High fat intake sustains sorbitol intolerance after antibiotic-mediated Clostridia depletion from the gut microbiota.

Carbohydrate intolerance, commonly linked to the consumption of lactose, fructose, or sorbitol, affects up to 30% of the population in high-income countries. Although sorbitol intolerance is attributed to malabsorption, the underlying mechanism remains unresolved. Here, we show that a history of antibiotic exposure combined with high fat intake triggered long-lasting sorbitol intolerance in mice by reducing Clostridia abundance, which impaired microbial sorbitol catabolism. The restoration of sorbitol catabolism by inoculation with probiotic Escherichia coli protected mice against sorbitol intolerance but did not restore Clostridia abundance. Inoculation with the butyrate producer Anaerostipes caccae restored a normal Clostridia abundance, which protected mice against sorbitol-induced diarrhea even when the probiotic was cleared. Butyrate restored Clostridia abundance by stimulating epithelial peroxisome proliferator-activated receptor-gamma (PPAR-γ) signaling to restore epithelial hypoxia in the colon. Collectively, these mechanistic insights identify microbial sorbitol catabolism as a potential target for approaches for the diagnosis, treatment, and prevention of sorbitol intolerance.

Bacterial ecology and evolution converge on seasonal and decadal scales.

Ecology and evolution are distinct theories, but the short lifespans and large population sizes of microbes allow evolution to unfold along contemporary ecological time scales. To document this in a natural system, we collected a two-decade, 471-metagenome time series from a single site in a freshwater lake, which we refer to as the TYMEFLIES dataset. This massive sampling and sequencing effort resulted in the reconstruction of 30,389 metagenomic-assembled genomes (MAGs) over 50% complete, which dereplicated into 2,855 distinct genomes (>96% nucleotide sequence identity). We found both ecological and evolutionary processes occurred at seasonal time scales. There were recurring annual patterns at the species level in abundances, nucleotide diversities (π), and single nucleotide variant (SNV) profiles for the majority of all taxa. During annual blooms, we observed both higher and lower nucleotide diversity, indicating that both ecological differentiation and competition drove evolutionary dynamics. Overlayed upon seasonal patterns, we observed long-term change in 20% of the species' SNV profiles including gradual changes, step changes, and disturbances followed by resilience. Most abrupt changes occurred in a single species, suggesting evolutionary drivers are highly specific. Nevertheless, seven members of the abundant Nanopelagicaceae family experienced abrupt change in 2012, an unusually hot and dry year. This shift coincided with increased numbers of genes under selection involved in amino acid and nucleic acid metabolism, suggesting fundamental organic nitrogen compounds drive strain differentiation in the most globally abundant freshwater family. Overall, we observed seasonal and decadal trends in both interspecific ecological and intraspecific evolutionary processes. The convergence of microbial ecology and evolution on the same time scales demonstrates that understanding microbiomes requires a new unified approach that views ecology and evolution as a single continuum.

A standardized quantitative analysis strategy for stable isotope probing metagenomics.

Stable isotope probing (SIP) facilitates culture-independent identification of active microbial populations within complex ecosystems through isotopic enrichment of nucleic acids. Many DNA-SIP studies rely on 16S rRNA gene sequences to identify active taxa, but connecting these sequences to specific bacterial genomes is often challenging. Here, we describe a standardized laboratory and analysis framework to quantify isotopic enrichment on a per-genome basis using shotgun metagenomics instead of 16S rRNA gene sequencing. To develop this framework, we explored various sample processing and analysis approaches using a designed microbiome where the identity of labeled genomes and their level of isotopic enrichment were experimentally controlled. With this ground truth dataset, we empirically assessed the accuracy of different analytical models for identifying active taxa and examined how sequencing depth impacts the detection of isotopically labeled genomes. We also demonstrate that using synthetic DNA internal standards to measure absolute genome abundances in SIP density fractions improves estimates of isotopic enrichment. In addition, our study illustrates the utility of internal standards to reveal anomalies in sample handling that could negatively impact SIP metagenomic analyses if left undetected. Finally, we present SIPmg, an R package to facilitate the estimation of absolute abundances and perform statistical analyses for identifying labeled genomes within SIP metagenomic data. This experimentally validated analysis framework strengthens the foundation of DNA-SIP metagenomics as a tool for accurately measuring the in situ activity of environmental microbial populations and assessing their genomic potential. IMPORTANCE Answering the questions, "who is eating what?" and "who is active?" within complex microbial communities is paramount for our ability to model, predict, and modulate microbiomes for improved human and planetary health. These questions can be pursued using stable isotope probing to track the incorporation of labeled compounds into cellular DNA during microbial growth. However, with traditional stable isotope methods, it is challenging to establish links between an active microorganism's taxonomic identity and genome composition while providing quantitative estimates of the microorganism's isotope incorporation rate. Here, we report an experimental and analytical workflow that lays the foundation for improved detection of metabolically active microorganisms and better quantitative estimates of genome-resolved isotope incorporation, which can be used to further refine ecosystem-scale models for carbon and nutrient fluxes within microbiomes.

Terabase-Scale Coassembly of a Tropical Soil Microbiome.

Petabases of environmental metagenomic data are publicly available, presenting an opportunity to characterize complex environments and discover novel lineages of life. Metagenome coassembly, in which many metagenomic samples from an environment are simultaneously analyzed to infer the underlying genomes' sequences, is an essential tool for achieving this goal. We applied MetaHipMer2, a distributed metagenome assembler that runs on supercomputing clusters, to coassemble 3.4 terabases (Tbp) of metagenome data from a tropical soil in the Luquillo Experimental Forest (LEF), Puerto Rico. The resulting coassembly yielded 39 high-quality (>90% complete, <5% contaminated, with predicted 23S, 16S, and 5S rRNA genes and ≥18 tRNAs) metagenome-assembled genomes (MAGs), including two from the candidate phylum Eremiobacterota. Another 268 medium-quality (≥50% complete, <10% contaminated) MAGs were extracted, including the candidate phyla Dependentiae, Dormibacterota, and Methylomirabilota. In total, 307 medium- or higher-quality MAGs were assigned to 23 phyla, compared to 294 MAGs assigned to nine phyla in the same samples individually assembled. The low-quality (<50% complete, <10% contaminated) MAGs from the coassembly revealed a 49% complete rare biosphere microbe from the candidate phylum FCPU426 among other low-abundance microbes, an 81% complete fungal genome from the phylum Ascomycota, and 30 partial eukaryotic MAGs with ≥10% completeness, possibly representing protist lineages. A total of 22,254 viruses, many of them low abundance, were identified. Estimation of metagenome coverage and diversity indicates that we may have characterized ≥87.5% of the sequence diversity in this humid tropical soil and indicates the value of future terabase-scale sequencing and coassembly of complex environments. IMPORTANCE Petabases of reads are being produced by environmental metagenome sequencing. An essential step in analyzing these data is metagenome assembly, the computational reconstruction of genome sequences from microbial communities. "Coassembly" of metagenomic sequence data, in which multiple samples are assembled together, enables more complete detection of microbial genomes in an environment than "multiassembly," in which samples are assembled individually. To demonstrate the potential for coassembling terabases of metagenome data to drive biological discovery, we applied MetaHipMer2, a distributed metagenome assembler that runs on supercomputing clusters, to coassemble 3.4 Tbp of reads from a humid tropical soil environment. The resulting coassembly, its functional annotation, and analysis are presented here. The coassembly yielded more, and phylogenetically more diverse, microbial, eukaryotic, and viral genomes than the multiassembly of the same data. Our resource may facilitate the discovery of novel microbial biology in tropical soils and demonstrates the value of terabase-scale metagenome sequencing.

Distribution and abundance of tetraether lipid cyclization genes in terrestrial hot springs reflect pH.

Many Archaea produce membrane-spanning lipids that enable life in extreme environments. These isoprenoid glycerol dibiphytanyl glycerol tetraethers (GDGTs) may contain up to eight cyclopentyl and one cyclohexyl ring, where higher degrees of cyclization are associated with more acidic, hotter or energy-limited conditions. Recently, the genes encoding GDGT ring synthases, grsAB, were identified in two Sulfolobaceae; however, the distribution and abundance of grs homologs across environments inhabited by these and related organisms remain a mystery. To address this, we examined the distribution of grs homologs in relation to environmental temperature and pH, from thermal springs across Earth, where sequences derive from metagenomes, metatranscriptomes, single-cell and cultivar genomes. The abundance of grs homologs shows a strong negative correlation to pH, but a weak positive correlation to temperature. Archaeal genomes and metagenome-assembled genomes (MAGs) that carry two or more grs copies are more abundant in low pH springs. We also find grs in 12 archaeal classes, with the most representatives in Thermoproteia, followed by MAGs of the uncultured Korarchaeia, Bathyarchaeia and Hadarchaeia, while several Nitrososphaeria encodes >3 copies. Our findings highlight the key role of grs-catalysed lipid cyclization in archaeal diversification across hot and acidic environments.

Exaggerated trans-membrane charge of ammonium transporters in nutrient-poor marine environments.

Transporter proteins are a vital interface between cells and their environment. In nutrient-limited environments, microbes with transporters that are effective at bringing substrates into their cells will gain a competitive advantage over variants with reduced transport function. Microbial ammonium transporters (Amt) bring ammonium into the cytoplasm from the surrounding periplasm space, but diagnosing Amt adaptations to low nutrient environments solely from sequence data has been elusive. Here, we report altered Amt sequence amino acid distribution from deep marine samples compared to variants sampled from shallow water in two important microbial lineages of the marine water column community-Marine Group I Archaea (Thermoproteota) and the uncultivated gammaproteobacterial lineage SAR86. This pattern indicates an evolutionary pressure towards an increasing dipole in Amt for these clades in deep ocean environments and is predicted to generate stronger electric fields facilitating ammonium acquisition. This pattern of increasing dipole charge with depth was not observed in lineages capable of accessing alternative nitrogen sources, including the abundant alphaproteobacterial clade SAR11. We speculate that competition for ammonium in the deep ocean drives transporter sequence evolution. The low concentration of ammonium in the deep ocean is therefore likely due to rapid uptake by Amts concurrent with decreasing nutrient flux.

Complete Genome Sequences of Two Phylogenetically Distinct Nitrospina Strains Isolated from the Atlantic and Pacific Oceans.

The complete genome sequences of two chemoautotrophic nitrite-oxidizing bacteria of the genus Nitrospina are reported. Nitrospina gracilis strain Nb-211 was isolated from the Atlantic Ocean, and Nitrospina sp. strain Nb-3 was isolated from the Pacific Ocean. We report two highly similar ~3.07-Mbp genome sequences that differ by the presence of ferric iron chelator (siderophore) biosynthesis genes.

Using cluster edge counting to aggregate iterations of centroid-linkage clustering results and avoid large distance matrices.

Sequence clustering is a fundamental tool of molecular biology that is being challenged by increasing dataset sizes from high-throughput sequencing. The agglomerative algorithms that have been relied upon for their accuracy require the construction of computationally costly distance matrices which can overwhelm basic research personal computers. Alternative algorithms exist, such as centroid-linkage, to circumvent large memory requirements but their results are often input-order dependent. We present a method for bootstrapping the results of many centroid-linkage clustering iterations into an aggregate set of clusters, increasing cluster accuracy without a distance matrix. This method ranks cluster edges by conservation across iterations and reconstructs aggregate clusters from the resulting ranked edge list, pruning out low-frequency cluster edges that may have been a result of a specific sequence input order. Aggregating centroid-linkage clustering iterations can help researchers using basic research personal computers acquire more reliable clustering results without increasing memory resources.

Using Dendritic Heat Maps to Simultaneously Display Genotype Divergence with Phenotype Divergence.

The advancement of techniques to visualize and analyze large-scale sequencing datasets is an area of active research and is rooted in traditional techniques such as heat maps and dendrograms. We introduce dendritic heat maps that display heat map results over aligned DNA sequence clusters for a range of clustering cutoffs. Dendritic heat maps aid in visualizing the effects of group differences on clustering hierarchy and relative abundance of sampled sequences. Here, we artificially generate two separate datasets with simplified mutation and population growth procedures with GC content group separation to use as example phenotypes. In this work, we use the term phenotype to represent any feature by which groups can be separated. These sequences were clustered in a fractional identity range of 0.75 to 1.0 using agglomerative minimum-, maximum-, and average-linkage algorithms, as well as a divisive centroid-based algorithm. We demonstrate that dendritic heat maps give freedom to scrutinize specific clustering levels across a range of cutoffs, track changes in phenotype inequity across multiple levels of sequence clustering specificity, and easily visualize how deeply rooted changes in phenotype inequity are in a dataset. As genotypes diverge in sample populations, clusters are shown to break apart into smaller clusters at higher identity cutoff levels, similar to a dendrogram. Phenotype divergence, which is shown as a heat map of relative abundance bin response, may or may not follow genotype divergences. This joined view highlights the relationship between genotype and phenotype divergence for treatment groups. We discuss the minimum-, maximum-, average-, and centroid-linkage algorithm approaches to building dendritic heat maps and make a case for the divisive "top-down" centroid-based clustering methodology as being the best option visualize the effects of changing factors on clustering hierarchy and relative abundance.

Draft Genome Sequence of Microvirga sp. Strain BSC39, Isolated from Biological Soil Crust of Moab, Utah.

Microvirga sp. BSC39 was isolated from a biological soil crust near Moab, Utah. The strain appears to be capable of chemotaxis and exopolysaccharide synthesis for biofilm adhesion. The BSC39 genome contains iron siderophore uptake and hydrolysis enzymes; however, it lacks siderophore synthesis pathways, suggesting the uptake of siderophores produced by neighboring microbes.

Draft Genome Sequence of Bacillus sp. Strain BSC154, Isolated from Biological Soil Crust of Moab, Utah.

Bacillus sp. BSC154 was isolated from a biological soil crust near Moab, Utah. The strain appears to be capable of chemotaxis and biofilm production. The BSC154 genome contains iron siderophore production, nitrate reduction, mixed acid-butanediol fermentation, and assimilatory and dissimilatory sulfate metabolism pathways.

Draft Genome Sequence of Massilia sp. Strain BSC265, Isolated from Biological Soil Crust of Moab, Utah.

Massilia sp. BSC265 was isolated from a biological soil crust near Moab, Utah. The strain appears to be capable of chemotaxis and exopolysaccharide synthesis for biofilm adhesion. The BSC265 genome contains a complete dissimilatory nitrate reduction pathway as well as a TCA cycle, making it a facultative anaerobe.

Neuropathological responses to chronic NMDA in rats are worsened by dietary n-3 PUFA deprivation but are not ameliorated by fish oil supplementation.

BACKGROUND: Dietary long-chain n-3 polyunsaturated fatty acid (PUFA) supplementation may be beneficial for chronic brain illnesses, but the issue is not agreed on. We examined effects of dietary n-3 PUFA deprivation or supplementation, compared with an n-3 PUFA adequate diet (containing alpha-linolenic acid [18:3 n-3] but not docosahexaenoic acid [DHA, 22:6n-3]), on brain markers of lipid metabolism and excitotoxicity, in rats treated chronically with NMDA or saline. METHODS: Male rats after weaning were maintained on one of three diets for 15 weeks. After 12 weeks, each diet group was injected i.p. daily with saline (1 ml/kg) or a subconvulsive dose of NMDA (25 mg/kg) for 3 additional weeks. Then, brain fatty acid concentrations and various markers of excitotoxicity and fatty acid metabolism were measured. RESULTS: Compared to the diet-adequate group, brain DHA concentration was reduced, while n-6 docosapentaenoic acid (DPA, 22:5n-6) concentration was increased in the n-3 deficient group; arachidonic acid (AA, 20:4n-6) concentration was unchanged. These concentrations were unaffected by fish oil supplementation. Chronic NMDA increased brain cPLA2 activity in each of the three groups, but n-3 PUFA deprivation or fish oil did not change cPLA2 activity or protein compared with the adequate group. sPLA2 expression was unchanged in the three conditions, whereas iPLA2 expression was reduced by deprivation but not changed by supplementation. BDNF protein was reduced by NMDA in N-3 PUFA deficient rats, but protein levels of IL-1ß, NGF, and GFAP did not differ between groups. CONCLUSIONS: N-3 PUFA deprivation significantly worsened several pathological NMDA-induced changes produced in diet adequate rats, whereas n-3 PUFA supplementation did not affect NMDA induced changes. Supplementation may not be critical for this measured neuropathology once the diet has an adequate n-3 PUFA content.

Identification and profiling of targeted oxidized linoleic acid metabolites in rat plasma by quadrupole time-of-flight mass spectrometry.

Linoleic acid (LA) and LA-esters are the precursors of LA hydroperoxides, which are readily converted to 9- and 13-hydroxy-​octadecadienoic acid (HODE) and 9- and 13-oxo-​octadecadienoic acid (oxo ODE) metabolites in vivo. These four oxidized LA metabolites (OXLAMs) have been implicated in a variety of pathological conditions. Therefore, their accurate measurement may provide mechanistic insights into disease pathogenesis. Here we present a novel quadrupole time-of-flight mass spectrometry (Q-TOFMS) method for quantitation and identification of target OXLAMs in rat plasma. In this method, the esterified OXLAMs were base-hydrolyzed and followed by liquid-liquid extraction. Quantitative analyses were based on one-point standard addition with isotope dilution. The Q-TOFMS data of target metabolites were acquired and multiple reaction monitoring extracted-ion chromatograms were generated post-acquisition with a 10 ppm extraction window. The limit of quantitation was 9.7-35.9 nmol/L depending on the metabolite. The method was reproducible with a coefficient of variation of <18.5%. Mean concentrations of target metabolites in rat plasma were 57.8, 123.2, 218.1 and 57.8 nmol/L for 9-HODE, 13-HODE, 9-oxoODE and 13-oxoODE, respectively. Plasma levels of total OXLAMs were 456.9 nmol/L, which correlated well with published concentrations obtained by gas chromatography/mass spectrometry (GC/MS). The concentrations were also obtained utilizing a standard addition curve approach. The calibration curves were linear with correlation coefficients of >0.991. Concentrations of 9-HODE, 13-HODE, 9-oxoODE and 13-oxoODE were 84.0, 138.6, 263.0 and 69.5 nmol/L, respectively, which were consistent with the results obtained from one-point standard addition. Target metabolites were simultaneously characterized based on the accurate Q-TOFMS data. This is the first study of secondary LA metabolites using Q-TOFMS. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.

Dose-dependent changes in neuroinflammatory and arachidonic acid cascade markers with synaptic marker loss in rat lipopolysaccharide infusion model of neuroinflammation.

BACKGROUND: Neuroinflammation, caused by six days of intracerebroventricular infusion of bacterial lipopolysaccharide (LPS), stimulates rat brain arachidonic acid (AA) metabolism. The molecular changes associated with increased AA metabolism are not clear. We examined effects of a six-day infusion of a low-dose (0.5 ng/h) and a high-dose (250 ng/h) of LPS on neuroinflammatory, AA cascade, and pre- and post-synaptic markers in rat brain. We used artificial cerebrospinal fluid-infused brains as controls. RESULTS: Infusion of low- or high-dose LPS increased brain protein levels of TNFα, and iNOS, without significantly changing GFAP. High-dose LPS infusion upregulated brain protein and mRNA levels of AA cascade markers (cytosolic cPLA2-IVA, secretory sPLA2-V, cyclooxygenase-2 and 5-lipoxygenase), and of transcription factor NF-κB p50 DNA binding activity. Both LPS doses increased cPLA2 and p38 mitogen-activated protein kinase levels, while reducing protein levels of the pre-synaptic marker, synaptophysin. Post-synaptic markers drebrin and PSD95 protein levels were decreased with high- but not low-dose LPS. CONCLUSIONS: Chronic LPS infusion has differential effects, depending on dose, on inflammatory, AA and synaptic markers in rat brain. Neuroinflammation associated with upregulated brain AA metabolism can lead to synaptic dysfunction.

Neuroinflammation and synaptic loss.

Neuroinflammation plays a critical role in the progression of many neurodegenerative, neuropsychiatric and viral diseases. In neuroinflammation, activated microglia and astrocytes release cytokines and chemokines as well as nitric oxide, which in turn activate many signal transduction pathways. The cytokines, interleukin-1 beta and tumor necrosis factor alpha, regulate transcription of a number of genes within the brain, which can lead to the formation of pro-inflammatory products of the arachidonic acid cascade. Formation of pro-inflammatory agents and associated cytotoxic products during neuroinflammation can be detrimental to neurons by altering synaptic proteins. Neuroinflammation as well as excitotoxic insults reduce synaptic markers such as synaptophysin and drebrin. Neurodegenerative, neuropsychiatric illnesses and viral infections are accompanied by loss of both pre- and post-synaptic proteins. These synaptic changes may contribute to the progressive cognitive decline and behavioral changes associated with these illnesses.

RETRACTED: Dysregulated glutamate and dopamine transporters in postmortem frontal cortex from bipolar and schizophrenic patients.

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been retracted at the request of The National Institutes of Health has found that the first author, Dr. Jagadeesh S. Rao engaged in research misconduct by falsifying data in "Dysregulated glutamate and dopamine transporters in postmortem frontal cortex from bipolar and schizophrenic patients". Rao JS, Kellom M, Reese EA, Rapoport SI, Kim HW. J. Affect Disord. 136(1­2):63­71. 2012. Data in Figures 2A, 2B, 3A, 3B and 4A were falsified.