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This paper reviews publications that have fortified our understanding of the electrowetting-on-dielectric (EWOD) actuation mechanism. Over the last decade, growing interest in EWOD has led to a wide range of scientific and technological investigations motivated by its applicability in microfluidics, especially for droplet-based optical and lab-on-a-chip systems. At this point in time, we believe that it is helpful to summarize the observations, insights, and modeling techniques that have led to the current picture showing how forces act on liquid droplets and how droplets respond in EWOD microfluidic devices. We discuss the basic physics of EWOD and explain the mechanical response of a droplet using free-body diagrams. It is our hope that this review will inspire new research approaches and help design useful devices. © 2012 Copyright Taylor and Francis Group, LLC.

We report here the sequencing and analysis of the genome of the thermophilic bacterium Carboxydothermus hydrogenoformans Z-2901. This species is a model for studies of hydrogenogens, which are diverse bacteria and archaea that grow anaerobically utilizing carbon monoxide (CO) as their sole carbon source and water as an electron acceptor, producing carbon dioxide and hydrogen as waste products. Organisms that make use of CO do so through carbon monoxide dehydrogenase complexes. Remarkably, analysis of the genome of C. hydrogenoformans reveals th e presence of at least five highly differentiated anaerobic carbon monoxide dehydrogenase complexes, which may in part explain how this species is able to grow so much more rapidly on CO than many other species. Analysis of the genome also has provided many general insights into the metabolism of this organism which should make it easier to use it as a source of biologically produced hydrogen gas. One surprising finding is the presence of many genes previously found only in sporulating species in the Firmicutes Phylum. Although this species is also a Firmicutes, it was not known to sporulate previously. Here we show that it does sporulate and because it is missing many of the genes involved in sporulation in other species, this organism may serve as a ''minimal'' model for sporulation studies. In addition, using phylogenetic profile analysis, we have identified many uncharacterized gene families found in all known sporulating Firmicutes, but not in any non-sporulating bacteria, including a sigma factor not known to be involved in sporulation previously. Copyright: ©2005 Wu et al.

Aims/hypothesis: The aim of this work was to explore molecular amino acids (AAs) and related structures of HLA-DQA1-DQB1 that underlie its contribution to the progression from stages 1 or 2 to stage 3 type 1 diabetes., Methods: Using high-resolution DQA1 and DQB1 genotypes from 1216 participants in the Diabetes Prevention Trial-Type 1 and the Diabetes Prevention Trial, we applied hierarchically organised haplotype association analysis (HOH) to decipher which AAs contributed to the associations of DQ with disease and their structural properties. HOH relied on the Cox regression to quantify the association of DQ with time-to-onset of type 1 diabetes., Results: By numerating all possible DQ heterodimers of α- and β-chains, we showed that the heterodimerisation increases genetic diversity at the cellular level from 43 empirically observed haplotypes to 186 possible heterodimers. Heterodimerisation turned several neutral haplotypes (DQ2.2, DQ2.3 and DQ4.4) to risk haplotypes (DQ2.2/2.3-DQ4.4 and DQ4.4-DQ2.2). HOH uncovered eight AAs on the α-chain (-16α, -13α, -6α, α22, α23, α44, α72, α157) and six AAs on the β-chain (-18β, β9, β13, β26, β57, β135) that contributed to the association of DQ with progression of type 1 diabetes. The specific AAs concerned the signal peptide (minus sign, possible linkage to expression levels), pockets 1, 4 and 9 in the antigen-binding groove of the α1β1 domain, and the putative homodimerisation of the αβ heterodimers., Conclusions/interpretation: These results unveil the contribution made by DQ to type 1 diabetes progression at individual residues and related protein structures, shedding light on its immunological mechanisms and providing new leads for developing treatment strategies., Data Availability: Clinical trial data and biospecimen samples are available through the National Institute of Diabetes and Digestive and Kidney Diseases Central Repository portal ( https://repository.niddk.nih.gov/studies )., (© 2024. The Author(s).)

Interactions between plants and soil microbial communities that benefit plant growth and enhance nutrient acquisition are driven by the selective release of metabolites from plant roots, or root exudation. To investigate these plant-microbe interactions, we developed a photoaffinity probe based on sorgoleone ( so rgoleone d iazirine a lkyne for p hoto a ffinity l abeling, SoDA-PAL), a hydrophobic secondary metabolite and allelochemical produced in Sorghum bicolor root exudates. We applied SoDA-PAL to the identification of sorgoleone-binding proteins in Acinetobacter pittii SO1, a potential plant growth-promoting microbe isolated from sorghum rhizosphere soil. Competitive photoaffinity labeling of A. pittii whole cell lysates with SoDA-PAL identified 137 statistically enriched proteins, including putative transporters, transcriptional regulators, and a subset of proteins with predicted enzymatic functions. We performed computational protein modeling and docking with sorgoleone to prioritize candidates for experimental validation and then confirmed binding of sorgoleone to four of these proteins in vitro : the α/β fold hydrolase SrgB (OH685_09420), a fumarylacetoacetase (OH685_02300), a lysophospholipase (OH685_14215), and an unannotated hypothetical protein (OH685_18625). Our application of this specialized sorgoleone-based probe coupled with structural bioinformatics streamlines the identification of microbial proteins involved in metabolite recognition, metabolism, and toxicity, widening our understanding of the range of cellular pathways that can be affected by a plant secondary metabolite.IMPORTANCEHere, we demonstrate that a photoaffinity-based chemical probe modeled after sorgoleone, an important secondary metabolite released by sorghum roots, can be used to identify microbial proteins that directly interact with sorgoleone. We applied this probe to the sorghum-associated bacterium Acinetobacter pittii and showed that probe labeling is dose-dependent and sensitive to competition with purified sorgoleone. Coupling the probe with proteomics and computational analysis facilitated the identification of putative sorgoleone binders, including a protein implicated in a conserved pathway essential for sorgoleone catabolism. We anticipate that discoveries seeded by this workflow will expand our understanding of the molecular mechanisms by which specific metabolites in root exudates shape the sorghum rhizosphere microbiome., Competing Interests: The authors declare no conflict of interest.

Objective: To explore if oral insulin could delay onset of stage 3 type 1 diabetes (T1D) among patients with stage 1/2 who carry HLA DR4-DQ8 and/or have elevated levels of IA-2 autoantibodies (IA-2As)., Research and Methods: Next-generation targeted sequencing technology was used to genotype eight HLA class II genes (DQA1, DQB1, DRB1, DRB3, DRB4, DRB5, DPA1, and DPB1) in 546 participants in the TrialNet oral insulin preventative trial (TN07). Baseline levels of autoantibodies against insulin (IAA), GAD65 (GADA), and IA-2A were determined prior to treatment assignment. Available clinical and demographic covariables from TN07 were used in this post hoc analysis with the Cox regression model to quantify the preventive efficacy of oral insulin., Results: Oral insulin reduced the frequency of T1D onset among participants with elevated IA-2A levels (HR 0.62; P = 0.012) but had no preventive effect among those with low IA-2A levels (HR 1.03; P = 0.91). High IA-2A levels were positively associated with the HLA DR4-DQ8 haplotype (OR 1.63; P = 6.37 × 10-6) and negatively associated with the HLA DR7-containing DRB1*07:01-DRB4*01:01-DQA1*02:01-DQB1*02:02 extended haplotype (OR 0.49; P = 0.037). Among DR4-DQ8 carriers, oral insulin delayed the progression toward stage 3 T1D onset (HR 0.59; P = 0.027), especially if participants also had high IA-2A level (HR 0.50; P = 0.028)., Conclusions: These results suggest the presence of a T1D endotype characterized by HLA DR4-DQ8 and/or elevated IA-2A levels; for those patients with stage 1/2 disease with such an endotype, oral insulin delays the clinical T1D onset., (© 2024 by the American Diabetes Association.)

Objective: To explore associations of HLA class II genes (HLAII) with the progression of islet autoimmunity from asymptomatic to symptomatic type 1 diabetes (T1D)., Research Design and Methods: Next-generation targeted sequencing was used to genotype eight HLAII genes (DQA1, DQB1, DRB1, DRB3, DRB4, DRB5, DPA1, DPB1) in 1,216 participants from the Diabetes Prevention Trial-1 and Randomized Diabetes Prevention Trial with Oral Insulin sponsored by TrialNet. By the linkage disequilibrium, DQA1 and DQB1 are haplotyped to form DQ haplotypes; DP and DR haplotypes are similarly constructed. Together with available clinical covariables, we applied the Cox regression model to assess HLAII immunogenic associations with the disease progression., Results: First, the current investigation updated the previously reported genetic associations of DQA1*03:01-DQB1*03:02 (hazard ratio [HR] = 1.25, P = 3.50*10-3) and DQA1*03:03-DQB1*03:01 (HR = 0.56, P = 1.16*10-3), and also uncovered a risk association with DQA1*05:01-DQB1*02:01 (HR = 1.19, P = 0.041). Second, after adjusting for DQ, DPA1*02:01-DPB1*11:01 and DPA1*01:03-DPB1*03:01 were found to have opposite associations with progression (HR = 1.98 and 0.70, P = 0.021 and 6.16*10-3, respectively). Third, DRB1*03:01-DRB3*01:01 and DRB1*03:01-DRB3*02:02, sharing the DRB1*03:01, had opposite associations (HR = 0.73 and 1.44, P = 0.04 and 0.019, respectively), indicating a role of DRB3. Meanwhile, DRB1*12:01-DRB3*02:02 and DRB1*01:03 alone were found to associate with progression (HR = 2.6 and 2.32, P = 0.018 and 0.039, respectively). Fourth, through enumerating all heterodimers, it was found that both DQ and DP could exhibit associations with disease progression., Conclusions: These results suggest that HLAII polymorphisms influence progression from islet autoimmunity to T1D among at-risk subjects with islet autoantibodies., (© 2024 by the American Diabetes Association.)

Bacteriophages are abundant in soils. However, the majority are uncharacterized, and their hosts are unknown. Here, we apply high-throughput chromosome conformation capture (Hi-C) to directly capture phage-host relationships. Some hosts have high centralities in bacterial community co-occurrence networks, suggesting phage infections have an important impact on the soil bacterial community interactions. We observe increased average viral copies per host (VPH) and decreased viral transcriptional activity following a two-week soil-drying incubation, indicating an increase in lysogenic infections. Soil drying also alters the observed phage host range. A significant negative correlation between VPH and host abundance prior to drying indicates more lytic infections result in more host death and inversely influence host abundance. This study provides empirical evidence of phage-mediated bacterial population dynamics in soil by directly capturing specific phage-host interactions., (© 2023. Battelle Memorial Institute.)

Motivation: The vast expansion of sequence data generated from single organisms and microbiomes has precipitated the need for faster and more sensitive methods to assess evolutionary and functional relationships between proteins. Representing proteins as sets of short peptide sequences (kmers) has been used for rapid, accurate classification of proteins into functional categories; however, this approach employs an exact-match methodology and thus may be limited in terms of sensitivity and coverage. We have previously used similarity groupings, based on the chemical properties of amino acids, to form reduced character sets and recode proteins. This amino acid recoding (AAR) approach simplifies the construction of protein representations in the form of kmer vectors, which can link sequences with distant sequence similarity and provide accurate classification of problematic protein families., Results: Here, we describe Snekmer, a software tool for recoding proteins into AAR kmer vectors and performing either (i) construction of supervised classification models trained on input protein families or (ii) clustering for de novo determination of protein families. We provide examples of the operation of the tool against a set of nitrogen cycling families originally collected using both standard hidden Markov models and a larger set of proteins from Uniprot and demonstrate that our method accurately differentiates these sequences in both operation modes., Availability and Implementation: Snekmer is written in Python using Snakemake. Code and data used in this article, along with tutorial notebooks, are available at http://github.com/PNNL-CompBio/Snekmer under an open-source BSD-3 license., Supplementary Information: Supplementary data are available at Bioinformatics Advances online., (© The Author(s) 2023. Published by Oxford University Press.)

Soil fungi facilitate the translocation of inorganic nutrients from soil minerals to other microorganisms and plants. This ability is particularly advantageous in impoverished soils because fungal mycelial networks can bridge otherwise spatially disconnected and inaccessible nutrient hot spots. However, the molecular mechanisms underlying fungal mineral weathering and transport through soil remains poorly understood primarily due to the lack of a platform for spatially resolved analysis of biotic-driven mineral weathering. Here, we addressed this knowledge gap by demonstrating a mineral-doped soil micromodel platform where mineral weathering mechanisms can be studied. We directly visualize acquisition and transport of inorganic nutrients from minerals through fungal hyphae in the micromodel using a multimodal imaging approach. We found that Fusarium sp. strain DS 682, a representative of common saprotrophic soil fungus, exhibited a mechanosensory response (thigmotropism) around obstacles and through pore spaces (~12 μm) in the presence of minerals. The fungus incorporated and translocated potassium (K) from K-rich mineral interfaces, as evidenced by visualization of mineral-derived nutrient transport and unique K chemical moieties following fungus-induced mineral weathering. Specific membrane transport proteins were expressed in the fungus in the presence of minerals, including those involved in oxidative phosphorylation pathways and the transmembrane transport of small-molecular-weight organic acids. This study establishes the significance of a spatial visualization platform for investigating microbial induced mineral weathering at microbially relevant scales. Moreover, we demonstrate the importance of fungal biology and nutrient translocation in maintaining fungal growth under water and carbon limitations in a reduced-complexity soil-like microenvironment. IMPORTANCE Fungal species are foundational members of soil microbiomes, where their contributions in accessing and transporting vital nutrients is key for community resilience. To date, the molecular mechanisms underlying fungal mineral weathering and nutrient translocation in low-nutrient environments remain poorly resolved due to the lack of a platform for spatial analysis of biotic weathering processes. Here, we addressed this knowledge gap by developing a mineral-doped soil micromodel platform. We demonstrate the function of this platform by directly probing fungal growth using spatially resolved optical and chemical imaging methodologies. We found the presence of minerals was required for fungal thigmotropism around obstacles and through soil-like pore spaces, and this was related to fungal transport of potassium (K) and corresponding K speciation from K-rich minerals. These findings provide new evidence and visualization into hyphal transport of mineral-derived nutrients under nutrient and water stresses.

Co-infections or secondary infections with SARS-CoV-2 have the potential to affect disease severity and morbidity. Additionally, the potential influence of the nasal microbiome on COVID-19 illness is not well understood. In this study, we analyzed 203 residual samples, originally submitted for SARS-CoV-2 testing, for the presence of viral, bacterial, and fungal pathogens and non-pathogens using a comprehensive microarray technology, the Lawrence Livermore Microbial Detection Array (LLMDA). Eighty-seven percent of the samples were nasopharyngeal samples, and 23% of the samples were oral, nasal and oral pharyngeal swabs. We conducted bioinformatics analyses to examine differences in microbial populations of these samples, as a proxy for the nasal and oral microbiome, from SARS-CoV-2 positive and negative specimens. We found 91% concordance with the LLMDA relative to a diagnostic RT-qPCR assay for detection of SARS-CoV-2. Sixteen percent of all the samples (32/203) revealed the presence of an opportunistic bacterial or frank viral pathogen with the potential to cause co-infections. The two most detected bacteria, Streptococcus pyogenes and Streptococcus pneumoniae, were present in both SARS-CoV-2 positive and negative samples. Human metapneumovirus was the most prevalent viral pathogen in the SARS-CoV-2 negative samples. Sequence analysis of 16S rRNA was also conducted to evaluate bacterial diversity and confirm LLMDA results., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Thissen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Dogs have served as one of the most reliable preclinical models for a variety of diseases and treatments, including stem/progenitor cell transplantation. At the genetic epicenter of dog transplantation models, polymorphic major histocompatibility complex (MHC) genes are most impactful on transplantation success. Among the canine class I and class II genes, DLA-88 has been best studied in transplantation matching and outcomes, with 129 DLA-88 alleles identified. In this study we developed and tested a next generation (NGS) sequencing protocol for rapid identification of DLA-88 genotypes in dogs and compared the workflow and data generated with an established DLA-88 Sanger sequencing protocol that has been in common prior use for clinical studies. By testing the NGS protocol on a random population of 382 dogs, it was possible to demonstrate superior efficacy based on laboratory execution and overall cost. In addition, NGS proved far more effective at discovering new alleles and detecting multiple alleles associated with gene duplication. A total of 51 new DLA-88 alleles are reported here. This rate of new allele discovery indicates that a large pool of yet un-discovered DLA-88 alleles exists in the domestic dog population. In addition, more than 46% of dogs carried three or more copies of DLA-88, further emphasizing the need for more sensitive and cost-effective DLA typing methodology for the dog clinical model., (© 2022 The Authors. HLA: Immune Response Genetics published by John Wiley & Sons Ltd.)

Over the last 25 years, biology has entered the genomic era and is becoming a science of 'big data'. Most interpretations of genomic analyses rely on accurate functional annotations of the proteins encoded by more than 500 000 genomes sequenced to date. By different estimates, only half the predicted sequenced proteins carry an accurate functional annotation, and this percentage varies drastically between different organismal lineages. Such a large gap in knowledge hampers all aspects of biological enterprise and, thereby, is standing in the way of genomic biology reaching its full potential. A brainstorming meeting to address this issue funded by the National Science Foundation was held during 3-4 February 2022. Bringing together data scientists, biocurators, computational biologists and experimentalists within the same venue allowed for a comprehensive assessment of the current state of functional annotations of protein families. Further, major issues that were obstructing the field were identified and discussed, which ultimately allowed for the proposal of solutions on how to move forward., (© The Author(s) 2022. Published by Oxford University Press.)

Development of profiling strategies to provide high resolution understanding of enzymes involved in bacterial infections remains an important need. These strategies help resolve enzyme mechanisms of actions and can guide therapeutic development. We have developed a selective new activity-based probe (ABP) targeting a highly conserved surface bound enzyme, C5a peptidase, present in several pathogenic Streptococci . We demonstrate our probe inhibits C5a peptidase activity and enables detection of C5a peptidase expressing pathogens in microbial mixtures. Our profiling strategy selectively labels the pathogen by phenotype and enables specific isolation of the live bacteria providing a route for further in-depth investigation. This study paves the way towards a rapid detection, isolation, and characterization pipeline for existing and emerging strains of most common pathogenic Streptococci .

Objective: The purpose was to test the hypothesis that the HLA-DQαβ heterodimer structure is related to the progression of islet autoimmunity from asymptomatic to symptomatic type 1 diabetes (T1D)., Research Design and Methods: Next-generation targeted sequencing was used to genotype HLA-DQA1-B1 class II genes in 670 subjects in the Diabetes Prevention Trial-Type 1 (DPT-1). Coding sequences were translated into DQ α- and β-chain amino acid residues and used in hierarchically organized haplotype (HOH) association analysis to identify motifs associated with diabetes onset., Results: The opposite diabetes risks were confirmed for HLA DQA1*03:01-B1*03:02 (hazard ratio [HR] 1.36; P = 2.01 ∗ 10-3) and DQA1*03:03-B1*03:01 (HR 0.62; P = 0.037). The HOH analysis uncovered residue -18β in the signal peptide and β57 in the β-chain to form six motifs. DQ*VA was associated with faster (HR 1.49; P = 6.36 ∗ 10-4) and DQ*AD with slower (HR 0.64; P = 0.020) progression to diabetes onset. VA/VA, representing DQA1*03:01-B1*03:02 (DQ8/8), had a greater HR of 1.98 (P = 2.80 ∗ 10-3). The DQ*VA motif was associated with both islet cell antibodies (P = 0.023) and insulin autoantibodies (IAAs) (P = 3.34 ∗ 10-3), while the DQ*AD motif was associated with a decreased IAA frequency (P = 0.015). Subjects with DQ*VA and DQ*AD experienced, respectively, increasing and decreasing trends of HbA1c levels throughout the follow-up., Conclusions: HLA-DQ structural motifs appear to modulate progression from islet autoimmunity to diabetes among at-risk relatives with islet autoantibodies. Residue -18β within the signal peptide may be related to levels of protein synthesis and β57 to stability of the peptide-DQab trimolecular complex., (© 2022 by the American Diabetes Association.)

SARS-CoV-2 is spreading worldwide with continuously evolving variants, some of which occur in the Spike protein and appear to increase viral transmissibility. However, variants that cause severe COVID-19 or lead to other breakthroughs have not been well characterized. To discover such viral variants, we assembled a cohort of 683 COVID-19 patients; 388 inpatients ("cases") and 295 outpatients ("controls") from April to August 2020 using electronically captured COVID test request forms and sequenced their viral genomes. To improve the analytical power, we accessed 7137 viral sequences in Washington State to filter out viral single nucleotide variants (SNVs) that did not have significant expansions over the collection period. Applying this filter led to the identification of 53 SNVs that were statistically significant, of which 13 SNVs each had 3 or more variant copies in the discovery cohort. Correlating these selected SNVs with case/control status, eight SNVs were found to significantly associate with inpatient status (q-values < 0.01). Using temporal synchrony, we identified a four SNV-haplotype (t19839-g28881-g28882-g28883) that was significantly associated with case/control status (Fisher's exact p = 2.84 × 10 -11 ). This haplotype appeared in April 2020, peaked in June, and persisted into January 2021. The association was replicated (OR = 5.46, p-value = 4.71 × 10 -12 ) in an independent cohort of 964 COVID-19 patients (June 1, 2020 to March 31, 2021). The haplotype included a synonymous change N73N in endoRNase, and three non-synonymous changes coding residues R203K, R203S and G204R in the nucleocapsid protein. This discovery points to the potential functional role of the nucleocapsid protein in triggering "cytokine storms" and severe COVID-19 that led to hospitalization. The study further emphasizes a need for tracking and analyzing viral sequences in correlations with clinical status., (© 2022. The Author(s).)

Soil viruses are abundant, but the influence of the environment and climate on soil viruses remains poorly understood. Here, we addressed this gap by comparing the diversity, abundance, lifestyle, and metabolic potential of DNA viruses in three grassland soils with historical differences in average annual precipitation, low in eastern Washington (WA), high in Iowa (IA), and intermediate in Kansas (KS). Bioinformatics analyses were applied to identify a total of 2,631 viral contigs, including 14 complete viral genomes from three deep metagenomes (1 terabase [Tb] each) that were sequenced from bulk soil DNA. An additional three replicate metagenomes (∼0.5 Tb each) were obtained from each location for statistical comparisons. Identified viruses were primarily bacteriophages targeting dominant bacterial taxa. Both viral and host diversity were higher in soil with lower precipitation. Viral abundance was also significantly higher in the arid WA location than in IA and KS. More lysogenic markers and fewer clustered regularly interspaced short palindromic repeats (CRISPR) spacer hits were found in WA, reflecting more lysogeny in historically drier soil. More putative auxiliary metabolic genes (AMGs) were also detected in WA than in the historically wetter locations. The AMGs occurring in 18 pathways could potentially contribute to carbon metabolism and energy acquisition in their hosts. Structural equation modeling (SEM) suggested that historical precipitation influenced viral life cycle and selection of AMGs. The observed and predicted relationships between soil viruses and various biotic and abiotic variables have value for predicting viral responses to environmental change. IMPORTANCE Soil viruses are abundant but poorly understood. Because soil viruses regulate the dynamics of their hosts and potentially key processes in soil ecology, it is important to understand them better. Here, we leveraged massive DNA sequencing to unearth previously unknown soil viruses. We found that soil viruses differed across a historical gradient of precipitation. We compared soil viruses from Iowa, which is traditionally wetter, to those from Washington, which is traditionally drier, and from Kansas, which is intermediate. This study provides strong evidence that changes in historical precipitation impact not only the types of soil viruses but also their functional potential.

Lipids play a fundamental role in fungal cell biology, being essential cell membrane components and major targets of antifungal drugs. A deeper knowledge of lipid metabolism is key for developing new drugs and a better understanding of fungal pathogenesis. Here, we built a comprehensive map of the Histoplasma capsulatum lipid metabolic pathway by incorporating proteomic and lipidomic analyses. We performed genetic complementation and overexpression of H. capsulatum genes in Saccharomyces cerevisiae to validate reactions identified in the map and to determine enzymes responsible for catalyzing orphan reactions. The map led to the identification of both the fatty acid desaturation and the sphingolipid biosynthesis pathways as targets for drug development. We found that the sphingolipid biosynthesis inhibitor myriocin, the fatty acid desaturase inhibitor thiocarlide, and the fatty acid analog 10-thiastearic acid inhibit H. capsulatum growth in nanomolar to low-micromolar concentrations. These compounds also reduced the intracellular infection in an alveolar macrophage cell line. Overall, this lipid metabolic map revealed pathways that can be targeted for drug development. IMPORTANCE It is estimated that 150 people die per hour due to the insufficient therapeutic treatments to combat fungal infections. A major hurdle to developing antifungal therapies is the scarce knowledge on the fungal metabolic pathways and mechanisms of virulence. In this context, fungal lipid metabolism is an excellent candidate for developing drugs due to its essential roles in cellular scaffolds, energy storage, and signaling transductors. Here, we provide a detailed map of Histoplasma capsulatum lipid metabolism. The map revealed points of this fungus lipid metabolism that can be targeted for developing antifungal drugs.

Background: HLA-DR4, a common antigen of HLA-DRB1, has multiple subtypes that are strongly associated with risk of type 1 diabetes (T1D); however, some are risk neutral or resistant. The pathobiological mechanism of HLA-DR4 subtypes remains to be elucidated., Methods: We used a population-based case-control study of T1D (962 patients and 636 controls) to decipher genetic associations of HLA-DR4 subtypes and specific residues with susceptibility to T1D. Using a birth cohort of 7865 children with periodically measured islet autoantibodies (GADA, IAA or IA-2A), we proposed to validate discovered genetic associations with a totally different study design and time-to-seroconversions prior to clinical onset of T1D. A novel analytic strategy hierarchically organized the HLA-DRB1 alleles by sequence similarity and identified critical amino acid residues by minimizing local genomic architecture and higher-order interactions., Findings: Three amino acid residues of HLA-DRB1 (β71, β74, β86) were found to be predictive of T1D risk in the population-based study. The "KAG" motif, corresponding to HLA-DRB1×04:01, was most strongly associated with T1D risk ([O]dds [R]atio=3.64, p = 3.19 × 10 -64 ). Three less frequent motifs ("EAV", OR = 2.55, p = 0.025; "RAG", OR = 1.93, p = 0.043; and "RAV", OR = 1.56, p = 0.003) were associated with T1D risk, while two motifs ("REG" and "REV") were equally protective (OR = 0.11, p = 4.23 × 10 -4 ). In an independent birth cohort of HLA-DR3 and HLA-DR4 subjects, those having the "KAG" motif had increased risk for time-to-seroconversion (Hazard Ratio = 1.74, p = 6.51 × 10 -14 ) after adjusting potential confounders., Interpretations: DNA sequence variation in HLA-DRB1 at positions β71, β74, and β86 are non-conservative (β74 A→E, β71 E vs K vs R and β86 G vs V). They result in substantial differences in peptide antigen anchor pocket preferences at p1, p4 and potentially neighboring regions such as pocket p7. Differential peptide antigen binding is likely to be affected. These sequence substitutions may account for most of the HLA-DR4 contribution to T1D risk as illustrated in two HLA-peptide model complexes of the T1D autoantigens preproinsulin and GAD65., Funding: National Institute of Diabetes and Digestive and Kidney Diseases and the Swedish Child Diabetes Foundation and the Swedish Research Council., Competing Interests: Declaration of Competing Interest Dr. Claude Marcus receives personal fees from Novo Nordisk and there are no other conflicts of interest relevant to this article. Other authors report no conflict of interest., (Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)

The novel fungal strain, Fusarium sp. strain DS 682, was isolated from the rhizosphere of the perennial grass, Bouteloua gracilis , at the Konza Prairie Biological Station in Kansas. This fungal strain is common across North American grasslands and is resilient to environmental fluctuations. The draft genome is estimated to be 97.2% complete., (Copyright © 2021 Bhattacharjee et al.)

Background: Crohn's disease (CD) is a chronic inflammatory intestinal disorder associated with intestinal dysbiosis. Diet modulates the intestinal microbiome and therefore has a therapeutic potential. The aim of this study is to determine the potential efficacy of three versions of the specific carbohydrate diet (SCD) in active Crohn's Disease., Methods: 18 patients with mild/moderate CD (PCDAI 15-45) aged 7 to 18 years were enrolled. Patients were randomized to either SCD, modified SCD(MSCD) or whole foods (WF) diet. Patients were evaluated at baseline, 2, 4, 8 and 12 weeks. PCDAI, inflammatory labs and multi-omics evaluations were assessed., Results: Mean age was 14.3 ± 2.9 years. At week 12, all participants (n = 10) who completed the study achieved clinical remission. The C-reactive protein decreased from 1.3 ± 0.7 at enrollment to 0.9 ± 0.5 at 12 weeks in the SCD group. In the MSCD group, the CRP decreased from 1.6 ± 1.1 at enrollment to 0.7 ± 0.1 at 12 weeks. In the WF group, the CRP decreased from 3.9 ± 4.3 at enrollment to 1.6 ± 1.3 at 12 weeks. In addition, the microbiome composition shifted in all patients across the study period. While the nature of the changes was largely patient specific, the predicted metabolic mode of the organisms increasing and decreasing in activity was consistent across patients., Conclusions: This study emphasizes the impact of diet in CD. Each diet had a positive effect on symptoms and inflammatory burden; the more exclusionary diets were associated with a better resolution of inflammation.

HLA-DQA1 and -DQB1 genes have significant and potentially causal associations with autoimmune type 1 diabetes (T1D). To follow up on the earlier analysis on high-risk HLA-DQ2.5 and DQ8.1, the current analysis uncovers seven residues (αa1, α157, α196, β9, β30, β57, and β70) that are resistant to T1D among subjects with DQ4-, 5-, 6-, and 7 -resistant DQ haplotypes. These 7 residues form 13 common motifs: 6 motifs are significantly resistant, 6 motifs have modest or no associations ( P values >0.05), and 1 motif has 7 copies observed among control subjects only. The motifs "DAAFYDG," "DAAYHDG," and "DAAYYDR" have significant resistance to T1D (odds ratios [ORs] 0.03, 0.25, and 0.18; P = 6.11 × 10 -24 , 3.54 × 10 -15 , and 1.03 × 10 -21 , respectively). Remarkably, a change of a single residue from the motif "DAAYHDG" to "DAAYHSG" (D to S at β57) alters the resistance potential, from resistant motif (OR 0.15; P = 3.54 × 10 -15 ) to a neutral motif ( P = 0.183), the change of which was significant (Fisher P value = 0.0065). The extended set of linked residues associated with T1D resistance and unique to each cluster of HLA-DQ haplotypes represents facets of all known features and functions of these molecules: antigenic peptide binding, peptide-MHC class II complex stability, β167-169 RGD loop, T-cell receptor binding, formation of homodimer of α-β heterodimers, and cholesterol binding in the cell membrane rafts. Identification of these residues is a novel understanding of resistant DQ associations with T1D. Our analyses endow potential molecular approaches to identify immunological mechanisms that control disease susceptibility or resistance to provide novel targets for immunotherapeutic strategies., (© 2020 by the American Diabetes Association.)

Background: Advances in sequencing, assembly, and assortment of contigs into species-specific bins has enabled the reconstruction of genomes from metagenomic data (MAGs). Though a powerful technique, it is difficult to determine whether assembly and binning techniques are accurate when applied to environmental metagenomes due to a lack of complete reference genome sequences against which to check the resulting MAGs., Methods: We compared MAGs derived from an enrichment culture containing ~20 organisms to complete genome sequences of 10 organisms isolated from the enrichment culture. Factors commonly considered in binning software-nucleotide composition and sequence repetitiveness-were calculated for both the correctly binned and not-binned regions. This direct comparison revealed biases in sequence characteristics and gene content in the not-binned regions. Additionally, the composition of three public data sets representing MAGs reconstructed from the Tara Oceans metagenomic data was compared to a set of representative genomes available through NCBI RefSeq to verify that the biases identified were observable in more complex data sets and using three contemporary binning software packages., Results: Repeat sequences were frequently not binned in the genome reconstruction processes, as were sequence regions with variant nucleotide composition. Genes encoded on the not-binned regions were strongly biased towards ribosomal RNAs, transfer RNAs, mobile element functions and genes of unknown function. Our results support genome reconstruction as a robust process and suggest that reconstructions determined to be >90% complete are likely to effectively represent organismal function; however, population-level genotypic heterogeneity in natural populations, such as uneven distribution of plasmids, can lead to incorrect inferences., Competing Interests: The authors declare that they have no competing interests., (© 2020 Nelson et al.)

Predictive biogeochemical modeling requires data-model integration that enables explicit representation of the sophisticated roles of microbial processes that transform substrates. Data from high-resolution organic matter (OM) characterization are increasingly available and can serve as a critical resource for this purpose, but their incorporation into biogeochemical models is often prohibited due to an over-simplified description of reaction networks. To fill this gap, we proposed a new concept of biogeochemical modeling-termed substrate-explicit modeling -that enables parameterizing OM-specific oxidative degradation pathways and reaction rates based on the thermodynamic properties of OM pools. Based on previous developments in the literature, we characterized the resulting kinetic models by only two parameters regardless of the complexity of OM profiles, which can greatly facilitate the integration with reactive transport models for ecosystem simulations by alleviating the difficulty in parameter identification. The two parameters include maximal growth rate (μ max ) and harvest volume (V h ) (i.e., the volume that a microbe can access for harvesting energy). For every detected organic molecule in a given sample, our approach provides a systematic way to formulate reaction kinetics from chemical formula, which enables the evaluation of the impact of OM character on biogeochemical processes across conditions. In a case study of two sites with distinct OM thermodynamics using ultra high-resolution metabolomics datasets derived from Fourier transform ion cyclotron resonance mass spectrometry analyses, our method predicted how oxidative degradation is primarily driven by thermodynamic efficiency of OM consistent with experimental rate measurements (as shown by correlation coefficients of up to 0.61), and how biogeochemical reactions can vary in response to carbon and/or oxygen limitations. Lastly, we showed that incorporation of enzymatic regulations into substrate-explicit models is critical for more reasonable predictions. This result led us to present integrative biogeochemical modeling as a unifying framework that can ideally describe the dynamic interplay among microbes, enzymes, and substrates to address advanced questions and hypotheses in future studies. Altogether, the new modeling concept we propose in this work provides a foundational platform for unprecedented predictions of biogeochemical and ecosystem dynamics through enhanced integration with diverse experimental data and extant modeling approaches., (Copyright © 2020 Song, Stegen, Graham, Lee, Garayburu-Caruso, Nelson, Chen, Moulton and Scheibe.)

To enable an in-depth survey of the metabolic potential of complex soil microbiomes, we performed ultra-deep metagenome sequencing, collecting >1 Tb of sequence data from three grassland soils representing different precipitation regimes., (Copyright © 2020 Nelson et al.)

The soil microbiome represents one of the most complex microbial communities on the planet, encompassing thousands of taxa and metabolic pathways, rendering holistic analyses computationally intensive and difficult. Here, we developed an alternative approach in which the complex soil microbiome was broken into components ("functional modules"), based on metabolic capacities, for individual characterization. We hypothesized that reproducible, low-complexity communities that represent functional modules could be obtained through targeted enrichments and that, in combination, they would encompass a large extent of the soil microbiome diversity. Enrichments were performed on a starting soil inoculum with defined media based on specific carbon substrates, antibiotics, alternative electron acceptors under anaerobic conditions, or alternative growing conditions reflective of common field stresses. The resultant communities were evaluated through 16S rRNA amplicon sequencing. Less permissive modules (anaerobic conditions, complex polysaccharides, and certain stresses) resulted in more distinct community profiles with higher richness and more variability between replicates, whereas modules with simple substrates were dominated by fewer species and were more reproducible. Collectively, approximately 27% of unique taxa present in the liquid soil extract control were found across functional modules. Taxa that were underrepresented or undetected in the source soil were also enriched across the modules. Metatranscriptomic analyses were carried out on a subset of the modules to investigate differences in functional gene expression. These results demonstrate that by dissecting the soil microbiome into discrete components it is possible to obtain a more comprehensive view of the soil microbiome and its biochemical potential than would be possible using more holistic analyses. IMPORTANCE The taxonomic and functional diversity inherent to the soil microbiome complicate assessments of the metabolic potential carried out by the community members. An alternative approach is to break down the soil microbiome into reduced-complexity subsets based on metabolic capacities (functional modules) prior to sequencing and analysis. Here, we demonstrate that this approach successfully identified specific phylogenetic and biochemical traits of the soil microbiome that otherwise remained hidden from a more top-down analysis.

HLA-DQA1 and -DQB1 are strongly associated with type 1 diabetes (T1D), and DQ8.1 and DQ2.5 are major risk haplotypes. Next-generation targeted sequencing of HLA-DQA1 and -DQB1 in Swedish newly diagnosed 1- to 18 year-old patients ( n = 962) and control subjects ( n = 636) was used to construct abbreviated DQ haplotypes, converted into amino acid (AA) residues, and assessed for their associations with T1D. A hierarchically organized haplotype (HOH) association analysis allowed 45 unique DQ haplotypes to be categorized into seven clusters. The DQ8/9 cluster included two DQ8.1 risk and the DQ9 resistant haplotypes, and the DQ2 cluster included the DQ2.5 risk and DQ2.2 resistant haplotypes. Within each cluster, HOH found residues α44Q (odds ratio [OR] 3.29, P = 2.38 * 10 -85 ) and β57A (OR 3.44, P = 3.80 * 10 -84 ) to be associated with T1D in the DQ8/9 cluster representing all ten residues (α22, α23, α44, α49, α51, α53, α54, α73, α184, β57) due to complete linkage disequilibrium (LD) of α44 with eight such residues. Within the DQ2 cluster and due to LD, HOH analysis found α44C and β135D to share the risk for T1D (OR 2.10, P = 1.96 * 10 -20 ). The motif "QAD" of α44, β57, and β135 captured the T1D risk association of DQ8.1 (OR 3.44, P = 3.80 * 10 -84 ), and the corresponding motif "CAD" captured the risk association of DQ2.5 (OR 2.10, P = 1.96 * 10 -20 ). Two risk associations were related to GAD65 autoantibody (GADA) and IA-2 autoantibody (IA-2A) but in opposite directions. CAD was positively associated with GADA (OR 1.56, P = 6.35 * 10 -8 ) but negatively with IA-2A (OR 0.59, P = 6.55 * 10 -11 ). QAD was negatively associated with GADA (OR 0.88; P = 3.70 * 10 -3 ) but positively with IA-2A (OR 1.64; P = 2.40 * 10 -14 ), despite a single difference at α44. The residues are found in and around anchor pockets 1 and 9, as potential T-cell receptor contacts, in the areas for CD4 binding and putative homodimer formation. The identification of three HLA-DQ AAs (α44, β57, β135) conferring T1D risk should sharpen functional and translational studies., (© 2020 by the American Diabetes Association.)

Biodiversity is thought to prevent decline in community function in response to changing environmental conditions through replacement of organisms with similar functional capacity but different optimal growth characteristics. We examined how this concept translates to the within-gene level by exploring seasonal dynamics of within-gene diversity for genes involved in nitrogen cycling in hyporheic zone communities. Nitrification genes displayed low richness-defined as the number of unique within-gene phylotypes-across seasons. Conversely, denitrification genes varied in both richness and the degree to which phylotypes were recruited or lost. These results demonstrate that there is not a universal mechanism for maintaining community functional potential for nitrogen cycling activities, even across seasonal environmental shifts to which communities would be expected to be well adapted. As such, extreme environmental changes could have very different effects on the stability of the different nitrogen cycle activities. These outcomes suggest a need to modify existing conceptual models that link biodiversity to microbiome function to incorporate within-gene diversity. Specifically, we suggest an expanded conceptualization that 1) recognizes component steps (genes) with low diversity as potential bottlenecks influencing pathway-level function, and 2) includes variation in both the number of entities (e.g. species, phylotypes) that can contribute to a given process and the turnover of those entities in response to shifting conditions. Building these concepts into process-based ecosystem models represents an exciting opportunity to connect within-gene-scale ecological dynamics to ecosystem-scale services., Competing Interests: The authors have declared that no competing interests exist.

Many clinical laboratories supporting solid organ transplant programs use multiple HLA genotyping technologies, depending on individual laboratory needs. Sequence-specific primers and quantitative polymerase chain reaction (qPCR) serve the rapid turnaround necessary for deceased donor workup, while sequence-specific oligonucleotide probe (SSOP) technology is widely employed for higher volumes. When clinical need mandates high-resolution data, Sanger sequencing-based typing (SBT) has been the "gold standard." However, all those methods commonly yield ambiguous typing results that utilize valuable laboratory resources when resolution is required. In solid organ transplantation, high-resolution typing may provide critical information for highly sensitized patients with donor-specific anti-HLA antibodies (DSA), particularly when DSA involve HLA alleles not discriminated by SSOP typing. Arguments against routine use of SBT include assay complexity, long turnaround times (TAT), and increased costs. Here, we compare a next generation sequencing (NGS) technology with SSOP for accuracy, effort, turnaround time, and level of resolution for genotyping of 11 HLA loci among 289 specimens from five clinical laboratories. Results were concordant except for SSOP misassignments in eight specimens and 21 novel sequences uniquely identified by NGS. With few exceptions, SSOP generated ambiguous results while NGS provided unambiguous three-field allele assignments. For complete HLA genotyping of up to 24 samples by either SSOP or NGS, bench work was completed on day 1 and typing results were available on day 2. This study provides compelling evidence that, although not viable for STAT typing of deceased donors, a single-pass NGS HLA typing method has direct application for solid organ transplantation., (© 2019 The Authors. HLA: Immune Response Genetics published by John Wiley & Sons Ltd.)

Next-generation targeted sequencing of HLA-DRB1 and HLA-DRB3, -DRB4, and -DRB5 (abbreviated as DRB345) provides high resolution of functional variant positions to investigate their associations with type 1 diabetes risk and with autoantibodies against insulin (IAA), GAD65 (GADA), IA-2 (IA-2A), and ZnT8 (ZnT8A). To overcome exceptional DR sequence complexity as a result of high polymorphisms and extended linkage disequilibrium among the DR loci, we applied a novel recursive organizer (ROR) to discover disease-associated amino acid residues. ROR distills disease-associated DR sequences and identifies 11 residues of DRB1, sequences of which retain all significant associations observed by DR genes. Furthermore, all 11 residues locate under/adjoining the peptide-binding groove of DRB1, suggesting a plausible functional mechanism through peptide binding. The 15 residues of DRB345, located respectively in the β49-55 homodimerization patch and on the face of the molecule shown to interact with and bind to the accessory molecule CD4, retain their significant disease associations. Further ROR analysis of DR associations with autoantibodies finds that DRB1 residues significantly associated with ZnT8A and DRB345 residues with GADA. The strongest association is between four residues (β14, β25, β71, and β73) and IA-2A, in which the sequence ERKA confers a risk association (odds ratio 2.15, P = 10 -18 ), and another sequence, ERKG, confers a protective association (odds ratio 0.59, P = 10 -11 ), despite a difference of only one amino acid. Because motifs of identified residues capture potentially causal DR associations with type 1 diabetes, this list of residuals is expected to include corresponding causal residues in this study population., (© 2019 by the American Diabetes Association.)

An intriguing aspect in microbial communities is that pairwise interactions can be influenced by neighboring species. This creates context dependencies for microbial interactions that are based on the functional composition of the community. Context dependent interactions are ecologically important and clearly present in nature, yet firmly established theoretical methods are lacking from many modern computational investigations. Here, we propose a novel network inference method that enables predictions for interspecies interactions affected by shifts in community composition and species populations. Our approach first identifies interspecies interactions in binary communities, which is subsequently used as a basis to infer modulation in more complex multi-species communities based on the assumption that microbes minimize adjustments of pairwise interactions in response to neighbor species. We termed this rule-based inference minimal interspecies interaction adjustment (MIIA). Our critical assessment of MIIA has produced reliable predictions of shifting interspecies interactions that are dependent on the functional role of neighbor organisms. We also show how MIIA has been applied to a microbial community composed of competing soil bacteria to elucidate a new finding that - in many cases - adding fewer competitors could impose more significant impact on binary interactions. The ability to predict membership-dependent community behavior is expected to help deepen our understanding of how microbiomes are organized in nature and how they may be designed and/or controlled in the future.

Posttranslational modifications, such as N ε-lysine acetylation, regulate protein function. N ε-lysine acetylation can occur either nonenzymatically or enzymatically. The nonenzymatic mechanism uses acetyl phosphate (AcP) or acetyl coenzyme A (AcCoA) as acetyl donor to modify an N ε-lysine residue of a protein. The enzymatic mechanism uses N ε-lysine acetyltransferases (KATs) to specifically transfer an acetyl group from AcCoA to N ε-lysine residues on proteins. To date, only one KAT (YfiQ, also known as Pka and PatZ) has been identified in Escherichia coli Here, we demonstrate the existence of 4 additional E. coli KATs: RimI, YiaC, YjaB, and PhnO. In a genetic background devoid of all known acetylation mechanisms (most notably AcP and YfiQ) and one deacetylase (CobB), overexpression of these putative KATs elicited unique patterns of protein acetylation. We mutated key active site residues and found that most of them eliminated enzymatic acetylation activity. We used mass spectrometry to identify and quantify the specificity of YfiQ and the four novel KATs. Surprisingly, our analysis revealed a high degree of substrate specificity. The overlap between KAT-dependent and AcP-dependent acetylation was extremely limited, supporting the hypothesis that these two acetylation mechanisms play distinct roles in the posttranslational modification of bacterial proteins. We further showed that these novel KATs are conserved across broad swaths of bacterial phylogeny. Finally, we determined that one of the novel KATs (YiaC) and the known KAT (YfiQ) can negatively regulate bacterial migration. Together, these results emphasize distinct and specific nonenzymatic and enzymatic protein acetylation mechanisms present in bacteria. IMPORTANCE N ε-Lysine acetylation is one of the most abundant and important posttranslational modifications across all domains of life. One of the best-studied effects of acetylation occurs in eukaryotes, where acetylation of histone tails activates gene transcription. Although bacteria do not have true histones, N ε-lysine acetylation is prevalent; however, the role of these modifications is mostly unknown. We constructed an E. coli strain that lacked both known acetylation mechanisms to identify four new N ε-lysine acetyltransferases (RimI, YiaC, YjaB, and PhnO). We used mass spectrometry to determine the substrate specificity of these acetyltransferases. Structural analysis of selected substrate proteins revealed site-specific preferences for enzymatic acetylation that had little overlap with the preferences of the previously reported acetyl-phosphate nonenzymatic acetylation mechanism. Finally, YiaC and YfiQ appear to regulate flagellum-based motility, a phenotype critical for pathogenesis of many organisms. These acetyltransferases are highly conserved and reveal deeper and more complex roles for bacterial posttranslational modification., (Copyright © 2018 Christensen et al.)

There was an error in the proposed genus name in the published article, in that the genus 'Salinivirga' was effectively published while this article was in review. Therefore, the genus 'Salinivirga' should be replaced with 'Saliniramus'. For the convenience of future readers, we have included the complete corrected article below, in which all occurrences of the incorrect genus name have been amended: A halophilic bacterial strain, HL-109 T , was isolated from the unicyanobacterial consortium UCC-O, which was obtained from the photosynthetic mat of Hot Lake (Washington, USA). A polyphasic approach using phenotypic, genotypic and chemotaxonomic data was used to classify the strain within the order Rhizobiales. The organism stained Gram-negative and was a moderate thermophile with a growth optimum of 45 °C. It was obligately aerobic, heterotrophic and halophilic, growing in both NaCl and MgSO4 brines. The novel isolate had a polymorphic cellular morphology of short rods with occasional branching, and cells were monotrichous. The major fatty acids detected were C18 : 1, C18 : 0, C16 : 0 and C18 : cyc. Phylogenetic analysis of the 16S rRNA gene placed the strain in the order Rhizobiales and it shared 94 % identity with the type strain of its nearest relative, Salinarimonas ramus. Morphological, chemotaxonomic and phylogenetic results did not affiliate the novel organism with any of the families in the Rhizobiales; therefore, HL-109 T is representative of a new lineage, for which the name Saliniramus fredricksonii gen. nov., sp. nov. is proposed, with the type strain HL-109 T (=JCM 31876 T =DSM 102886 T ). In addition, examination of the phylogenetics of strain HL-109 T and its nearest relatives, Salinarimonas ramus and Salinarimonasrosea, demonstrates that these halophiles form a clade distinct from the described families of the Rhizobiales. We further propose the establishment of a new family, Salinarimonadaceae fam. nov., to accommodate the genera Saliniramus and Salinarimonas (the type genus of the family).

A halophilic bacterial strain, HL-109 T , was isolated from the unicyanobacterial consortium UCC-O, which was obtained from the photosynthetic mat of Hot Lake (Washington, USA). A polyphasic approach using phenotypic, genotypic and chemotaxonomic data was used to classify the strain within the order Rhizobiales. The organism stained Gram-negative and was a moderate thermophile with a growth optimum of 45 °C. It was obligately aerobic, heterotrophic and halophilic, growing in both NaCl and MgSO4 brines. The novel isolate had a polymorphic cellular morphology of short rods with occasional branching, and cells were monotrichous. The major fatty acids detected were C18 : 1, C18 : 0, C16 : 0 and C18 : cyc. Phylogenetic analysis of the 16S rRNA gene placed the strain in the order Rhizobiales and it shared 94 % identity with the type strain of its nearest relative, Salinarimonas ramus. Morphological, chemotaxonomic and phylogenetic results did not affiliate the novel organism with any of the families in the Rhizobiales; therefore, HL-109 T is representative of a new lineage, for which the name Salinivirga fredricksonii gen. nov., sp. nov. is proposed, with the type strain HL-109 T (=JCM 31876 T =DSM 102886 T ). In addition, examination of the phylogenetics of strain HL-109 T and its nearest relatives, Salinarimonas ramus and Salinarimonasrosea, demonstrates that these halophiles form a clade distinct from the described families of the Rhizobiales. We further propose the establishment of a new family, Salinarimonadaceae fam. nov., to accommodate the genera Salinivirga and Salinarimonas (the type genus of the family).

The original version of this Article contained an error in Fig. 6e, in which the text in the legend was omitted. This has been corrected in both the PDF and HTML versions of the article.

The complete genome sequence of Cyanobacterium sp. strain HL-69 consists of 3,155,247 bp and contains 2,897 predicted genes comprising a chromosome and two plasmids. The genome is consistent with a halophilic nondiazotrophic phototrophic lifestyle, and this organism is able to synthesize most B vitamins and produces several secondary metabolites., (Copyright © 2018 Mobberley et al.)

The hyporheic corridor (HC) encompasses the river-groundwater continuum, where the mixing of groundwater (GW) with river water (RW) in the HC can stimulate biogeochemical activity. Here we propose a novel thermodynamic mechanism underlying this phenomenon and reveal broader impacts on dissolved organic carbon (DOC) and microbial ecology. We show that thermodynamically favorable DOC accumulates in GW despite lower DOC concentration, and that RW contains thermodynamically less-favorable DOC, but at higher concentrations. This indicates that GW DOC is protected from microbial oxidation by low total energy within the DOC pool, whereas RW DOC is protected by lower thermodynamic favorability of carbon species. We propose that GW-RW mixing overcomes these protections and stimulates respiration. Mixing models coupled with geophysical and molecular analyses further reveal tipping points in spatiotemporal dynamics of DOC and indicate important hydrology-biochemistry-microbial feedbacks. Previously unrecognized thermodynamic mechanisms regulated by GW-RW mixing may therefore strongly influence biogeochemical and microbial dynamics in riverine ecosystems.

The fundamental question of whether different microbial species will co-exist or compete in a given environment depends on context, composition and environmental constraints. Model microbial systems can yield some general principles related to this question. In this study we employed a naturally occurring co-culture composed of heterotrophic bacteria, Halomonas sp. HL-48 and Marinobacter sp. HL-58, to ask two fundamental scientific questions: 1) how do the phenotypes of two naturally co-existing species respond to partnership as compared to axenic growth? and 2) how do growth and molecular phenotypes of these species change with respect to competitive and commensal interactions? We hypothesized - and confirmed - that co-cultivation under glucose as the sole carbon source would result in competitive interactions. Similarly, when glucose was swapped with xylose, the interactions became commensal because Marinobacter HL-58 was supported by metabolites derived from Halomonas HL-48. Each species responded to partnership by changing both its growth and molecular phenotype as assayed via batch growth kinetics and global transcriptomics. These phenotypic responses depended on nutrient availability and so the environment ultimately controlled how they responded to each other. This simplified model community revealed that microbial interactions are context-specific and different environmental conditions dictate how interspecies partnerships will unfold.