Search for: All records

Metagenomic studies on geothermal environments have been central in recent discoveries on the diversity of archaeal methane and alkane metabolism. Here, we investigated methanogenic populations inhabiting terrestrial geothermal features in Yellowstone National Park (YNP) by combining amplicon sequencing with metagenomics and mesocosm experiments. Detection of methyl-coenzyme M reductase subunit A (mcrA) gene amplicons demonstrated a wide diversity of Mcr-encoding archaea inhabit geothermal features with differing physicochemical regimes across YNP. From three selected hot springs we recovered twelve Mcr-encoding metagenome assembled genomes (MAGs) affiliated with lineages of cultured methanogens as well as Candidatus (Ca.) Methanomethylicia, Ca. Hadesarchaeia, and Archaeoglobi. These MAGs encoded the potential for hydrogenotrophic, aceticlastic, hydrogen-dependent methylotrophic methanogenesis, or anaerobic short-chain alkane oxidation. While Mcr-encoding archaea represent minor fractions of the microbial community of hot springs, mesocosm experiments with methanogenic precursors resulted in the stimulation of methanogenic activity and the enrichment of lineages affiliated with Methanosaeta and Methanothermobacter as well as with uncultured Mcr-encoding archaea including Ca. Korarchaeia, Ca. Nezhaarchaeia, and Archaeoglobi. We revealed that diverse Mcr-encoding archaea with the metabolic potential to produce methane from different precursors persist in the geothermal environments of YNP and can be enriched under methanogenic conditions. This study highlights the importance of combining environmental metagenomics with laboratory-based experiments to expand our understanding of uncultured Mcr-encoding archaea and their potential impact on microbial carbon transformations in geothermal environments and beyond.

 

Environmentally relevant metagenomes and BONCAT-FACS derived translationally active metagenomes from Powder River Basin coal seams were investigated to elucidate potential genes and functional groups involved in hydrocarbon degradation to methane in coal seams with high- and low-sulfate levels. An advanced subsurface environmental sampler allowed the establishment of coal-associated microbial communities under in situ conditions for metagenomic analyses from environmental and translationally active populations. Metagenomic sequencing demonstrated that biosurfactants, aerobic dioxygenases, and anaerobic phenol degradation pathways were present in active populations across the sampled coal seams. In particular, results suggested the importance of anaerobic degradation pathways under high-sulfate conditions with an emphasis on fumarate addition. Under low-sulfate conditions, a mixture of both aerobic and anaerobic pathways was observed but with a predominance of aerobic dioxygenases. The putative low-molecular-weight biosurfactant, lichysein, appeared to play a more important role compared to rhamnolipids. The methods used in this study—subsurface environmental samplers in combination with metagenomic sequencing of both total and translationally active metagenomes—offer a deeper and environmentally relevant perspective on community genetic potential from coal seams poised at different redox conditions broadening the understanding of degradation strategies for subsurface carbon.

 

Global warming and eutrophication contribute to the worldwide increase in cyanobacterial blooms, and the level of cyanobacterial biomass is strongly associated with rises in methane emissions from surface lake waters. Hence, methane‐metabolizing microorganisms may be important for modulating carbon flow in cyanobacterial blooms. Here, we surveyed methanogenic and methanotrophic communities associated with floatingMicrocystisaggregates in 10 lakes spanning four continents, through sequencing of 16S rRNA and functional marker genes. Methanogenic archaea (mainlyMethanoregulaandMethanosaeta) were detectable in 5 of the 10 lakes and constituted the majority (~50%–90%) of the archaeal community in these lakes. Three of the 10 lakes contained relatively more abundant methanotrophs than the other seven lakes, with the methanotrophic generaMethyloparacoccus,Crenothrix, and an uncultured species related toMethylobacterdominating and nearly exclusively found in each of those three lakes. These three are among the five lakes in which methanogens were observed. Operational taxonomic unit (OTU) richness and abundance of methanotrophs were strongly positively correlated with those of methanogens, suggesting that their activities may be coupled. TheseMicrocystis‐aggregate‐associated methanotrophs may be responsible for a hitherto overlooked sink for methane in surface freshwaters, and their co‐occurrence with methanogens sheds light on the methane cycle in cyanobacterial aggregates.

 

Metagenomic studies have revolutionized our understanding of the metabolic potential of uncultured microorganisms in various ecosystems. However, many of these genomic predictions have yet to be experimentally tested, and the functional expression of genomic potential often remains unaddressed. In order to obtain a more thorough understanding of cell physiology, novel techniques capable of testing microbial metabolism under close to in situ conditions must be developed. Here, we provide a benchmark study to demonstrate that bioorthogonal non-canonical amino acid tagging (BONCAT) in combination with fluorescence-activated cell sorting (FACS) and 16S rRNA gene sequencing can be used to identify anabolically active members of a microbial community incubated in the presence of various growth substrates or under changing physicochemical conditions. We applied this approach to a hot spring sediment microbiome from Yellowstone National Park (Wyoming, USA) and identified several microbes that changed their activity levels in response to substrate addition, including uncultured members of the phyla Thaumarchaeota, Acidobacteria, and Fervidibacteria. Because shifts in activity in response to substrate amendment or headspace changes are indicative of microbial preferences for particular growth conditions, results from this and future BONCAT-FACS studies could inform the development of cultivation media to specifically enrich uncultured microbes. Most importantly, BONCAT-FACS is capable of providing information on the physiology of uncultured organisms at as close to in situ conditions as experimentally possible.

 

Natural polysaccharides being investigated for use in the field of drug delivery commonly require the addition of sugars or pretreated biomass for fabrication. Geobacillus sp. strain WSUCF1 is a thermophile capable of secreting natural polymers, termed exopolysaccharides (EPSs), cultivated from cost-effective, non-treated lignocellulosic biomass carbon substrates. This preliminary investigation explores the capabilities of a 5% wt/wt amikacin-loaded film constructed from the crude EPS extracted from the strain WSUCF1. Film samples were seen to be non-cytotoxic to human keratinocytes and human skin-tissue fibroblasts, maintaining cell viability, on average, above 85% for keratinocytes over 72-h during a cell viability assay. The drug release profile of a whole film sample revealed a steady release of the antibiotic up to 12 h. The amikacin eluted by the EPS film was seen to be active against Staphylococcus aureus, maintaining above a 91% growth inhibition over a period of 48 h. Overall, this study demonstrates that a 5% amikacin-EPS film, grown from lignocellulosic biomass, can be a viable option for preventing or combating infections in clinical treatment. 

Sulfate-reducing bacteria (SRB) are anaerobic bacteria that form biofilm and induce corrosion on various material surfaces. The quorum sensing (QS) system that employs acyl homoserine lactone (AHL)-type QS molecules primarily govern biofilm formation. Studies on SRB have reported the presence of AHL, but no AHL synthase have been annotated in SRB so far. In this computational study, we used a combination of data mining, multiple sequence alignment (MSA), homology modeling and docking to decode a putative AHL synthase in the model SRB, Desulfovibrio vulgaris Hildenborough (DvH). Through data mining, we shortlisted 111 AHL synthase genes. Conserved domain analysis of 111 AHL synthase genes generated a consensus sequence. Subsequent MSA of the consensus sequence with DvH genome indicated that DVU_2486 (previously uncharacterized protein from acetyltransferase family) is the gene encoding for AHL synthase. Homology modeling revealed the existence of seven α-helices and six β sheets in the DvH AHL synthase. The amalgamated study of hydrophobicity, binding energy, and tunnels and cavities revealed that Leu99, Trp104, Arg139, Trp97, and Tyr36 are the crucial amino acids that govern the catalytic center of this putative synthase. Identifying AHL synthase in DvH would provide more comprehensive knowledge on QS mechanism and help design strategies to control biofilm formation. 

A significant amount of literature is available on biocorrosion, which makes manual extraction of crucial information such as genes and proteins a laborious task. Despite the fast growth of biology related corrosion studies, there is a limited number of gene collections relating to the corrosion process (biocorrosion). Text mining offers a potential solution by automatically extracting the essential information from unstructured text. We present a text mining workflow that extracts biocorrosion associated genes/proteins in sulfate-reducing bacteria (SRB) from literature databases (e.g., PubMed and PMC). This semi-automatic workflow is built with the Named Entity Recognition (NER) method and Convolutional Neural Network (CNN) model. With PubMed and PMCID as inputs, the workflow identified 227 genes belonging to several Desulfovibrio species. To validate their functions, Gene Ontology (GO) enrichment and biological network analysis was performed using UniprotKB and STRING-DB, respectively. The GO analysis showed that metal ion binding, sulfur binding, and electron transport were among the principal molecular functions. Furthermore, the biological network analysis generated three interlinked clusters containing genes involved in metal ion binding, cellular respiration, and electron transfer, which suggests the involvement of the extracted gene set in biocorrosion. Finally, the dataset was validated through manual curation, yielding a similar set of genes as our workflow; among these, hysB and hydA, and sat and dsrB were identified as the metal ion binding and sulfur metabolism genes, respectively. The identified genes were mapped with the pangenome of 63 SRB genomes that yielded the distribution of these genes across 63 SRB based on the amino acid sequence similarity and were further categorized as core and accessory gene families. SRB’s role in biocorrosion involves the transfer of electrons from the metal surface via a hydrogen medium to the sulfate reduction pathway. Therefore, genes encoding hydrogenases and cytochromes might be participating in removing hydrogen from the metals through electron transfer. Moreover, the production of corrosive sulfide from the sulfur metabolism indirectly contributes to the localized pitting of the metals. After the corroboration of text mining results with SRB biocorrosion mechanisms, we suggest that the text mining framework could be utilized for genes/proteins extraction and significantly reduce the manual curation time. 

Biofilm formation on surfaces via microbial colonization causes infections and has become a major health issue globally. The biofilm lifestyle provides resistance to environmental stresses and antimicrobial therapies. Biofilms can cause several chronic conditions, and effective treatment has become a challenge due to increased antimicrobial resistance. Antibiotics available for treating biofilm-associated infections are generally not very effective and require high doses that may cause toxicity in the host. Therefore, it is essential to study and develop efficient anti-biofilm strategies that can significantly reduce the rate of biofilm-associated healthcare problems. In this context, some effective combating strategies with potential anti-biofilm agents, including plant extracts, peptides, enzymes, lantibiotics, chelating agents, biosurfactants, polysaccharides, organic, inorganic, and metal nanoparticles, etc., have been reviewed to overcome biofilm-associated healthcare problems. From their extensive literature survey, it can be concluded that these molecules with considerable structural alterations might be applied to the treatment of biofilm-associated infections, by evaluating their significant delivery to the target site of the host. To design effective anti-biofilm molecules, it must be assured that the minimum inhibitory concentrations of these anti-biofilm compounds can eradicate biofilm-associated infections without causing toxic effects at a significant rate.