyla. Only 48% of the 325 genera containing all six nif genes are currently supported by biochemical evidence of diazotrophy. In addition, this work provides reference for any inter-phyla comparison of Nif sequences and a quality database of Nif proteins that can be used for identifying new Nif sequences.SUPPLEMENTARY MATERIAL : FIGURE S1: Phylogenetic analysis of individual NifH proteins by FastTree using the JTT+CAT evolution model, FIGURE S2: Phylogenetic analysis of individual NifD proteins by FastTree using the JTT+CAT evolution model, FIGURE S3: Phylogenetic analysis of individual NifK proteins by FastTree using the JTT+CAT evolution model, FIGURE S4: Phylogenetic analysis of individual NifE proteins by FastTree using the JTT+CAT evolution model, FIGURE S5: Phylogenetic analysis of individual NifN proteins by FastTree using the JTT+CAT evolution model, FIGURE S6: Phylogenetic analysis of individual NifN proteins by FastTree using the JTT+CAT evolution model, FIGURE S7: Molecular phylogenetic analysis of concatenated NifHDKENB proteins by Maximum Likelihood (PhyML) with branch support by posterior probability. Each clade is highlighted by the bacterial or archaeal phylum and Proteobacteria are further divided into classes, FIGURE S8: Molecular phylogenetic analysis of concatenated NifHDKENB proteins Neighbour joining by RapidNJ using Kimura model. Each clade is highlighted by the bacterial or archaeal phylum and Proteobacteria are further divided into classes, FIGURE S9: Cladogram showing comparison of Astral tree obtained from six individual trees vs. majority consensus tree obtained from three trees obtained by FASTTREE, PhyML, and Neighbour Joining using concatenated NifHDKENB proteins. Black dots in Astral tree represents the Astral bootstrapping and on the concatenated tree represents the branching present in all three trees and all other splits present in at least two trees, FIGURE S10: Chronogram of evolution of diazotrophs obtained by selecting diazotrophic genera from the microbial evolution tree proposed by Zhu et al., 2019 using source data file. Node labels represent the time in billion years ago (Ga) in the original tree, FIGURE S11: Number of genomes containing all six nifHDKENB genes according to the year they were reported. Number of genomes without biochemical evidence increased rapidly with the increase in the number of genomes reported, SUPPLEMENTAL DATA S1: Nif/Vnf/Anf HDKENB protein sequences used for analyses, SUPPLEMENTAL DATA S2: Information on the strains and gene/protein sequences used, SUPPLEMENTAL DATA S3: List of all genera for which biochemical evidence of nitrogen fixation could be found in the literature, Supplemental tree file: High resolution tanglegram comparing the concatenated NifHDKENB tree with 16S rRNA phylogeny of the diazotrophs, both obtained using FastTree. Lines indicate the respective positions of the 963 bacteria in the 2 trees.The South Dakota Agricultural Experiment Stationhttps://www.mdpi.com/journal/microorganismsam2022BiochemistryGeneticsMicrobiology and Plant Patholog

Surface properties and adherence of Bradyrhizobium diazoefficiens to Glycine max roots are altered when grown in soil extracted nutrients

Soybean roots are colonized and nodulated by multiple strains of compatible nitrogenfixing rhizobia primarily belonging to the Genus Bradyrhizobium. Motility towards the root and attachment to root hairs are key determinants of competitive colonization and subsequent nodulation. Bacterial surface properties and motility are known to vary with chemical composition of the culture medium, and root adhesion and nodulation occur in a soil environment rather than laboratory medium. We asked whether the nodulation-promoting factors motility, surface hydrophobicity and surface adhesion of Bradyrhizobium are affected by growth in a soil nutrient environment. B. diazoefficiens USDA 110, 126, 3384, and B. elkanii USDA 26 were grown in mineral salt medium with peptone, yeast extract and arabinose (PSY), and in a soil extracted soluble organic matter (SESOM) medium. Surface hydrophobicity was determined by partitioning into hydrocarbon, motility by transition through soft agar, and surface-exposed saccharides by lectin profiling, followed by biofilm formation and soybean root adhesion capacity of populations. SESOM-grown populations were generally less motile and more hydrophobic. They bound fewer lectins than PSY-grown populations, indicating a simpler surface saccharide profile. SESOM populations of USDA 110 did not form detectable biofilm, but showed increased binding to soy roots. Our results indicate that growth in a soil environment impacts surface properties, motility, and subsequent soy root adhesion propensity. Hence, evaluation of Bradyrhizobium for nodulation efficiency should be performed using soil from the specific field where the soybeans are to be planted, rather than laboratory culture media.The National Science Foundation/EPSCoR RII Track-1: Building on The 2020 Vision: Expanding Research, Education and Innovation in South Dakota and by the South Dakota Board of Regents.https://www.mdpi.com/journal/nitrogenam2022BiochemistryGeneticsMicrobiology and Plant Patholog

Impacts of biochar-based controlled-release nitrogen fertilizers on soil prokaryotic and fungal communities

DATA AVAILABILITY STATEMENT : The raw data is available on NCBI’s Sequence Read Archive (SRA) database under BioProject: PRJNA854759.SUPPLEMENTARY MATERIAL : FIGURE S1: Alpha diversity using Shannon index, Bacterial (A) and Fungal (B) asterisk represent comparisons made using Kruskal–Wallis test with *p < 0.05; FIGURE S2: Bubble plot showing prokaryotic species significantly different for at least one treatment. Multiple dots together signify same grouping across different phyla; TABLE S1: Corn yield and Biomass; TABLE S2: Fertilizer descriptions (wt. % amount with moistures); TABLE S3: Soil Properties; TABLE S4: Commercial fertilizer ingredients; TABLE S5: Taxonomic distribution of the prokaryotic community in soil for each treatment; TABLE S6: Taxa different in high yield compared to other treatments at lowest taxa; TABLE S7: Taxonomic distribution of the fungal community in soil for each treatment; TABLE S8: Genera of fungus significantly different for treatment method.Controlled-release Nitrogen Fertilizers (CRNFs) are an effective fertilization technique by minimizing nutrient loss and making Nitrogen (N) available to plants as they grow. Biochar-based CRNF (BCRNF) technologies have been demonstrated very promising in increase of corn yield. Despite the beneficial effects of BCRNFs, their impacts on prokaryotic and fungal soil communities are not well evaluated. Different formulations of BCRNF were developed to investigate their effects on corn productivity. We analyzed the soil microbes and their functional potential under different BCRNF regimes using amplified V3–V4 region of 16s rRNA for determining prokaryotic, and ITS genes for fungal communities. The soil prokaryotic diversity was similar across the treatments, with differences in prokaryotic genera with relative abundance of 0.1% or less in the soil (p < 0.05). In contrast, the fungal community diversity was different only for unfertilized soil. It had a high relative abundance for Aspergillus. Genus level comparison showed that Pseudofabraea was higher in Bioasphalt-based BCRNF compared to other treatments. Moreover, the N-fixing communities in soil were also similar across the treatments. At genus level, Microvirga, Azospirillum, and Methyloprofundus were highest in no-fertilizer control. The functional potential predictions using PICRUSt2 portrayed a consistent N-cycling functions across the treatments. However, the predicted gene functions related to nitrous-oxide reductase (nosZ) and hydroxylamine reductase (hcp) were significantly lower in soil receiving BCRNF containing biosolid. Overall, BCRNF treatments previously identified to increase corn yield displayed minimal shifts in the soil microbial communities. Thus, such novel fertilization would enable increased crop yield without affecting soil communities leading to sustainable crop production.The South Dakota Governor’s Office of Economic Development and the USDA NIFA through the North Central Regional Sun Grant Center and Hatch Projects of the South Dakota Agricultural Experimental Station.https://www.mdpi.com/journal/agricultuream2023BiochemistryGeneticsMicrobiology and Plant Patholog

Niche preference of Escherichia coli in a peri-urban pond ecosystem

Escherichia coli comprises diverse strains with a large accessory genome, indicating functional diversity and the ability to adapt to a range of niches. Specific strains would display greatest fitness in niches matching their combination of phenotypic traits. Given this hypothesis, we sought to determine whether E. coli in a peri-urban pond and associated cattle pasture display niche preference. Samples were collected from water, sediment, aquatic plants, water snails associated with the pond, as well as bovine feces from cattle in an adjacent pasture. Isolates (120) were obtained after plating on Membrane Lactose Glucuronide Agar (MLGA). We used the uidA and mutS sequences for all isolates to determine phylogeny by maximum likelihood, and population structure through gene flow analysis. PCR was used to allocate isolates to phylogroups and to determine the presence of pathogenicity/virulence genes (stxI, stxII, eaeA, hlyA, ST, and LT). Antimicrobial resistance was determined using a disk diffusion assay for Tetracycline, Gentamicin, Ciprofloxacin, Meropenem, Ceftriaxone, and Azithromycin. Our results showed that isolates from water, sediment, and water plants were similar by phylogroup distribution, virulence gene distribution, and antibiotic resistance while both snail and feces populations were significantly different. Few of the feces isolates were significantly similar to aquatic ones, and most of the snail isolates were also different. Population structure analysis indicated three genetic backgrounds associated with bovine, snail, and aquatic environments. Collectively these data support niche preference of E. coli isolates occurring in this ecosystem.SUPPLEMENTARY MATERIAL : Figure S1: Multinomial log-linear regression analysis of phylogroup distribution of isolates across sample types. Phylogrouping was performed according to the scheme of Clermont et al., 2013. The X axis denotes phylogroups and the Y-axis represents proportion of isolates. Sed–sediment, W–water, WP–water plant, SN–snail, Figure S2: Virulence gene distribution across isolates allocate to phylogroups based on the scheme of Clermont et al., 2013. The number of isolates for each phylogroup is given in parentheses on the x axis, Figure S3: Distribution of sensitive (0) and isolates displaying Intermediate resistance to 1, 2, 3, 4 or 5 antibiotics from the five sampling sites, Table S1: Primers used for determining the uidA and mutS genes, and for phylogrouping, Table S2: Primers used for amplification of virulence genes.The South Dakota Agricultural Experiment Stationhttps://www.mdpi.com/journal/lifeam2022BiochemistryGeneticsMicrobiology and Plant Patholog

Distribution of Shewanella putrefaciens and Desulfovibrio vulgaris in sulphidogenic biofilms of industrial cooling water systems determined by fluorescent in situ hybridisation

Limited research has been done on the distribution and role of sulphidogenic facultative anaerobes within biofilms in microbially influenced corrosion (MIC). Sulphate-reducing bacteria (SRB) cause MIC and occur in the anaerobic zone of multispecies biofilms. Laboratory-grown multispecies biofilms irrigated with sulphate or sulphite-containing synthetic cooling water, and biofilms from an open simulated cooling water system, were hybridised with a rhodamine-labeled probe SPN3 (Shewanella putrefaciens) and fluorescein-labeled probe SRB385 (Desulfovibrio vulgaris) and investigated using scanning confocal laser microscopy. The facultative anaerobe S. putrefaciens and the strict anaerobe D. vulgaris synergistically coexisted in multispecies biofilms, but as time progressed, S. putrefaciens flourished, displacing D. vulgaris. The results show that S. putrefaciens is capable of growing in sulphidogenic biofilms in aerated environments such as industrial cooling water systems, colonising sulphidogenic biofilms and out-competing the true sulphate-reducing bacteria. WaterSA Vol.28(2) 2002: 123-12

GC‐Clamp Primer Batches Yield 16S rRNA Amplicon Pools with Variable GC Clamps, Affecting Denaturing Gradient Gel Electrophoresis Profiles

Fingerprinting methods such as denaturing gradient gel electrophoresis (DGGE) of 16S rRNA gene pools have become a popular tool for comparisons between microbial communities. The GC‐clamp portion of primers for DGGE amplicon preparation provides a key component in resolving fragments of similar size but different sequence. We hypothesized that repeat syntheses of identical 40‐base GC‐clamp primers lead to different DGGE profiles. Three repeat syntheses of the same GC‐clamp primer and two different GC‐clamp primers directed at the V3–5 region of the 16S rRNA gene were compared. Genomic DNA of two separate soil bacterial communities and three bacterial species was amplified and resolved by DGGE. The DGGE profiles obtained with repeat‐synthesized primers differed among each other as much as with alternate primers, for both soil DNA and pure single species. The GC‐clamp portion of members of amplicon pools varied among each other, deviating from the design sequence, and was the likely cause for multiple bands derived from a single 16S rRNA gene sequence. We recommend procuring an oligonucleotide batch large enough to conduct an entire project. This should help to avoid any DGGE profile variations due to performance differences between repeat syntheses of GC‐clamp oligonucleotide primers

Influence of Manure from Pigs Fed Chlortetracycline as Growth Promotant on Soil Microbial Community Structure

Chlortetracycline (CTC), an antimicrobial compound used in animal production, is not sorbed or degraded in the animal, and may enter the field environment through manure land-spreading. This study determined the influence of a single application of manure with or without CTC on field soil microbial community characteristics. Manures from swine fed unamended or CTC-amended rations were applied at 7,000 kg solid ha−1 to a Brandt silty clay loam soil that had no known prior history of manure application. Soil samples taken 1, 7, 28, or 42 days after treatment (DAT) were analyzed for aerobic culturable counts on R2A agar and most probable number using 2,4-D as sole carbon source. Soil extracts of 1, 7, and 42 DAT samples were subjected to polymerase chain reaction followed by denaturing gradient gel electrophoresis (DGGE) analysis of the V3 region of the 16S rRNA gene pool. Gels were analyzed by Neighbor Joining based on Euclidean distance and Raup–Crick multivariate statistical analysis, and selected bands were extracted to identify predominant community members. Both manure applications initially changed soil microbial diversity, however, communities appeared to converge over time, so that no long-term significant effect was detected with this single application