Integrating multi-platform assembly to recover MAGs from hot spring biofilms: insights into microbial diversity, biofilm formation, and carbohydrate degradation.

BACKGROUND: Hot spring biofilms provide a window into the survival strategies of microbial communities in extreme environments and offer potential for biotechnological applications. This study focused on green and brown biofilms thriving on submerged plant litter within the Sungai Klah hot spring in Malaysia, characterised by temperatures of 58-74 °C. Using Illumina shotgun metagenomics and Nanopore ligation sequencing, we investigated the microbial diversity and functional potential of metagenome-assembled genomes (MAGs) with specific focus on biofilm formation, heat stress response, and carbohydrate catabolism. RESULTS: Leveraging the power of both Illumina short-reads and Nanopore long-reads, we employed an Illumina-Nanopore hybrid assembly approach to construct MAGs with enhanced quality. The dereplication process, facilitated by the dRep tool, validated the efficiency of the hybrid assembly, yielding MAGs that reflected the intricate microbial diversity of these extreme ecosystems. The comprehensive analysis of these MAGs uncovered intriguing insights into the survival strategies of thermophilic taxa in the hot spring biofilms. Moreover, we examined the plant litter degradation potential within the biofilms, shedding light on the participation of diverse microbial taxa in the breakdown of starch, cellulose, and hemicellulose. We highlight that Chloroflexota and Armatimonadota MAGs exhibited a wide array of glycosyl hydrolases targeting various carbohydrate substrates, underscoring their metabolic versatility in utilisation of carbohydrates at elevated temperatures. CONCLUSIONS: This study advances understanding of microbial ecology on plant litter under elevated temperature by revealing the functional adaptation of MAGs from hot spring biofilms. In addition, our findings highlight potential for biotechnology application through identification of thermophilic lignocellulose-degrading enzymes. By demonstrating the efficiency of hybrid assembly utilising Illumina-Nanopore reads, we highlight the value of combining multiple sequencing methods for a more thorough exploration of complex microbial communities.

Genome-Wide Computational Prediction and Analysis of Noncoding RNAs in Oleidesulfovibrio alaskensis G20.

Noncoding RNAs (ncRNAs) play key roles in the regulation of important pathways, including cellular growth, stress management, signaling, and biofilm formation. Sulfate-reducing bacteria (SRB) contribute to huge economic losses causing microbial-induced corrosion through biofilms on metal surfaces. To effectively combat the challenges posed by SRB, it is essential to understand their molecular mechanisms of biofilm formation. This study aimed to identify ncRNAs in the genome of a model SRB, Oleidesulfovibrio alaskensis G20 (OA G20). Three in silico approaches revealed genome-wide distribution of 37 ncRNAs excluding tRNAs in the OA G20. These ncRNAs belonged to 18 different Rfam families. This study identified riboswitches, sRNAs, RNP, and SRP. The analysis revealed that these ncRNAs could play key roles in the regulation of several pathways of biosynthesis and transport involved in biofilm formation by OA G20. Three sRNAs, Pseudomonas P10, Hammerhead type II, and sX4, which were found in OA G20, are rare and their roles have not been determined in SRB. These results suggest that applying various computational methods could enrich the results and lead to the discovery of additional novel ncRNAs, which could lead to understanding the "rules of life of OA G20" during biofilm formation.

From genome to evolution: investigating type II methylotrophs using a pangenomic analysis.

A comprehensive pangenomic approach was employed to analyze the genomes of 75 type II methylotrophs spanning various genera. Our investigation revealed 256 exact core gene families shared by all 75 organisms, emphasizing their crucial role in the survival and adaptability of these organisms. Additionally, we predicted the functionality of 12 hypothetical proteins. The analysis unveiled a diverse array of genes associated with key metabolic pathways, including methane, serine, glyoxylate, and ethylmalonyl-CoA (EMC) metabolic pathways. While all selected organisms possessed essential genes for the serine pathway, Methylooceanibacter marginalis lacked serine hydroxymethyltransferase (SHMT), and Methylobacterium variabile exhibited both isozymes of SHMT, suggesting its potential to utilize a broader range of carbon sources. Notably, Methylobrevis sp. displayed a unique serine-glyoxylate transaminase isozyme not found in other organisms. Only nine organisms featured anaplerotic enzymes (isocitrate lyase and malate synthase) for the glyoxylate pathway, with the rest following the EMC pathway. Methylovirgula sp. 4MZ18 stood out by acquiring genes from both glyoxylate and EMC pathways, and Methylocapsa sp. S129 featured an A-form malate synthase, unlike the G-form found in the remaining organisms. Our findings also revealed distinct phylogenetic relationships and clustering patterns among type II methylotrophs, leading to the proposal of a separate genus for Methylovirgula sp. 4M-Z18 and Methylocapsa sp. S129. This pangenomic study unveils remarkable metabolic diversity, unique gene characteristics, and distinct clustering patterns of type II methylotrophs, providing valuable insights for future carbon sequestration and biotechnological applications. IMPORTANCE: Methylotrophs have played a significant role in methane-based product production for many years. However, a comprehensive investigation into the diverse genetic architectures across different genera of methylotrophs has been lacking. This study fills this knowledge gap by enhancing our understanding of core hypothetical proteins and unique enzymes involved in methane oxidation, serine, glyoxylate, and ethylmalonyl-CoA pathways. These findings provide a valuable reference for researchers working with other methylotrophic species. Furthermore, this study not only unveils distinctive gene characteristics and phylogenetic relationships but also suggests a reclassification for Methylovirgula sp. 4M-Z18 and Methylocapsa sp. S129 into separate genera due to their unique attributes within their respective genus. Leveraging the synergies among various methylotrophic organisms, the scientific community can potentially optimize metabolite production, increasing the yield of desired end products and overall productivity.

Genome-based approach to evaluate the metabolic potentials and exopolysaccharides production of Bacillus paralicheniformis CamBx3 isolated from a Chilean hot spring.

In the present study, a thermophilic strain designated CamBx3 was isolated from the Campanario hot spring, Chile. Based on 16S rRNA gene sequence, phylogenomic, and average nucleotide identity analysis the strain CamBx3 was identified as Bacillus paralicheniformis. Genome analysis of B. paralicheniformis CamBx3 revealed the presence of genes related to heat tolerance, exopolysaccharides (EPS), dissimilatory nitrate reduction, and assimilatory sulfate reduction. The pangenome analysis of strain CamBx3 with eight Bacillus spp. resulted in 26,562 gene clusters, 7,002 shell genes, and 19,484 cloud genes. The EPS produced by B. paralicheniformis CamBx3 was extracted, partially purified, and evaluated for its functional activities. B. paralicheniformis CamBx3 EPS with concentration 5 mg mL-1 showed an optimum 92 mM ferrous equivalent FRAP activity, while the same concentration showed a maximum 91% of Fe2+ chelating activity. B. paralicheniformis CamBx3 EPS (0.2 mg mL-1) demonstrated ß-glucosidase inhibition. The EPS formed a viscoelastic gel at 45°C with a maximum instantaneous viscosity of 315 Pa.s at acidic pH 5. The present study suggests that B. paralicheniformis CamBx3 could be a valuable resource for biopolymers and bioactive molecules for industrial applications.

Psychrophiles to control ice-water phase changes in frost-susceptible soils.

The phase changes of soil water or porous media have a crucial influence on the performance of natural and man-made infrastructures in cold regions. While various methods have been explored to address the impacts of frost-action arising from these phase changes, conventional approaches often rely on chemicals, mechanical techniques, and the reuse of waste materials, which often exhibit certain limitations and environmental concerns. In contrast, certain organisms produce ice-binding proteins (IBPs) or antifreeze proteins (AFPs) to adapt to low temperatures, which can inhibit ice crystal growth by lowering the freezing point and preventing ice crystallization without the need for external intervention. This study explores the potential of three psychrophilic microbes: Sporosarcina psychrophile, Sporosarcina globispora, and Polaromonas hydrogenivorans, to induce non-equilibrium freezing point depression and thermal hysteresis in order to control ice lens growth in frost-susceptible soils. We hypothesize that the AFPs produced by psychrophiles will alter the phase changes of porous media in frost-susceptible soils. The growth profiles of the microbes, the concentration of released proteins in the extracellular solution, and the thermal properties of the protein-mixed soils are monitored at an interval of three days. The controlled soil showed a freezing point of - 4.59 °C and thermal hysteresis of 4.62 °C, whereas protein-treated soil showed a maximum freezing point depression of - 8.54 °C and thermal hysteresis of 7.71 °C. Interestingly, except for the controlled sample, all the protein-treated soil samples were thawed at a negative temperature (minimum recorded at - 0.85 °C). Further analysis showed that the treated soils compared to porous media mixed soil freeze (1.25 °C vs. 0.51 °C) and thaw (2.75 °C vs. 1.72 °C) at extensive temperature gap. This freezing and thawing temperature gap is the temperature difference between the beginning of ice core formation and completed frozen, and the beginning of ice core thawing and completed thawed for the treated soil samples selected from different incubation days. Overall, this study presents a novel bio-mediated approach using psychrophilic microbes to control ice formation in frost-susceptible soils.

Biochemical unravelling of the endoxylanase activity in a bifunctional GH39 enzyme cloned and expressed from thermophilic Geobacillus sp. WSUCF1.

The glycoside hydrolase family 39 (GH39) proteins are renowned for their extremophilic and multifunctional enzymatic properties, yet the molecular mechanisms underpinning these unique characteristics continue to be an active subject of research. In this study, we introduce WsuXyn, a GH39 protein with a molecular weight of 58 kDa, originating from the thermophilic Geobacillus sp. WSUCF1. Previously reported for its exceptional thermostable ß-xylosidase activity, WsuXyn has recently demonstrated a significant endoxylanase activity (3752 U·mg-1) against beechwood xylan, indicating towards its bifunctional nature. Physicochemical characterization revealed that WsuXyn exhibits optimal endoxylanase activity at 70 °C and pH 7.0. Thermal stability assessments revealed that the enzyme is resilient to elevated temperatures, with a half-life of 168 h. Key kinetic parameters highlight the exceptional catalytic efficiency and strong affinity of the protein for xylan substrate. Moreover, WsuXyn-mediated hydrolysis of beechwood xylan has achieved 77 % xylan conversion, with xylose as the primary product. Structural analysis, amalgamated with docking simulations, has revealed strong binding forces between xylotetraose and the protein, with key amino acid residues, including Glu278, Tyr230, Glu160, Gly202, Cys201, Glu324, and Tyr283, playing pivotal roles in these interactions. Therefore, WsuXyn holds a strong promise for biodegradation and value-added product generation through lignocellulosic biomass conversion.

Convergence research and training in computational bioengineering: a case study on AI/ML driven biofilm-material interaction discovery.

Initially, research disciplines operated independently, but the emergence of trans-disciplinary sciences led to convergence research, impacting graduate programs and research laboratories, especially in bioengineering and material engineering as presented here. Current graduate curriculum fails to efficiently prepare students for multidisciplinary and convergence research, thus creating a gap between the students and research laboratory expectations. We present a convergence training framework for graduate students, incorporating problem-based learning under the guidance of senior scientists and collaboration with postdoctoral researchers. This case study serves as a template for transdisciplinary convergent training projects - bridging the expertise gap and fostering successful convergence learning experiences in computational biointerface (material-biology interface). The 18-month Advanced Data Science Workshop, initiated in 2019, involves project-based learning, online training modules, and data collection. A pilot solution utilized Jupyter notebook on Google collaborator and culminated in a face-to-face workshop where project presentations and finalization occurred. The program started with 9 experts in the four diverse fields creating 14 curated projects in data science (Artificial Intelligence/Machine Learning), material science, biofilm engineering, and biointerface. These were integrated into convergence research through webinars by the experts. The experts chose 8 of the 14 projects to be part of an all-day in-person workshop, where over 20 learners formed eight teams that tackled complex problems at the interface of digital image processing, gene expression analysis, and material prediction. Each team was comprised of students and postdoctoral researchers or research scientists from diverse domains including computer science, materials science, and biofilm research. Some projects were selected for presentation at the international IEEE Bioinformatics conference in 2022, with three resulting Machine Learning (ML) models submitted as a journal paper. Students engaged in problem discussions, collaborated with experts from different disciplines, and received guidance in decomposing learning objectives. Based on learner feedback, this successful experience allows for consolidation and integration of convergence research via problem-based learning into the curriculum. Three bioengineering participants, who received training in data science and engineering, have received bioinformatics jobs in biotechnology industries.

Integration of text mining and biological network analysis: Identification of essential genes in sulfate-reducing bacteria.

The growth and survival of an organism in a particular environment is highly depends on the certain indispensable genes, termed as essential genes. Sulfate-reducing bacteria (SRB) are obligate anaerobes which thrives on sulfate reduction for its energy requirements. The present study used Oleidesulfovibrio alaskensis G20 (OA G20) as a model SRB to categorize the essential genes based on their key metabolic pathways. Herein, we reported a feedback loop framework for gene of interest discovery, from bio-problem to gene set of interest, leveraging expert annotation with computational prediction. Defined bio-problem was applied to retrieve the genes of SRB from literature databases (PubMed, and PubMed Central) and annotated them to the genome of OA G20. Retrieved gene list was further used to enrich protein-protein interaction and was corroborated to the pangenome analysis, to categorize the enriched gene sets and the respective pathways under essential and non-essential. Interestingly, the sat gene (dde_2265) from the sulfur metabolism was the bridging gene between all the enriched pathways. Gene clusters involved in essential pathways were linked with the genes from seleno-compound metabolism, amino acid metabolism, secondary metabolite synthesis, and cofactor biosynthesis. Furthermore, pangenome analysis demonstrated the gene distribution, where 69.83% of the 116 enriched genes were mapped under "persistent," inferring the essentiality of these genes. Likewise, 21.55% of the enriched genes, which involves specially the formate dehydrogenases and metallic hydrogenases, appeared under "shell." Our methodology suggested that semi-automated text mining and network analysis may play a crucial role in deciphering the previously unexplored genes and key mechanisms which can help to generate a baseline prior to perform any experimental studies.

5-Fluorouracil-Encapsulated Films Using Exopolysaccharides from a Thermophilic Bacterium Geobacillus sp. WSUCF1 for Topical Drug Delivery.

Bacteria are capable of producing a specific type of biopolymer, termed exopolysaccharides (EPSs). EPSs from thermophile Geobacillus sp. strain WSUCF1 specifically can be assembled using cost-effective lignocellulosic biomass as the primary carbon substrate in lieu of traditional sugars. 5-fluorouracil (5-FU) is an FDA-approved, versatile chemotherapeutic that has yielded high efficacy against colon, rectum, and breast cancers. The present study investigates the feasibility of a 5% 5-fluorouracil film using thermophilic exopolysaccharides as the foundation in conjunction with a simple self-forming method. The drug-loaded film formulation was seen to be highly effective against A375 human malignant melanoma at its current concentration with viability of A375 dropping to 12% after six hours of treatment. A drug release profile revealed a slight burst release before it settled into an extended and maintained release of 5-FU. These initial findings provide evidence for the versatility of thermophilic exopolysaccharides produced from lignocellulosic biomass to act as a chemotherapeutic-delivering device and expand the overall applications of extremophilic EPSs.

Thermophilic Exopolysaccharide Films: A Potential Device for Local Antibiotic Delivery.

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.

Text-Mining to Identify Gene Sets Involved in Biocorrosion by Sulfate-Reducing Bacteria: A Semi-Automated Workflow.

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.

Graphene as Thinnest Coating on Copper Electrodes in Microbial Methanol Fuel Cells.

Dehydrogenation of methanol (CH3OH) into direct current (DC) in fuel cells can be a potential energy conversion technology. However, their development is currently hampered by the high cost of electrocatalysts based on platinum and palladium, slow kinetics, the formation of carbon monoxide intermediates, and the requirement for high temperatures. Here, we report the use of graphene layers (GL) for generating DC electricity from microbially driven methanol dehydrogenation on underlying copper (Cu) surfaces. Genetically tractable Rhodobacter sphaeroides 2.4.1 (Rsp), a nonarchetypical methylotroph, was used for dehydrogenating methanol at the GL-Cu surfaces. We use electrochemical methods, microscopy, and spectroscopy methods to assess the effects of GL on methanol dehydrogenation by Rsp cells. The GL-Cu offers a 5-fold higher power density and 4-fold higher current density compared to bare Cu. The GL lowers charge transfer resistance to methanol dehydrogenation by 4 orders of magnitude by mitigating issues related to pitting corrosion of underlying Cu surfaces. The presented approach for catalyst-free methanol dehydrogenation on copper electrodes can improve the overall sustainability of fuel cell technologies.

BASIN: A Semi-automatic Workflow, with Machine Learning Segmentation, for Objective Statistical Analysis of Biomedical and Biofilm Image Datasets.

Micrograph comparison remains useful in bioscience. This technology provides researchers with a quick snapshot of experimental conditions. But sometimes a two- condition comparison relies on researchers' eyes to draw conclusions. Our Bioimage Analysis, Statistic, and Comparison (BASIN) software provides an objective and reproducible comparison leveraging inferential statistics to bridge image data with other modalities. Users have access to machine learning-based object segmentation. BASIN provides several data points such as images' object counts, intensities, and areas. Hypothesis testing may also be performed. To improve BASIN's accessibility, we implemented it using R Shiny and provided both an online and offline version. We used BASIN to process 498 image pairs involving five bioscience topics. Our framework supported either direct claims or extrapolations 57% of the time. Analysis results were manually curated to determine BASIN's accuracy which was shown to be 78%. Additionally, each BASIN version's initial release shows an average 82% FAIR compliance score.

Photosynthetic microbial fuel cells for methanol treatment using graphene electrodes.

Photosynthetic microbial fuel cells (pMFC) represent a promising approach for treating methanol (CH3OH) wastewater. However, their use is constrained by a lack of knowledge on the extracellular electron transfer capabilities of photosynthetic methylotrophs, especially when coupled with metal electrodes. This study assessed the CH3OH oxidation capabilities of Rhodobacter sphaeroides 2.4.1 in two-compartment pMFCs. A 3D nickel (Ni) foam modified with plasma-grown graphene (Gr) was used as an anode, nitrate mineral salts media (NMS) supplemented with 0.1% CH3OH as anolyte, carbon brush as cathode, and 50 mM ferricyanide as catholyte. Two simultaneous pMFCs that used bare Ni foam and carbon felt served as controls. The Ni/Gr electrode registered a two-fold lower charge transfer resistance (0.005 kΩ cm2) and correspondingly 16-fold higher power density (141 mW/m2) compared to controls. The underlying reasons for the enhanced performance of R. sphaeroides at the graphene interface were discerned. The real-time polymerase chain reaction (PCR) analysis revealed the upregulation of cytochrome c oxidase, aa3 type, subunit I gene, and Flp pilus assembly protein genes in the sessile cells compared to their planktonic counterparts. The key EET pathways used for sustaining CH3OH oxidation were discussed.

Thermophilic Geobacillus WSUCF1 Secretome for Saccharification of Ammonia Fiber Expansion and Extractive Ammonia Pretreated Corn Stover.

A thermophilic Geobacillus bacterial strain, WSUCF1 contains different carbohydrate-active enzymes (CAZymes) capable of hydrolyzing hemicellulose in lignocellulosic biomass. We used proteomic, genomic, and bioinformatic tools, and genomic data to analyze the relative abundance of cellulolytic, hemicellulolytic, and lignin modifying enzymes present in the secretomes. Results showed that CAZyme profiles of secretomes varied based on the substrate type and complexity, composition, and pretreatment conditions. The enzyme activity of secretomes also changed depending on the substrate used. The secretomes were used in combination with commercial and purified enzymes to carry out saccharification of ammonia fiber expansion (AFEX)-pretreated corn stover and extractive ammonia (EA)-pretreated corn stover. When WSUCF1 bacterial secretome produced at different conditions was combined with a small percentage of commercial enzymes, we observed efficient saccharification of EA-CS, and the results were comparable to using a commercial enzyme cocktail (87% glucan and 70% xylan conversion). It also opens the possibility of producing CAZymes in a biorefinery using inexpensive substrates, such as AFEX-pretreated corn stover and Avicel, and eliminates expensive enzyme processing steps that are used in enzyme manufacturing. Implementing in-house enzyme production is expected to significantly reduce the cost of enzymes and biofuel processing cost.

Enhancement of Methane Catalysis Rates in Methylosinus trichosporium OB3b.

Particulate methane monooxygenase (pMMO), a membrane-bound enzyme having three subunits (α, ß, and γ) and copper-containing centers, is found in most of the methanotrophs that selectively catalyze the oxidation of methane into methanol. Active sites in the pMMO of Methylosinus trichosporium OB3b were determined by docking the modeled structure with ethylbenzene, toluene, 1,3-dibutadiene, and trichloroethylene. The docking energy between the modeled pMMO structure and ethylbenzene, toluene, 1,3-dibutadiene, and trichloroethylene was -5.2, -5.7, -4.2, and -3.8 kcal/mol, respectively, suggesting the existence of more than one active site within the monomeric subunits due to the presence of multiple binding sites within the pMMO monomer. The evaluation of tunnels and cavities of the active sites and the docking results showed that each active site is specific to the radius of the substrate. To increase the catalysis rates of methane in the pMMO of M. trichosporium OB3b, selected amino acid residues interacting at the binding site of ethylbenzene, toluene, 1,3-dibutadiene, and trichloroethylene were mutated. Based on screening the strain energy, docking energy, and physiochemical properties, five mutants were downselected, B:Leu31Ser, B:Phe96Gly, B:Phe92Thr, B:Trp106Ala, and B:Tyr110Phe, which showed the docking energy of -6.3, -6.7, -6.3, -6.5, and -6.5 kcal/mol, respectively, as compared to the wild type (-5.2 kcal/mol) with ethylbenzene. These results suggest that these five mutants would likely increase methane oxidation rates compared to wild-type pMMO.