Molecular-Level Dysregulation of Insulin Pathways and Inflammatory Processes in Peripheral Blood Mononuclear Cells by Circadian Misalignment.

Circadian misalignment due to night work has been associated with an elevated risk for chronic diseases. We investigated the effects of circadian misalignment using shotgun protein profiling of peripheral blood mononuclear cells taken from healthy humans during a constant routine protocol, which was conducted immediately after participants had been subjected to a 3-day simulated night shift schedule or a 3-day simulated day shift schedule. By comparing proteomic profiles between the simulated shift conditions, we identified proteins and pathways that are associated with the effects of circadian misalignment and observed that insulin regulation pathways and inflammation-related proteins displayed markedly different temporal patterns after simulated night shift. Further, by integrating the proteomic profiles with previously assessed metabolomic profiles in a network-based approach, we found key associations between circadian dysregulation of protein-level pathways and metabolites of interest in the context of chronic metabolic diseases. Endogenous circadian rhythms in circulating glucose and insulin differed between the simulated shift conditions. Overall, our results suggest that circadian misalignment is associated with a tug of war between central clock mechanisms controlling insulin secretion and peripheral clock mechanisms regulating insulin sensitivity, which may lead to adverse long-term outcomes such as diabetes and obesity. Our study provides a molecular-level mechanism linking circadian misalignment and adverse long-term health consequences of night work.

Cell-type-specific transcriptomics uncovers spatial regulatory networks in bioenergy sorghum stems.

Bioenergy sorghum is a low-input, drought-resilient, deep-rooting annual crop that has high biomass yield potential enabling the sustainable production of biofuels, biopower, and bioproducts. Bioenergy sorghum's 4-5 m stems account for ~80% of the harvested biomass. Stems accumulate high levels of sucrose that could be used to synthesize bioethanol and useful biopolymers if information about cell-type gene expression and regulation in stems was available to enable engineering. To obtain this information, laser capture microdissection was used to isolate and collect transcriptome profiles from five major cell types that are present in stems of the sweet sorghum Wray. Transcriptome analysis identified genes with cell-type-specific and cell-preferred expression patterns that reflect the distinct metabolic, transport, and regulatory functions of each cell type. Analysis of cell-type-specific gene regulatory networks (GRNs) revealed that unique transcription factor families contribute to distinct regulatory landscapes, where regulation is organized through various modes and identifiable network motifs. Cell-specific transcriptome data was combined with known secondary cell wall (SCW) networks to identify the GRNs that differentially activate SCW formation in vascular sclerenchyma and epidermal cells. The spatial transcriptomic dataset provides a valuable source of information about the function of different sorghum cell types and GRNs that will enable the engineering of bioenergy sorghum stems, and an interactive web application developed during this project will allow easy access and exploration of the data (https://mc-lab.shinyapps.io/lcm-dataset/).

Oligosaccharide production and signaling correlate with delayed flowering in an Arabidopsis genotype grown and selected in high [CO2].

Since industrialization began, atmospheric CO2 ([CO2]) has increased from 270 to 415 ppm and is projected to reach 800-1000 ppm this century. Some Arabidopsis thaliana (Arabidopsis) genotypes delayed flowering in elevated [CO2] relative to current [CO2], while others showed no change or accelerations. To predict genotype-specific flowering behaviors, we must understand the mechanisms driving flowering response to rising [CO2]. [CO2] changes alter photosynthesis and carbohydrates in plants. Plants sense carbohydrate levels, and exogenous carbohydrate application influences flowering time and flowering transcript levels. We asked how organismal changes in carbohydrates and transcription correlate with changes in flowering time under elevated [CO2]. We used a genotype (SG) of Arabidopsis that was selected for high fitness at elevated [CO2] (700 ppm). SG delays flowering under elevated [CO2] (700 ppm) relative to current [CO2] (400 ppm). We compared SG to a closely related control genotype (CG) that shows no [CO2]-induced flowering change. We compared metabolomic and transcriptomic profiles in these genotypes at current and elevated [CO2] to assess correlations with flowering in these conditions. While both genotypes altered carbohydrates in response to elevated [CO2], SG had higher levels of sucrose than CG and showed a stronger increase in glucose and fructose in elevated [CO2]. Both genotypes demonstrated transcriptional changes, with CG increasing genes related to fructose 1,6-bisphosphate breakdown, amino acid synthesis, and secondary metabolites; and SG decreasing genes related to starch and sugar metabolism, but increasing genes involved in oligosaccharide production and sugar modifications. Genes associated with flowering regulation within the photoperiod, vernalization, and meristem identity pathways were altered in these genotypes. Elevated [CO2] may alter carbohydrates to influence transcription in both genotypes and delayed flowering in SG. Changes in the oligosaccharide pool may contribute to delayed flowering in SG. This work extends the literature exploring genotypic-specific flowering responses to elevated [CO2].

A crucial role for dynamic expression of components encoding the negative arm of the circadian clock.

In the Neurospora circadian system, the White Collar Complex (WCC) drives expression of the principal circadian negative arm component frequency (frq). FRQ interacts with FRH (FRQ-interacting RNA helicase) and CKI, forming a stable complex that represses its own expression by inhibiting WCC. In this study, a genetic screen identified a gene, designated as brd-8, that encodes a conserved auxiliary subunit of the NuA4 histone acetylation complex. Loss of brd-8 reduces H4 acetylation and RNA polymerase (Pol) II occupancy at frq and other known circadian genes, and leads to a long circadian period, delayed phase, and defective overt circadian output at some temperatures. In addition to strongly associating with the NuA4 histone acetyltransferase complex, BRD-8 is also found complexed with the transcription elongation regulator BYE-1. Expression of brd-8, bye-1, histone h2a.z, and several NuA4 subunits is controlled by the circadian clock, indicating that the molecular clock both regulates the basic chromatin status and is regulated by changes in chromatin. Taken together, our data identify auxiliary elements of the fungal NuA4 complex having homology to mammalian components, which along with conventional NuA4 subunits, are required for timely and dynamic frq expression and thereby a normal and persistent circadian rhythm.

A crucial role for dynamic expression of components encoding the negative arm of the circadian clock.

In the Neurospora circadian system, the White Collar Complex (WCC) drives expression of the principal circadian negative arm component frequency ( frq ). FRQ interacts with FRH (FRQ-interacting helicase) and CK-1 forming a stable complex that represses its own expression by inhibiting WCC. In this study, a genetic screen identified a gene, designated as brd-8 , that encodes a conserved auxiliary subunit of the NuA4 histone acetylation complex. Loss of brd-8 reduces H4 acetylation and RNA polymerase (Pol) II occupancy at frq and other known circadian genes, and leads to a long circadian period, delayed phase, and defective overt circadian output at some temperatures. In addition to strongly associating with the NuA4 histone acetyltransferase complex, BRD-8 is also found complexed with the transcription elongation regulator BYE-1. Expression of brd-8, bye-1, histone hH2Az , and several NuA4 subunits is controlled by the circadian clock, indicating that the molecular clock both regulates the basic chromatin status and is regulated by changes in chromatin. Taken together, our data identify new auxiliary elements of the fungal NuA4 complex having homology to mammalian components, which along with conventional NuA4 subunits, are required for timely and dynamic frq expression and thereby a normal and persistent circadian rhythm.

Uncovering Hidden Members and Functions of the Soil Microbiome Using De Novo Metaproteomics.

Metaproteomics has been increasingly utilized for high-throughput characterization of proteins in complex environments and has been demonstrated to provide insights into microbial composition and functional roles. However, significant challenges remain in metaproteomic data analysis, including creation of a sample-specific protein sequence database. A well-matched database is a requirement for successful metaproteomics analysis, and the accuracy and sensitivity of PSM identification algorithms suffer when the database is incomplete or contains extraneous sequences. When matched DNA sequencing data of the sample is unavailable or incomplete, creating the proteome database that accurately represents the organisms in the sample is a challenge. Here, we leverage a de novo peptide sequencing approach to identify the sample composition directly from metaproteomic data. First, we created a deep learning model, Kaiko, to predict the peptide sequences from mass spectrometry data and trained it on 5 million peptide-spectrum matches from 55 phylogenetically diverse bacteria. After training, Kaiko successfully identified organisms from soil isolates and synthetic communities directly from proteomics data. Finally, we created a pipeline for metaproteome database generation using Kaiko. We tested the pipeline on native soils collected in Kansas, showing that the de novo sequencing model can be employed as an alternative and complementary method to construct the sample-specific protein database instead of relying on (un)matched metagenomes. Our pipeline identified all highly abundant taxa from 16S rRNA sequencing of the soil samples and uncovered several additional species which were strongly represented only in proteomic data.

Expression Patterns of Energy-Related Genes in Single Cells Uncover Key Isoforms and Enzymes That Gain Priority Under Nanoparticle-Induced Stress.

Cellular responses to nanoparticles (NPs) have been largely studied in cell populations, providing averaged values that often misrepresent the true molecular processes that occur in the individual cell. To understand how a cell redistributes limited molecular resources to achieve optimal response and survival requires single-cell analysis. Here we applied multiplex single molecule-based fluorescence in situ hybridization (fliFISH) to quantify the expression of 10 genes simultaneously in individual intact cells, including glycolysis and glucose transporter genes, which are critical for restoring and maintaining energy balance. We focused on individual gill epithelial cell responses to lithium cobalt oxide (LCO) NPs, which are actively pursued as cathode materials in lithium-ion batteries, raising concerns about their impact on the environment and human health. We found large variabilities in the expression levels of all genes between neighboring cells under the same exposure conditions, from only a few transcripts to over 100 copies in individual cells. Gene expression ratios among the 10 genes in each cell uncovered shifts in favor of genes that play key roles in restoring and maintaining energy balance. Among these genes are isoforms that can secure and increase glycolysis rates more efficiently, as well as genes with multiple cellular functions, in addition to glycolysis, including DNA repair, regulation of gene expression, cell cycle progression, and proliferation. Our study uncovered prioritization of gene expression in individual cells for restoring energy balance under LCO NP exposures. Broadly, our study gained insight into single-cell strategies for redistributing limited resources to achieve optimal response and survival under stress.

Capturing an Early Gene Induction Event during Wood Decay by the Brown Rot Fungus Rhodonia placenta.

Brown rot fungi dominate wood decomposition in coniferous forests, and their carbohydrate-selective mechanisms are of commercial interest. Brown rot was recently described as a two-step, sequential mechanism orchestrated by fungi using differentially expressed genes (DEGs) and consisting of oxidation via reactive oxygen species (ROS) followed by enzymatic saccharification. There have been indications, however, that the initial oxidation step itself might require induction. To capture this early gene regulation event, here, we integrated fine-scale cryosectioning with whole-transcriptome sequencing to dissect gene expression at the single-hyphal-cell scale (tens of micrometers). This improved the spatial resolution 50-fold, relative to previous work, and we were able to capture the activity of the first 100 µm of hyphal front growth by Rhodonia placenta in aspen wood. This early decay period was dominated by delayed gene expression patterns as the fungus ramped up its mechanism. These delayed DEGs included many genes implicated in ROS pathways (lignocellulose oxidation [LOX]) that were previously and incorrectly assumed to be constitutively expressed. These delayed DEGs, which include those with and without predicted functions, also create a focused subset of target genes for functional genomics. However, this delayed pattern was not universal, with a few genes being upregulated immediately at the hyphal front. Most notably, this included a gene commonly implicated in hydroquinone and iron redox cycling: benzoquinone reductase. IMPORTANCE Earth's aboveground terrestrial biomass is primarily wood, and fungi dominate wood decomposition. Here, we studied these fungal pathways in a common "brown rot"-type fungus, Rhodonia placenta, that selectively extracts sugars from carbohydrates embedded within wood lignin. Using a space-for-time design to map fungal gene expression at the extreme hyphal front in wood, we made two discoveries. First, we found that many genes long assumed to be "on" (constitutively expressed) from the very beginning of decay were instead "off" before being upregulated, when mapped (via transcriptome sequencing [RNA-seq]) at a high resolution. Second, we found that the gene encoding benzoquinone reductase was "on" in incipient decay and quickly downregulated, implying a key role in "kick-starting" brown rot.

Distinctive carbon repression effects in the carbohydrate-selective wood decay fungus Rhodonia placenta.

Brown rot fungi dominate the carbon degradation of northern terrestrial conifers. These fungi adapted unique genetic inventories to degrade lignocellulose and to rapidly release a large quantity of carbohydrates for fungal catabolism. We know that brown rot involves "two-step" gene regulation to delay most hydrolytic enzyme expression until after harsh oxidative pretreatments. This implies the crucial role of concise gene regulation to brown rot efficacy, but the underlying regulatory mechanisms remain uncharacterized. Here, using the combined transcriptomic and enzyme analyses we investigated the roles of carbon catabolites in controlling gene expression in model brown rot fungus Rhodonia placenta. We identified co-regulated gene regulons as shared transcriptional responses to no-carbon controls, glucose, cellobiose, or aspen wood (Populus sp.). We found that cellobiose, a common inducing catabolite for fungi, induced expression of main chain-cleaving cellulases in GH5 and GH12 families (cellobiose vs. no-carbon > 4-fold, Padj < 0.05), whereas complex aspen was a universal inducer for Carbohydrate Active Enzymes (CAZymes) expression. Importantly, we observed the attenuated glucose-mediated repression effects on cellulases expression, but not on hemicellulases and lignin oxidoreductases, suggesting fungi might have adapted diverged regulatory routes to boost cellulase production for the fast carbohydrate release. Using carbon regulons, we further predicted the cis- and trans-regulatory elements and assembled a network model of the distinctive regulatory machinery of brown rot. These results offer mechanistic insights into the energy efficiency traits of a common group of decomposer fungi with enormous influence on the carbon cycle.

Novel metabolic interactions and environmental conditions mediate the boreal peatmoss-cyanobacteria mutualism.

Interactions between Sphagnum (peat moss) and cyanobacteria play critical roles in terrestrial carbon and nitrogen cycling processes. Knowledge of the metabolites exchanged, the physiological processes involved, and the environmental conditions allowing the formation of symbiosis is important for a better understanding of the mechanisms underlying these interactions. In this study, we used a cross-feeding approach with spatially resolved metabolite profiling and metatranscriptomics to characterize the symbiosis between Sphagnum and Nostoc cyanobacteria. A pH gradient study revealed that the Sphagnum-Nostoc symbiosis was driven by pH, with mutualism occurring only at low pH. Metabolic cross-feeding studies along with spatially resolved matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) identified trehalose as the main carbohydrate source released by Sphagnum, which were depleted by Nostoc along with sulfur-containing choline-O-sulfate, taurine and sulfoacetate. In exchange, Nostoc increased exudation of purines and amino acids. Metatranscriptome analysis indicated that Sphagnum host defense was downregulated when in direct contact with the Nostoc symbiont, but not as a result of chemical contact alone. The observations in this study elucidated environmental, metabolic, and physiological underpinnings of the widespread plant-cyanobacterial symbioses with important implications for predicting carbon and nitrogen cycling in peatland ecosystems as well as the basis of general host-microbe interactions.

Unfolded Protein Response Inhibition Reduces Middle East Respiratory Syndrome Coronavirus-Induced Acute Lung Injury.

Tissue- and cell-specific expression patterns are highly variable within and across individuals, leading to altered host responses after acute virus infection. Unraveling key tissue-specific response patterns provides novel opportunities for defining fundamental mechanisms of virus-host interaction in disease and the identification of critical tissue-specific networks for disease intervention in the lung. Currently, there are no approved therapeutics for Middle East respiratory syndrome coronavirus (MERS-CoV) patients, and little is understood about how lung cell types contribute to disease outcomes. MERS-CoV replicates equivalently in primary human lung microvascular endothelial cells (MVE) and fibroblasts (FB) and to equivalent peak titers but with slower replication kinetics in human airway epithelial cell cultures (HAE). However, only infected MVE demonstrate observable virus-induced cytopathic effect. To explore mechanisms leading to reduced MVE viability, donor-matched human lung MVE, HAE, and FB were infected, and their transcriptomes, proteomes, and lipidomes were monitored over time. Validated functional enrichment analysis demonstrated that MERS-CoV-infected MVE were dying via an unfolded protein response (UPR)-mediated apoptosis. Pharmacologic manipulation of the UPR in MERS-CoV-infected primary lung cells reduced viral titers and in male mice improved respiratory function with accompanying reductions in weight loss, pathological signatures of acute lung injury, and times to recovery. Systems biology analysis and validation studies of global kinetic transcript, protein, and lipid data sets confirmed that inhibition of host stress pathways that are differentially regulated following MERS-CoV infection of different tissue types can alleviate symptom progression to end-stage lung disease commonly seen following emerging coronavirus outbreaks. IMPORTANCE Middle East respiratory syndrome coronavirus (MERS-CoV) causes severe atypical pneumonia in infected individuals, but the underlying mechanisms of pathogenesis remain unknown. While much has been learned from the few reported autopsy cases, an in-depth understanding of the cells targeted by MERS-CoV in the human lung and their relative contribution to disease outcomes is needed. The host response in MERS-CoV-infected primary human lung microvascular endothelial (MVE) cells and fibroblasts (FB) was evaluated over time by analyzing total RNA, proteins, and lipids to determine the cellular pathways modulated postinfection. Findings revealed that MERS-CoV-infected MVE cells die via apoptotic mechanisms downstream of the unfolded protein response (UPR). Interruption of enzymatic processes within the UPR in MERS-CoV-infected male mice reduced disease symptoms, virus-induced lung injury, and time to recovery. These data suggest that the UPR plays an important role in MERS-CoV infection and may represent a host target for therapeutic intervention.

Hypergraph models of biological networks to identify genes critical to pathogenic viral response.

BACKGROUND: Representing biological networks as graphs is a powerful approach to reveal underlying patterns, signatures, and critical components from high-throughput biomolecular data. However, graphs do not natively capture the multi-way relationships present among genes and proteins in biological systems. Hypergraphs are generalizations of graphs that naturally model multi-way relationships and have shown promise in modeling systems such as protein complexes and metabolic reactions. In this paper we seek to understand how hypergraphs can more faithfully identify, and potentially predict, important genes based on complex relationships inferred from genomic expression data sets. RESULTS: We compiled a novel data set of transcriptional host response to pathogenic viral infections and formulated relationships between genes as a hypergraph where hyperedges represent significantly perturbed genes, and vertices represent individual biological samples with specific experimental conditions. We find that hypergraph betweenness centrality is a superior method for identification of genes important to viral response when compared with graph centrality. CONCLUSIONS: Our results demonstrate the utility of using hypergraphs to represent complex biological systems and highlight central important responses in common to a variety of highly pathogenic viruses.

Re-routing of Sugar Catabolism Provides a Better Insight Into Fungal Flexibility in Using Plant Biomass-Derived Monomers as Substrates.

The filamentous ascomycete Aspergillus niger has received increasing interest as a cell factory, being able to efficiently degrade plant cell wall polysaccharides as well as having an extensive metabolism to convert the released monosaccharides into value added compounds. The pentoses D-xylose and L-arabinose are the most abundant monosaccharides in plant biomass after the hexose D-glucose, being major constituents of xylan, pectin and xyloglucan. In this study, the influence of selected pentose catabolic pathway (PCP) deletion strains on growth on plant biomass and re-routing of sugar catabolism was addressed to gain a better understanding of the flexibility of this fungus in using plant biomass-derived monomers. The transcriptome, metabolome and proteome response of three PCP mutant strains, ΔlarAΔxyrAΔxyrB, ΔladAΔxdhAΔsdhA and ΔxkiA, grown on wheat bran (WB) and sugar beet pulp (SBP), was evaluated. Our results showed that despite the absolute impact of these PCP mutations on pure pentose sugars, they are not as critical for growth of A. niger on more complex biomass substrates, such as WB and SBP. However, significant phenotypic variation was observed between the two biomass substrates, but also between the different PCP mutants. This shows that the high sugar heterogeneity of these substrates in combination with the high complexity and adaptability of the fungal sugar metabolism allow for activation of alternative strategies to support growth.

Intracellular pathways for lignin catabolism in white-rot fungi.

Lignin is a biopolymer found in plant cell walls that accounts for 30% of the organic carbon in the biosphere. White-rot fungi (WRF) are considered the most efficient organisms at degrading lignin in nature. While lignin depolymerization by WRF has been extensively studied, the possibility that WRF are able to utilize lignin as a carbon source is still a matter of controversy. Here, we employ 13C-isotope labeling, systems biology approaches, and in vitro enzyme assays to demonstrate that two WRF, Trametes versicolor and Gelatoporia subvermispora, funnel carbon from lignin-derived aromatic compounds into central carbon metabolism via intracellular catabolic pathways. These results provide insights into global carbon cycling in soil ecosystems and furthermore establish a foundation for employing WRF in simultaneous lignin depolymerization and bioconversion to bioproducts-a key step toward enabling a sustainable bioeconomy.

Night shift schedule causes circadian dysregulation of DNA repair genes and elevated DNA damage in humans.

Circadian disruption has been identified as a risk factor for health disorders such as obesity, cardiovascular disease, and cancer. Although epidemiological studies suggest an increased risk of various cancers associated with circadian misalignment due to night shift work, the underlying mechanisms have yet to be elucidated. We sought to investigate the potential mechanistic role that circadian disruption of cancer hallmark pathway genes may play in the increased cancer risk in shift workers. In a controlled laboratory study, we investigated the circadian transcriptome of cancer hallmark pathway genes and associated biological pathways in circulating leukocytes obtained from healthy young adults during a 24-hour constant routine protocol following 3 days of simulated day shift or night shift. The simulated night shift schedule significantly altered the normal circadian rhythmicity of genes involved in cancer hallmark pathways. A DNA repair pathway showed significant enrichment of rhythmic genes following the simulated day shift schedule, but not following the simulated night shift schedule. In functional assessments, we demonstrated that there was an increased sensitivity to both endogenous and exogenous sources of DNA damage after exposure to simulated night shift. Our results suggest that circadian dysregulation of DNA repair may increase DNA damage and potentiate elevated cancer risk in night shift workers.

Metabolic Interactions between Brachypodium and Pseudomonas fluorescens under Controlled Iron-Limited Conditions.

Iron (Fe) availability has well-known effects on plant and microbial metabolism, but its effects on interspecies interactions are poorly understood. The purpose of this study was to investigate metabolite exchange between the grass Brachypodium distachyon strain Bd21 and the soil bacterium Pseudomonas fluorescens SBW25::gfp/lux (SBW25) during Fe limitation under axenic conditions. We compared the transcriptional profiles and root exudate metabolites of B. distachyon plants grown semihydroponically with and without SBW25 inoculation and Fe amendment. Liquid chromatography-mass spectrometry analysis of the hydroponic solution revealed an increase in the abundance of the phytosiderophores mugineic acid and deoxymugineic acid under Fe-limited conditions compared to Fe-replete conditions, indicating greater secretion by roots presumably to facilitate Fe uptake. In SBW25-inoculated roots, expression of genes encoding phytosiderophore biosynthesis and uptake proteins increased compared to that in sterile roots, but external phytosiderophore abundances decreased. P. fluorescens siderophores were not detected in treatments without Fe. Rather, expression of SBW25 genes encoding a porin, a transporter, and a monooxygenase was significantly upregulated in response to Fe deprivation. Collectively, these results suggest that SBW25 consumed root-exuded phytosiderophores in response to Fe deficiency, and we propose target genes that may be involved. SBW25 also altered the expression of root genes encoding defense-related enzymes and regulators, including thionin and cyanogenic glycoside production, chitinase, and peroxidase activity, and transcription factors. Our findings provide insights into the molecular bases for the stress response and metabolite exchange of interacting plants and bacteria under Fe-deficient conditions.IMPORTANCE Rhizosphere bacteria influence the growth of their host plant by consuming and producing metabolites, nutrients, and antibiotic compounds within the root system that affect plant metabolism. Under Fe-limited growth conditions, different plant and microbial species have distinct Fe acquisition strategies, often involving the secretion of strong Fe-binding chelators that scavenge Fe and facilitate uptake. Here, we studied interactions between P. fluorescens SBW25, a plant-colonizing bacterium that produces siderophores with antifungal properties, and B. distachyon, a genetic model for cereal grain and biofuel grasses. Under controlled growth conditions, bacterial siderophore production was inhibited in the root system of Fe-deficient plants, bacterial inoculation altered transcription of genes involved in defense and stress response in the roots of B. distachyon, and SBW25 degraded phytosiderophores secreted by the host plant. These findings provide mechanistic insight into interactions that may play a role in rhizosphere dynamics and plant health in soils with low Fe solubility.

Comprehensive Proteomics Analysis of Stressed Human Islets Identifies GDF15 as a Target for Type 1 Diabetes Intervention.

Type 1 diabetes (T1D) results from the progressive loss of ß cells, a process propagated by pro-inflammatory cytokine signaling that disrupts the balance between pro- and anti-apoptotic proteins. To identify proteins involved in this process, we performed comprehensive proteomics of human pancreatic islets treated with interleukin-1ß and interferon-γ, leading to the identification of 11,324 proteins, of which 387 were significantly regulated by treatment. We then tested the function of growth/differentiation factor 15 (GDF15), which was repressed by the treatment. We found that GDF15 translation was blocked during inflammation, and it was depleted in islets from individuals with T1D. The addition of exogenous GDF15 inhibited interleukin-1ß+interferon-γ-induced apoptosis of human islets. Administration of GDF15 reduced by 53% the incidence of diabetes in NOD mice. Our approach provides a unique resource for the identification of the human islet proteins regulated by cytokines and was effective in discovering a potential target for T1D therapy.

Automated mass spectrometry imaging of over 2000 proteins from tissue sections at 100-µm spatial resolution.

Biological tissues exhibit complex spatial heterogeneity that directs the functions of multicellular organisms. Quantifying protein expression is essential for elucidating processes within complex biological assemblies. Imaging mass spectrometry (IMS) is a powerful emerging tool for mapping the spatial distribution of metabolites and lipids across tissue surfaces, but technical challenges have limited the application of IMS to the analysis of proteomes. Methods for probing the spatial distribution of the proteome have generally relied on the use of labels and/or antibodies, which limits multiplexing and requires a priori knowledge of protein targets. Past efforts to make spatially resolved proteome measurements across tissues have had limited spatial resolution and proteome coverage and have relied on manual workflows. Here, we demonstrate an automated approach to imaging that utilizes label-free nanoproteomics to analyze tissue voxels, generating quantitative cell-type-specific images for >2000 proteins with 100-µm spatial resolution across mouse uterine tissue sections preparing for blastocyst implantation.

Colonies of the fungus Aspergillus niger are highly differentiated to adapt to local carbon source variation.

Saprobic fungi, such as Aspergillus niger, grow as colonies consisting of a network of branching and fusing hyphae that are often considered to be relatively uniform entities in which nutrients can freely move through the hyphae. In nature, different parts of a colony are often exposed to different nutrients. We have investigated, using a multi-omics approach, adaptation of A. niger colonies to spatially separated and compositionally different plant biomass substrates. This demonstrated a high level of intra-colony differentiation, which closely matched the locally available substrate. The part of the colony exposed to pectin-rich sugar beet pulp and to xylan-rich wheat bran showed high pectinolytic and high xylanolytic transcript and protein levels respectively. This study therefore exemplifies the high ability of fungal colonies to differentiate and adapt to local conditions, ensuring efficient use of the available nutrients, rather than maintaining a uniform physiology throughout the colony.

The Role of EGFR in Influenza Pathogenicity: Multiple Network-Based Approaches to Identify a Key Regulator of Non-lethal Infections.

Despite high sequence similarity between pandemic and seasonal influenza viruses, there is extreme variation in host pathogenicity from one viral strain to the next. Identifying the underlying mechanisms of variability in pathogenicity is a critical task for understanding influenza virus infection and effective management of highly pathogenic influenza virus disease. We applied a network-based modeling approach to identify critical functions related to influenza virus pathogenicity using large transcriptomic and proteomic datasets from mice infected with six influenza virus strains or mutants. Our analysis revealed two pathogenicity-related gene expression clusters; these results were corroborated by matching proteomics data. We also identified parallel downstream processes that were altered during influenza pathogenesis. We found that network bottlenecks (nodes that bridge different network regions) were highly enriched in pathogenicity-related genes, while network hubs (highly connected network nodes) were significantly depleted in these genes. We confirmed that this trend persisted in a distinct virus: Severe Acute Respiratory Syndrome Coronavirus (SARS). The role of epidermal growth factor receptor (EGFR) in influenza pathogenesis, one of the bottleneck regulators with corroborating signals across transcript and protein expression data, was tested and validated in additional mouse infection experiments. We demonstrate that EGFR is important during influenza infection, but the role it plays changes for lethal versus non-lethal infections. Our results show that by using association networks, bottleneck genes that lack hub characteristics can be used to predict a gene's involvement in influenza virus pathogenicity. We also demonstrate the utility of employing multiple network approaches for analyzing host response data from viral infections.