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White, R. A.

Publications and source records attributed to White, R. A..

17 recordsLinked to original sources

HydraMPP: A lightweight library for distributed massive parallel processing in Python - threading at scale.

We now exist in the era of massive datasets from genomics, large language models, and all the known knowledge of humanity right at our fingertips. Much of this data is becoming more accessible; however, processing such data remains an ongoing issue across systems including high performance computing (HPC) infrastructures. Massively parallel computing (MPP) has solved this using a divide and conquer approach by splitting workloads across independent nodes (i.e., central processing units (CPU) allowing for higher scaling of data). The main engine for this in python is Ray; however, it has many issues including a large code space, security issues, debugging opacity, and memory management issues. Here, we present HydraMPP, a lightweight, ease of use and utilization, with high auditability, and with SLURM ergonomics.

bioinformatics↗

Netrin-1 promotes pancreatic tumorigenesis and innervation through NEO1.

Nerves have been shown to regulate cancer progression. However, a clear demonstration of a role for axon guidance molecules in pancreatic tumorigenesis, innervation, and metastasis has been lacking. Using murine KrasG12D-mutant pancreatic organoids, we screened axon guidance molecules by qRT-PCR, identified Ntn1 upregulation, and then verified its in vivo upregulation during pancreatic tumorigenesis in humans and mice. NTN1 and its receptor NEO1 were upregulated in epithelial cells by the Kras mutation and {beta}-adrenergic signaling, in part, through the MAPK pathway. Ex-vivo culture of celiac ganglia showed that NTN1 promoted the axonogenesis of sympathetic neurons through the nerve NEO1 receptor. In the Pdx1-Cre;LSL-KrasG12D/+ model, Ntn1 knockout decreased sympathetic innervation and the development of pancreatic intraepithelial neoplasia. Treatment of pancreatic tumor organoids with recombinant NTN1 enhanced cell growth, epithelial-mesenchymal transition (EMT), and cancer stemness with the upregulation of ZEB1 and SOX9 through NEO1-mediated activation of focal adhesion kinase (FAK). In Pdx1-Cre;LSL-KrasG12D/+;LSL-Trp53R172H/+mice, Ntn1 knockout reduced innervation, FAK phosphorylation, and the features of EMT and stemness to extend mouse survival. In a liver metastasis model of PDAC (pancreatic ductal adenocarcinoma), treatment with a NTN1-neutralizing antibody or tumoral knockdown of Neo1 reduced ZEB1 and SOX9 and decreased tumor progression. In contrast, Ntn1 overexpression promoted innervation and the progression of PDAC liver metastasis. These data suggest that the NTN1/NEO1 axis is a key regulator of PDAC progression, directly influencing cancer cell stemness and EMT, while indirectly promoting tumor growth through nerves. Inhibiting the NTN1/NEO1 axis could represent a potential therapeutic approach for PDAC. Statement of SignificanceNTN1 promotes pancreatic tumorigenesis and metastasis directly and indirectly through nerves, highlighting the importance of tumor cell-nerve crosstalk in cancer. NTN1 blockade could represent a promising strategy for treating PDAC liver metastasis. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=88 SRC="FIGDIR/small/666009v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@ca611corg.highwire.dtl.DTLVardef@ad9264org.highwire.dtl.DTLVardef@1661c00org.highwire.dtl.DTLVardef@b86798_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

Comparative genomics reveals multipartite genomes undergoing loss in the fungal endosymbiotic genus Mycetohabitans

Endosymbiotic bacteria extensively impact phenotypes of their eukaryotic hosts, while experiencing dramatic changes to their own genome as they become more host-restricted in lifestyle. Understanding the trajectory of such a genome has largely been done through study of animal-associated bacteria, especially insect endosymbionts. Yet, endofungal bacteria provide another natural experimental model for investigating how microbial genomes change when living inside of a host cell. Mycetohabitans spp. are culturable bacterial endosymbionts of the Mucoromycota fungus Rhizopus microsporus. To investigate the genome dynamics resulting from the endohyphal nature of this emerging model genus, we long-read sequenced and assembled new complete genomes to combine with previous assemblies, creating a global dataset of 28 complete Mycetohabitans genomes. All genomes were between 3.3 and 3.9 Mbp in size and were multipartite, structured into two conserved replicons with some strains having an additional plasmid. Based on evolutionary rate and gene content analysis of the different replicons, we termed the two major ones a chromosome and chromid. The differential presence of a third, mobilome-rich plasmid in some strains and the proliferation of transposable elements provide putative mechanisms for recombination or gene loss. The conservation of intact prophage and putative toxin-antitoxin systems, and extensive enrichment of secondary metabolite clusters in the Mycetohabitans genomes highlight the dynamic nature of this reducing genome. With fungal-bacterial symbioses becoming increasingly apparent phenomena, lessons learned from this symbiosis will inform our understanding of bacterial adaptation to novel hosts, and the process of microbe-microbe coevolution. SIGNIFICANCEGenomes change when organisms become closely associated, as bacterial partners undergo less opportunities for genetic exchange and become more reliant on their hosts. Our pangenome analysis of the endofungal genus Mycetohabitans shows a snapshot of evolution where the bacteria are moving from a facultative towards an obligate relationship with their host fungi. We find that Mycetohabitans genomes are marked by transposable elements, pseudogenes, a large biosynthetic repertoire, and novel bacteriophage. We provide a genomic resource to match publicly accessible strains for future work on endosymbiotic genetics and evolution.

genomics↗

Unlocking the genomic repertoire of a cultivated megaphage

Megaphages are bacteriophages (i.e., phages) with exceptionally large genomes that are ecosystem cosmopolitans, infect various bacterial hosts, and have been discovered across various metagenomic datasets globally. To date, almost all megaphages have evaded cultivation, with only phage G being in active culture for over 50 years. We examined with multiomics this five decades long cultivated history from nine different laboratories with five different lab variants to the modern era. In this work, we resolved the five complete phage G genomes, the particle proteome, de novo methylome, and used artificial intelligence (AI) to annotate the genome of phage G. Phage G is one of the largest phages with a size of >0.6 {micro}m, about half the width of the host cell, and a 499 kbp, non-permuted, linear genome that has, uniquely among known phages, two pairs of ends. Its closest known relative is Moose phage W30-1 which was metagenomically assembled without cultivation from a moose rumen sample. Phage G has >650 protein-coding open reading frames (ORFs), with >65% being hypothetical proteins with no known function, with the rest of the genome geared towards nucleic acid replication (e.g., helicases, polymerases, endonucleases) and are structural in nature (e.g., capsid, tail, portal, terminase). The genome encodes a 35 kbp stretch with 66 ORFs without any known functional homology, a cryptic genomic region that is roughly the size of phage lambda. Phage G has an expansive repertoire of auxiliary metabolic genes (AMGs) acquired from its bacterial host, including a phoH,ftsZ,UvsX/RecA-like, gyrA, gyrB,and DHFR. Furthermore, AMGs discovered in phage G could manipulate host sporulation (sspD, RsfA, spoK) and antiviral escape genes (e.g., anti-CBass nuclease and Anti-Pycsar protein). Phage proteomics found >15% of the protein ORFs were present in either the wild-type or mutant variants of phage G, including genes involved in replication (e.g.,UvsX/RecA-like), host sporulation, as well as structural genes (e.g., capsid, tail, portal). The methylome of phage G was localized to the cryptic region with limited functional homology, with supervised machine learning (i.e., HMMs) was unable to resolve this region, but was resolved with protein structural AI. This cryptic region was a hot spot for methylation at 32%, where many of the functions of the ORF are still unknown. Our study represents a doorway into the complexity of the genomic repertoire of the only cultivated megaphage, highlighting five decades of continuous cultivation for the first time.

microbiology↗

Experimental Phage Evolution Results in Expanded Host Ranges Against MDR and XDR Klebsiella pneumoniae Isolates

Resistance to antibiotics is approaching crisis levels for organisms such as the ESKAPEE pathogens (includes Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp., and Escherichia coli) that often are acquired in hospitals. These organisms sometimes have acquired plasmids that confer resistance to most if not all beta-lactam antibiotics such as those produced by Carbapenem Resistant Enterobacterales (CREs). We have been developing alternative means for dealing with antibiotic resistant microbes that cause infections in humans by developing viruses (bacteriophages) that attack and kill them. We have been working with one of the ESKAPEE pathogens, K. pneumoniae, that has one of the highest propensities for antimicrobial resistance, to develop phages that target and kill it. We identified a number of phages that have lytic capacity against only a few clinical isolates, and through experimental evolution over the course of 30 days, were able to vastly expand the host ranges of these phages to kill a broader range of clinical K. pneumoniae isolates including MDR (multi-drug resistant) and XDR (extensively-drug resistant) isolates. Most interestingly, they were capable of inhibiting growth of clinical isolates both on solid and in liquid medium over extended periods. That we were able to extend the host ranges of multiple naive MDR and XDR K. pneumoniae through experimental phage evolution suggests that such a technique may be applicable to other antibiotic-resistant organisms to help stem the tide of antibiotic resistance and offer further options for medical treatments. ImportanceBacterial pathogens are becoming greater threats given the rise in antibiotic resistance, where traditional therapies may no longer work to cure some infections. Chief amongst these multidrug resistant infections (MDR) and extensively drug-resistant infections (XDR) is Klebsiella pneumoniae, which is known to sometimes harbor genetic elements that render it incredibly difficult to treat with conventional antibiotics. Treatments like bacteriophages have not had much success against such pathogens because resistance to the phages used often develops rapidly. We adapted a co-evolutionary technique to develop K. pneumoniae phages to be highly active longitudinally against K. pneumoniae clinical isolates. In as few as 30 days, we were able to vastly expand the host ranges of K. pneumoniae phages against MDR and XDR clinical isolates and that maintain their infectivity over clinically relevant time periods. By adapting these established techniques to clinical MDR and XDR K. pneumoniae isolates, we believe we can establish similar techniques for expanding phage host ranges against most antibiotic-resistant bacteria. As such, phages can be viable alternatives to antibiotics when antibiotic resistance exists in hospitals and communities.

microbiology↗

High Throughput Viral Enumeration of Aquatic Ecosystems via Flow Cytometry

For the past 25 years, flow cytometry has been a gold standard for the direct measurement of viral-like particles (VLP) in aquatic ecosystems. Flow cytometry allows for higher throughput and costs less than alternative enumeration methods, leading to its broad usage in aquatic viral ecology. A major challenge associated with flow cytometry is the degradation of VLPs over time, making the use of high throughput plates not possible, thus lowering overall throughput. It has also been difficult to maintain a method with low contamination, high signal-to-noise ratios, and observations of real VLPs vs. fake particles. For these reasons, the use of flow cytometry has rapidly declined over the years due to the advent of massively parallel sequencing. Here, we describe a high throughput method in a 96 well plate format that provides a hands-free approach to viral enumeration. Our approach limits fake particles, noise levels, and cross-sample contamination. In a standard run, 60 samples can be measured for VLPs within 2.25 hours, which is [~]1 hour faster than the standard single tube approach and [~]1.5 hours faster than epifluorescence microscopy (EFM). Direct measurement of VLPs still provides a window into the viral-host interactions within aquatic ecosystems, which can be rapidly measured and resolved in a high throughput manner.

microbiology↗

A CXCR4 partial agonist improves immunotherapy by targeting polymorphonuclear myeloid-derived suppressor cells and cancer-driven granulopoiesis

Polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) are pathologically activated neutrophils that potently impair immunotherapy responses. The chemokine receptor CXCR4, a central regulator of hematopoiesis, represents an attractive PMN-MDSC target1. Here, we fused a secreted CXCR4 partial agonist TFF2 to mouse serum albumin (MSA) and demonstrated that TFF2-MSA peptide synergized with anti-PD-1 to induce tumor regression or eradication, inhibited distant metastases, and prolonged survival in multiple gastric cancer (GC) models. Using histidine decarboxylase (Hdc)-GFP transgenic mice to track PMN-MDSC in vivo, we found TFF2-MSA selectively reduced the immunosuppressive Hdc-GFP+ CXCR4hi tumor PMN-MDSCs while preserving proinflammatory neutrophils, thereby boosting CD8+ T cell-mediated anti-tumor response together with anti-PD-1. Furthermore, TFF2-MSA systemically reduced PMN-MDSCs and bone marrow granulopoiesis. In contrast, CXCR4 antagonism plus anti-PD-1 failed to provide a similar therapeutic benefit. In GC patients, expanded PMN-MDSCs containing a prominent CXCR4+LOX-1+ subset are inversely correlated with the TFF2 level and CD8+ T cells in circulation. Collectively, our studies introduce a strategy of using CXCR4 partial agonism to restore anti-PD-1 sensitivity in GC by targeting PMN-MDSCs and granulopoiesis.

cancer biology↗

Large-Scale Computational Modeling of H5 Influenza Variants Against HA1-Neutralizing Antibodies

The United States Department of Agriculture has recently released reports that show samples from 2022-2024 of highly pathogenic avian influenza (H5N1) have been detected in mammals and birds (1). To date, the United States Centers for Disease Control reports that there have been 27 humans infected with H5N1 in 2024 (2). The broader potential impact on human health remains unclear. In this study, we computationally model 1,804 protein complexes consisting of various H5 isolates from 1959 to 2024 against 11 hemagglutinin domain 1 (HA1)-neutralizing antibodies. This study shows a trend of weakening binding affinity of existing antibodies against H5 isolates over time, indicating that the H5N1 virus is evolving immune escape of our medical defenses. We also found that based on the wide variety of host species and geographic locations in which H5N1 was observed to have been transmitted from birds to mammals, there is not a single central reservoir host species or location associated with H5N1s spread. These results indicate that the virus has potential to move from epidemic to pandemic status in the near future. This study illustrates the value of high-performance computing to rapidly model protein-protein interactions and viral genomic sequence data at-scale for functional insights into medical preparedness. Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSPrevious studies have shown cases of avian influenza transmissions to mammals that are increasing in frequency, which is of concern to human health. Since 1997, nearly a thousand H5N1 cases have been reported in humans with a 52% fatality rate. Previous analyses have indicated specific mutations on the hemagglutinin protein that allow for this "host jumping" between birds and mammals (3). There are also existing evidence of recent viral strains with reduced neutralization to sera (4). Added value of this studyThis study provides a comprehensive look at the mutational space of hemagglutinin of H5N1 influenza and presents computational predictions of the binding between various HA1-neutralizing antibodies derived from infected vaccinated patients and humanized mice and 1,804 representative H5 HA1 proteins. These analyses show a weakening trend of existing antibodies. We also confirm that the mutations found in other studies that enable zoonosis also affect binding affinities of the antibodies tested. Furthermore, through phylogenetic analyses, we quantify the avian-to-mammalian transmissions from 1959 to 2024 and show a persistent circulation of isolates between North America and Europe. Taken together, the continuous transmission of H5N1 from birds to mammals and the increase in immuno-evasive HA strains in mammals sampled over time suggest that antigenic drift is a source of spillover risk. Implications of all the available evidenceOur findings indicate that the worsening in antibody binding, along with the increase in of avian-to-mammalian H5N1 influenza transmissions are risks to public health. Through the findings of previous studies along with the predictions reported in this study, we can now monitor specific mutations of interest, quantified by their potential impact on antibody evasion, and inform public health monitoring of circulating isolates in 2024 and beyond. In addition, these findings may help to guide future vaccine and therapeutic development in the fight against H5N1 influenza infections in humans.

bioinformatics↗

Resolving and Quantifying Viral-Like Particles via Blind Deconvolution

Viruses represent the most numerous biological entities on Earth; but the direct quantification of viruses within ecosystems reminds an ongoing challenge. The classical method of epifluorescence microscopy (EFM) reminds the gold standard measurement of viral-like particles (VLPs) within ecosystems. Quantifying VLPs in epifluorescence microscopy is burdened by ongoing challenges that include manual human counting, an absence of accurate morphological sizing, and the a range of viral sizes (20-300 nm) falling below the diffraction limit of light microscopy. Here, a proof-of-concept computer vision framework for the automated enumeration and sizing of viral-like particles is presented, known as EpiVirQuant. A novel tunable pointspread function is introduced which allows for a dynamic blind deconvolution. Final enumeration by EpiVirQuant was directly compared to manual human counting which yielded 18% more VLPs identified. EpiVirQuant quantified average VLP size of 179.5 nm, which is consistent with median size of VLPs in nature of of _160 nm. Runtime ranged from 60-80 seconds-perimage depending on parameter selection. This provides a viable proof-of-concept cost-effective solution for the enumeration and large-scale morphological analysis of VLPs.

bioinformatics↗

NFixDB (Nitrogen Fixation DataBase) - A Comprehensive Integrated Database for Robust 'Omics Analysis of Diazotrophs

Biological nitrogen fixation is a fundamental biogeochemical process that transforms that provides fixed biologically available nitrogen by diazotrophic microbes. Diazotrophs anaerobically fix nitrogen using the nitrogenase enzyme which has three different gene clusters: 1) molybdenum nitrogenase (nifDHK) is the most abundant, followed by its alternatives 2) vanadium nitrogenase (vnfDHK), and 3) iron nitrogenase (anfDHK). Multiple databases have been constructed as resources for diazotrophic omics analysis; however, an integrated database based on whole genome references does not exist. Here, we present NFixDB (Nitrogen Fixation DataBase), a comprehensive integrated whole genome based database for diazotrophs, which includes all nitrogenases (nifDHK, vnfDHK, anfDHK) and nitrogenase-like enzymes (e.g., nflDH) linked to ribosomal operons (16S-5.8S-23S). NFixDB was computed using Hidden Markov Models (HMMs) against the entire whole genome based Genome Taxonomy Database (GTDB R214), providing searchable reference HMMs for all nitrogenase and nitrogenase-like genes, complete ribosomal operons, both GTDB and NCBI/RefSeq taxonomy, and an SQL database for querying matches. We compared NFixDB to nifH databases from Buckley, Zehr, Mise, and FunGene finding extensive evidence of nifH, in addition to vnfH and nflH. NFixDB contains more than 4,000 verified nifHDK sequences contained on 50 unique phyla of bacteria and archaea. NFixDB offers the first comprehensive nitrogenase database available to researchers.

bioinformatics↗

The eukaryome of modern microbialites reveals distinct colonization across aquatic ecosystems

Microbial diversity includes bacteria, archaea, eukaryotes, and viruses; however, protists are less studied for their impact and diversity within ecosystems. Protists have been suggested to shape the emergence and decline of ancient stromatolites. Modern microbialites offer a unique proxy to study the deposition of carbonate by microbial communities due to analog status for ancient ecosystems and their cosmopolitan abundance. We examined protists across aquatic ecosystems between freshwater (Kelly and Pavilion Lake in British Columbia, Canada) and marine microbialites (Shark Bay, Australia and Highborne Cay, Bahamas) to decipher the transition with respect to diversity and composition. While factors such as sequencing technology and primer-bias might influence our conclusions, we found that at the taxonomic compositional-level, the freshwater microbialite communities were clearly distinct from the marine microbialite communities. Chlorophytes were significantly more abundant in the freshwater microbialites, while saltwater microbialites communities were primarily composed of pennate diatoms. Despite the differences in taxonomic make-up, we can infer the convergent important role of these protists to microbialite community health and function. These results highlight not only the consistency and potential role of microbialite eukaryotic communities across geographic locations, but also that other factors such as salinity seem to be the main drivers of community composition.

microbiology↗

DeGenPrime provides robust primer design and optimization1 unlocking the biosphere

Polymerase chain reaction (PCR) is the worlds most important molecular diagnostic with applications ranging from medicine to ecology. PCR can fail because of poor primer design. The nearest-neighbor thermodynamic properties, picking conserved regions, and filtration via penalty of oligonucleotides form the basis for good primer design. DeGenPrime is a console-based high quality PCR primer design tool that can utilize MSA formats and degenerate bases expanding target range for a single primer set. Our software utilizes thermodynamic properties, filtration metrics, penalty scoring, and conserved region finding of any proposed primer. It has degeneracy, repeated k-mers, relative GC content, and temperature range filters. Minimal penalty scoring is included according to secondary structure self-dimerization metrics, GC clamping, tri- and tetra-loop hairpins and internal repetition. We compared PrimerDesign-M, DegePrime, ConsensusPrimer, and DeGenPrime on acceptable primer yield. PrimerDesign-M, DegePrime, and ConsensusPrimer provided 0%, 11%, and 17% yield respectively for alternative iron nitrogenase (anfD) gene target. DeGenPrime successfully identified quality primers within the conserved regions of the T4-like phage major capsid protein (g23), conserved regions of molybdenum-based nitrogenase (nif), and its alternatives vanadium (vnf) and iron (anf) nitrogenase. DeGenPrime provides a universal and scalable primer design tool for the entire tree of life.

bioinformatics↗

MetaCerberus: distributed highly parallelized scalable HMM-based implementation for robust functional annotation across the tree of life

SummaryMetaCerberus is an exclusive HMM/HMMER-based tool that is massively parallel, on low memory, and provides rapid scalable annotation for functional gene inference across genomes to metacommunities. It provides robust enumeration of functional genes and pathways across many current public databases including KEGG (KO), COGs, CAZy, FOAM, and viral specific databases (i.e., VOGs and PHROGs). In a direct comparison, MetaCerberus was twice as fast as EggNOG-Mapper, and produced better annotation of viruses, phages, and archaeal viruses than DRAM, PROKKA, or InterProScan. MetaCerberus annotates more KOs across domains when compared to DRAM, with a 186x smaller database and a third less memory. MetaCerberus is fully integrated with differential statistical tools (i.e., DESeq2 and edgeR), pathway enrichment (GAGE R), and Pathview R for quantitative elucidation of metabolic pathways. MetaCerberus implements the key to unlocking the biosphere across the tree of life at scale. Availability and implementationMetaCerberus is written in Python and distributed under a BSD-3 license. The source code of MetaCerberus is freely available at https://github.com/raw-lab/metacerberus. Written in python 3 for both Linux and Mac OS X. MetaCerberus can also be easily installed using mamba create -n metacerberus -c bioconda -c conda-forge metacerberus

bioinformatics↗

Positing changes in neutralizing antibody activity for SARS-CoV-2 XBB.1.5 using in silico protein modeling

The SARS-CoV-2 variant XBB.1.5 is of concern as it has high transmissibility. XBB.1.5 currently accounts for upwards of 30% of new infections in the United States. One year after our group published the predicted structure of the Omicron (B.1.1.529) variants receptor binding domain (RBD) and antibody binding affinity, we return to investigate the new mutations seen in XBB.1.5 which is a descendant of Omicron. Using in silico ico modeling approaches against newer neutralizing antibodies that are shown effective against B.1.1.529, we predict the immune consequences of XBB.1.5s mutations and show that there is no statistically significant difference in overall antibody evasion when comparing to the B.1.1.529 and other related variants (e.g., BJ.1 and BM.1.1.1). However, noticeable changes in antibody binding affinity were seen due to specific amino acid changes of interest in the newer variants.

biochemistry↗

MerCat2: a versatile k-mer counter and diversity estimator for database-independent property analysis obtained from omics data

SummaryMerCat2 ("Mer - Catenate2") is a versatile, parallel, scalable and modular property software package for robustly analyzing features in omics data. Using massively parallel sequencing raw reads, assembled contigs, and protein sequences from any platform as input, MerCat2 performs k-mer counting of any length k, resulting in feature abundance counts tables, quality control reports, protein feature metrics, ecological diversity metrics, and graphical representation (i.e., PCA). MerCat2 allows for direct analysis of data properties in a database-independent manner that initializes all data, which other profilers and assembly-based methods cannot perform. MerCat2 represents an integrated tool to illuminate omics data within a sample for rapid cross-examination and comparisons. Availability and implementationMerCat2 is written in Python and distributed under a BSD-3 license. The source code of MerCat2 is freely available at https://github.com/raw-lab/mercat2. MerCat2 is compatible with Python 3 on Mac OS X and Linux. MerCat2 can also be easily installed using bioconda: conda install MerCat2. ContactRichard Allen White III, UNC Charlotte, rwhit101@uncc.edu Supplementary informationSupplementary data are available online.

bioinformatics↗

Metabolic traits and the niche of bulk soil bacteria in a Mediterranean grassland

Soil microorganisms have adapted to compete and exploit different metabolic niches in their physically and chemically diverse environment via evolution and acquisition of distinct physiological and biochemical traits. As the interface for most carbon and nutrient exchange between plants and microorganisms, the rhizosphere has received substantial attention. By comparison, what is commonly termed bulk-soil (soil free of living roots) represents a far greater volume and surface area throughout the season, and substantially higher taxonomic and phylogenetic diversity; the traits and activity of its inhabitants may also have a significant impact on overall soil function. We used a combination of comparative genomics and exoproteomics to identify metabolic traits of bacteria adapted to life in bulk soil and compared these with traits of bacteria living in the rhizosphere of wild oat, Avena barbata. In bulk soil bacteria, we observed: (i) greater investment in extracellular polymer-degrading enzyme production; (ii) greater potential for secretion (presence of signal peptides) of polymer-degrading enzymes; (iii) production of accessory proteins (carbohydrate binding modules) fused with glycoside hydrolases that enhance substrate affinity, stabilize, and increase reaction rates of polymer degrading enzymes; and (iv) organization of polymer degradation machinery within gene clusters that facilitate co-transcription of enzymes, transcription factors and transporters for polymer depolymerization products. Together, these findings suggest that unlike rhizosphere-adapted bacteria--which specialize on small molecules released primarily as root exudates--bulk soil-adapted bacteria have evolved to exploit plant polymers. This biochemically costly strategy may be mitigated by protein-level adaptations that enhance the efficiency of extracellular enzyme-mediated substrate acquisition. IMPORTANCEPlant-soil-microbe interactions are dynamic and complex, with significant implications for ecosystem functioning. Microbial traits, such as nutrient acquisition and growth yield, combined with soil and climate parameters, impact major biogeochemical processes and can define the future fate of soil carbon. Diverse soil microorganisms occupy different physical habitats within soil and exploit distinct niches by expressing different metabolic traits. Identifying and quantifying traits that underlie their fitness and function is key for understanding and predicting how soil carbon transformation and stabilization will change in the future or can be managed through intervention.

microbiology↗

Microbial dark matter filling the niche in hypersaline microbial mats

Shark Bay, Australia, harbours one of the most extensive and diverse systems of living microbial mats, that are proposed to be analogs of some of the earliest ecosystems on Earth. These ecosystems have been shown to possess a substantial abundance of uncultivable microorganisms. These enigmatic groups - microbial dark matter (MDM) - are hypothesised to play key roles in microbial mats. We reconstructed 115 metagenome-assembled genomes (MAGs) affiliated to MDM, spanning 42 phyla within the bacterial and archaeal domains. We classified bacterial MDM from the PVC group, FCB group, Microgenomates, Parcubacteria, and Peregrinibacteria, as well as a high proportion of archaeal MDM under the TACK, DPANN, Altiarchaeales, and Asgard archaea. The latter includes the first putative Heimdallarchaeota MAG obtained from any microbial mat system. This study reports novel microorganisms (Zixibacterial order GN15) putatively taking part in dissimilatory sulfate reduction in surface hypersaline settings, as well as novel eukaryote signature proteins in the Asgard archaea. Despite possessing reduced-size genomes, the MDM MAGs are capable of fermenting and degrading organic carbon, suggesting a role in recycling organic carbon. Several forms of RuBisCo were identified, allowing putative CO2 incorporation into nucleotide salvaging pathways, which may act as an alternative carbon and phosphorus source. High capacity of hydrogen production was found among Shark Bay MDM. Putative schizorhodopsins were also identified in Parcubacteria, Asgard archaea, DPANN archaea, and Bathyarchaeota, allowing these members to potentially capture light energy. Diversity-generating retroelements were prominent in DPANN archaea that likely facilitate the adaptation to a dynamic, host-dependent lifestyle. In light of our findings, we propose H2, ribose and CO/CO2 as the main energy currencies of the MDM community in these mat systems.

microbiology↗