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Senescence is a non-proliferative, survival state that cancer cells can enter to escape therapy. In addition to soluble factors, senescence cells secrete extracellular vesicles (EVs), which are important mediators of intercellular communication. To explore the role of senescent cell-derived EVs (senEVs) in inflammatory responses to senescence, we developed an engraftment-based senescence model in wild-type mice and genetically blocked senEV release in vivo, without significantly affecting soluble mediators. SenEVs were both necessary and sufficient to trigger immune-mediated clearance of senescent cells, thereby suppressing tumor growth. In the absence of senEVs, the recruitment of MHC-II+ antigen-presenting cells to the senescence microenvironment was markedly impaired. Blocking senEV release redirected the primary target of senescent cell signaling from antigen-presenting cells to neutrophils. Comprehensive transcriptional and proteomic analyses identified six ligands specific to senEVs, highlighting their role in promoting antigen-presenting cell-T cell adhesion and synapse formation. Antigen-presenting cells activated CCR2+CD4+ TH17 cells, which appeared to inhibit B cell activation, and CD4+ T cells were essential for preventing tumor recurrence. These findings suggest that senEVs complement the activity of secreted inflammatory mediators by recruiting and activating distinct immune cell subsets, thereby enhancing the efficient clearance of senescent cells. These conclusions may have implications not only for tumor recurrence but also for understanding senescence during de novo carcinogenesis. Consequently, this work could inform the development of early detection strategies for cancer based on the biology of cellular senescence.

Introduction: Human metabolomics has made significant strides in understanding metabolic changes and their implications for human health, with promising applications in diagnostics and treatment, particularly regarding the gut microbiome. However, progress is hampered by issues with data comparability and reproducibility across studies, limiting the translation of these discoveries into practical applications., Objectives: This study aims to evaluate the fit-for-purpose of a suite of human stool samples as potential candidate reference materials (RMs) and assess the state of the field regarding harmonizing gut metabolomics measurements., Methods: An interlaboratory study was conducted with 18 participating institutions. The study allowed for the use of preferred analytical techniques, including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS), and nuclear magnetic resonance (NMR)., Results: Different laboratories used various methods and analytical platforms to identify the metabolites present in human stool RM samples. The study found a 40% to 70% recurrence in the reported top 20 most abundant metabolites across the four materials. In the full annotation list, the percentage of metabolites reported multiple times after nomenclature standardization was 36% (LC-MS), 58% (GC-MS) and 76% (NMR). Out of 9,300 unique metabolites, only 37 were reported across all three measurement techniques., Conclusion: This collaborative exercise emphasized the broad chemical survey possible with multi-technique approaches. Community engagement is essential for the evaluation and characterization of common materials designed to facilitate comparability and ensure data quality underscoring the value of determining current practices, challenges, and progress of a field through interlaboratory studies., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Lysine and arginine methylation is an important regulator of enzyme activity and transcription in eukaryotes. However, little is known about this covalent modification in bacteria. In this work, we investigated the role of methylation in bacteria. By reanalyzing a large phyloproteomics data set from 48 bacterial strains representing six phyla, we found that almost a quarter of the bacterial proteome is methylated. Many of these methylated proteins are conserved across diverse bacterial lineages, including those involved in central carbon metabolism and translation. Among the proteins with the most conserved methylation sites is ribosomal protein L11 (bL11). bL11 methylation has been a mystery for five decades, as the deletion of its methyltransferase PrmA causes no cell growth defects. Comparative proteomics analysis combined with inorganic polyphosphate and guanosine tetra/pentaphosphate assays of the ΔprmA mutant in Escherichia coli revealed that bL11 methylation is important for stringent response signaling. In the stationary phase, we found that the ΔprmA mutant has impaired guanosine tetra/pentaphosphate production. This leads to a reduction in inorganic polyphosphate levels, accumulation of RNA and ribosomal proteins, and an abnormal polysome profile. Overall, our investigation demonstrates that the evolutionarily conserved bL11 methylation is important for stringent response signaling and ribosomal activity regulation and turnover., Importance: Protein methylation in bacteria was first identified over 60 years ago. Since then, its functional role has been identified for only a few proteins. To better understand the functional role of methylation in bacteria, we analyzed a large phyloproteomics data set encompassing 48 diverse bacteria. Our analysis revealed that ribosomal proteins are often methylated at conserved residues, suggesting that methylation of these sites may have a functional role in translation. Further analysis revealed that methylation of ribosomal protein L11 is important for stringent response signaling and ribosomal homeostasis., Competing Interests: The authors declare no conflict of interest.

Understanding fungal lipid biology and metabolism is critical for antifungal target discovery as lipids play central roles in cellular processes. Nuances in lipid structural differences can significantly impact their functions, making it necessary to characterize lipids in detail to understand their roles in these complex systems. In particular, lipid double bond (DB) locations are an important component of lipid structure that can only be determined using a few specialized analytical techniques. Ozone-induced dissociation mass spectrometry (OzID-MS) is one such technique that uses ozone to break lipid DBs, producing pairs of characteristic fragments that allow the determination of DB positions. In this work, we apply OzID-MS and LipidOz software to analyze the complex lipids of Saccharomyces cerevisiae yeast strains transformed with different fatty acid desaturases from Histoplasma capsulatum to determine the specific unsaturated lipids produced. The automated data analysis in LipidOz made the determination of DB positions from this large dataset more practical, but manual verification for all targets was still time-consuming. The DL model reduces manual involvement in data analysis, but since it was trained using mammalian lipid extracts, the prediction accuracy on yeast-derived data was reduced. We addressed both shortcomings by retraining the DL model to act as a pre-filter to prioritize targets for automated analysis, providing confident manually verified results but requiring less computational time and manual effort. Our workflow resulted in the determination of detailed DB positions and enzymatic specificity., (© 2024 Battelle Memorial Institute. Journal of Mass Spectrometry published by John Wiley & Sons Ltd.)

Microbial conversion of lignocellulosic biomass represents an alternative route for production of biofuels and bioproducts. While researchers have mostly focused on engineering strains such as Rhodotorula toruloides for better bisabolene production as a sustainable aviation fuel, less is known about the impact of the feedstock heterogeneity on bisabolene production. Critical material attributes like feedstock composition, nutritional content, and inhibitory compounds can all influence bioconversion. Further, the given feedstocks can have a marked influence on selection of suitable pretreatment and hydrolysis technologies, optimizing the fermentation conditions, and possibly even modifying the microorganism's metabolic pathways, to better utilize the available feedstock. This work aimed to examine and understand how variations in corn stover batches, anatomical fractions, and storage conditions impact the efficiency of bisabolene production by R. toruloides. All of these represent different facets of feedstock heterogeneity. Deacetylation, mechanical refining, and enzymatic hydrolysis of these variable feedstocks served as the basis of this research. The resulting hydrolysates were converted to bisabolene via fermentation, a sustainable aviation fuel precursor, using an engineered R. toruloides strain. This study showed that different sources of feedstock heterogeneity can influence microbial growth and product titer in counterintuitive ways, as revealed through global analysis of protein expression. The maximum bisabolene produced by R. toruloides was on the stalk fraction of corn stover hydrolysate (8.89 ± 0.47 g/L). Further, proteomics analysis comparing the protein expression between the anatomic fractions showed that proteins relating to carbohydrate metabolism, energy production, and conversion as well as inorganic ion transport metabolism were either significantly upregulated or downregulated. Specifically, downregulation of proteins related to the iron-sulfur cluster in stalk fraction suggests a coordinated response by R. toruloides to maintain overall metabolic balance, and this was corroborated by the concentration of iron in the feedstocks., One-Sentence Summary: This study elucidates the effects of different sources of corn stover on bisabolene production by engineered Rhodotorula toruloides, highlighting the importance of understanding feedstock variability to enhance bioprocess efficiency and economic outcomes., (Published by Oxford University Press on behalf of Society of Industrial Microbiology and Biotechnology 2024.)

Efficient conversion of pentose sugars remains a significant barrier to the replacement of petroleum-derived chemicals with plant biomass-derived bioproducts. While the oleaginous yeast Rhodosporidium toruloides (also known as Rhodotorula toruloides) has a relatively robust native metabolism of pentose sugars compared to other wild yeasts, faster assimilation of those sugars will be required for industrial utilization of pentoses. To increase the rate of pentose assimilation in R. toruloides, we leveraged previously reported high-throughput fitness data to identify potential regulators of pentose catabolism. Two genes were selected for further investigation, a putative transcription factor (RTO4_12978, Pnt1) and a homolog of a glucose transceptor involved in carbon catabolite repression (RTO4_11990). Overexpression of Pnt1 increased the specific growth rate approximately twofold early in cultures on xylose and increased the maximum specific growth by 18% while decreasing accumulation of arabitol and xylitol in fast-growing cultures. Improved growth dynamics on xylose translated to a 120% increase in the overall rate of xylose conversion to fatty alcohols in batch culture. Proteomic analysis confirmed that Pnt1 is a major regulator of pentose catabolism in R. toruloides. Deletion of RTO4_11990 increased the growth rate on xylose, but did not relieve carbon catabolite repression in the presence of glucose. Carbon catabolite repression signaling networks remain poorly characterized in R. toruloides and likely comprise a different set of proteins than those mainly characterized in ascomycete fungi., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Lipids play essential roles in many biological processes and disease pathology, but unambiguous identification of lipids is complicated by the presence of multiple isomeric species differing by fatty acyl chain length, stereospecifically numbered (sn) position, and position/stereochemistry of double bonds. Conventional liquid chromatography-mass spectrometry (LC-MS/MS) analyses enable the determination of fatty acyl chain lengths (and in some cases sn position) and number of double bonds, but not carbon-carbon double bond positions. Ozone-induced dissociation (OzID) is a gas-phase oxidation reaction that produces characteristic fragments from lipids containing double bonds. OzID can be incorporated into ion mobility spectrometry (IMS)-MS instruments for the structural characterization of lipids, including additional isomer separation and confident assignment of double bond positions. The complexity and repetitive nature of OzID data analysis and lack of software tool support have limited the application of OzID for routine lipidomics studies. Here, we present an open-source Python tool, LipidOz, for the automated determination of lipid double bond positions from OzID-IMS-MS data, which employs a combination of traditional automation and deep learning approaches. Our results demonstrate the ability of LipidOz to robustly assign double bond positions for lipid standard mixtures and complex lipid extracts, enabling practical application of OzID for future lipidomics., (© 2023. Battelle Memorial Institute.)

Graphene oxide (GO) nanomaterials have unique physicochemical properties that make them highly promising for biomedical, environmental, and agricultural applications. There is growing interest in the use of GO and extensive in vitro and in vivo studies have been conducted to assess its nanotoxicity. Although it is known that GO can alter the composition of the gut microbiota in mice and zebrafish, studies on the potential impacts of GO on the human gut microbiome are largely lacking. This study addresses an important knowledge gap by investigating the impact of GO exposure- at low (25 mg/L) and high (250 mg/L) doses under both fed (nutrient rich) and fasted (nutrient deplete) conditions- on the gut microbial communitys' structure and function, using an in vitro model. This model includes simulated oral, gastric, small intestinal phase digestion of GO followed by incubation in a colon bioreactor. 16S rRNA amplicon sequencing revealed that GO exposure resulted in a restructuring of community composition. 25 mg/L GO induced a marked decrease in the Bacteroidota phylum and increased the ratio of Firmicutes to Bacteroidota (F/B). Untargeted metabolomics on the supernatants indicated that 25 mg/L GO impaired microbial utilization and metabolism of substrates (amino acids, carbohydrate metabolites) and reduced production of beneficial microbial metabolites such as 5-hydroxyindole-3-acetic acid and GABA. Exposure to 250 mg/L GO resulted in community composition and metabolome profiles that were very similar to the controls that lacked both GO and digestive enzymes. Differential abundance analyses revealed that 3 genera from the phylum Bacteroidota (Bacteroides, Dysgonomonas, and Parabacteroides) were more abundant after 250 mg/L GO exposure, irrespective of feed state. Integrative correlation network analysis indicated that the phylum Bacteroidota showed strong positive correlations to multiple microbial metabolites including GABA and 3-indoleacetic acid, are much larger number of correlations compared to other phyla. These results show that GO exposure has a significant impact on gut microbial community composition and metabolism at both low and high GO concentrations., Competing Interests: Declaration of Competing Interest There are no conflicts to declare., (Copyright © 2023 Battelle Memorial Institute, The Author(s). Published by Elsevier B.V. All rights reserved.)

The global regulator LaeA controls secondary metabolism in diverse Aspergillus species. Here we explored its role in regulation of itaconic acid production in Aspergillus pseudoterreus . To understand its role in regulating metabolism, we deleted and overexpressed laeA, and assessed the transcriptome, proteome, and secreted metabolome prior to and during initiation of phosphate limitation induced itaconic acid production. We found that secondary metabolite clusters, including the itaconic acid biosynthetic gene cluster, are regulated by laeA and that laeA is required for high yield production of itaconic acid. Overexpression of LaeA improves itaconic acid yield at the expense of biomass by increasing the expression of key biosynthetic pathway enzymes and attenuating the expression of genes involved in phosphate acquisition and scavenging. Increased yield was observed in optimized conditions as well as conditions containing excess nutrients that may be present in inexpensive sugar containing feedstocks such as excess phosphate or complex nutrient sources. This suggests that global regulators of metabolism may be useful targets for engineering metabolic flux that is robust to environmental heterogeneity., Competing Interests: The authors declare no competing interests., (© 2022 The Authors.)

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.

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.

Optimizing the metabolism of microbial cell factories for yields and titers is a critical step for economically viable production of bioproducts and biofuels. In this process, tuning the expression of individual enzymes to obtain the desired pathway flux is a challenging step, in which data from separate multiomics techniques must be integrated with existing biological knowledge to determine where changes should be made. Following a design-build-test-learn strategy, building on recent advances in Bayesian metabolic control analysis, we identify key enzymes in the oleaginous yeast Yarrowia lipolytica that correlate with the production of itaconate by integrating a metabolic model with multiomics measurements. To this extent, we quantify the uncertainty for a variety of key parameters, known as flux control coefficients (FCCs), needed to improve the bioproduction of target metabolites and statistically obtain key correlations between the measured enzymes and boundary flux. Based on the top five significant FCCs and five correlated enzymes, our results show phosphoglycerate mutase, acetyl-CoA synthetase (ACSm), carbonic anhydrase (HCO3E), pyrophosphatase (PPAm), and homoserine dehydrogenase (HSDxi) enzymes in rate-limiting reactions that can lead to increased itaconic acid production.

Extracellular vesicles (EVs) are lipid bilayer structures released by organisms from all kingdoms of life. The diverse biogenesis pathways of EVs result in a wide variety of physical properties and functions across different organisms. Fungal EVs were first described in 2007 and different omics approaches have been fundamental to understand their composition, biogenesis, and function. In this review, we discuss the role of omics in elucidating fungal EVs biology. Transcriptomics, proteomics, metabolomics, and lipidomics have each enabled the molecular characterization of fungal EVs, providing evidence that these structures serve a wide array of functions, ranging from key carriers of cell wall biosynthetic machinery to virulence factors. Omics in combination with genetic approaches have been instrumental in determining both biogenesis and cargo loading into EVs. We also discuss how omics technologies are being employed to elucidate the role of EVs in antifungal resistance, disease biomarkers, and their potential use as vaccines. Finally, we review recent advances in analytical technology and multi-omic integration tools, which will help to address key knowledge gaps in EVs biology and translate basic research information into urgently needed clinical applications such as diagnostics, and immuno- and chemotherapies to fungal infections., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Zamith-Miranda, Peres da Silva, Couvillion, Bredeweg, Burnet, Coelho, Camacho, Nimrichter, Puccia, Almeida, Casadevall, Rodrigues, Alves, Nosanchuk and Nakayasu.)

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 13 C-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., Competing Interests: The authors declare no competing interest.

We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography-mass spectrometry (GC-MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC-MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples.

Targeted proteomics is a mass spectrometry-based protein quantification technique with high sensitivity, accuracy, and reproducibility. As a key component in the multi-omics toolbox of systems biology, targeted liquid chromatography-selected reaction monitoring (LC-SRM) measurements are critical for enzyme and pathway identification and design in metabolic engineering. To fulfill the increasing need for analyzing large sample sets with faster turnaround time in systems biology, high-throughput LC-SRM is greatly needed. Even though nanoflow LC-SRM has better sensitivity, it lacks the speed offered by microflow LC-SRM. Recent advancements in mass spectrometry instrumentation significantly enhance the scan speed and sensitivity of LC-SRM, thereby creating opportunities for applying the high speed of microflow LC-SRM without losing peptide multiplexing power or sacrificing sensitivity. Here, we studied the performance of microflow LC-SRM relative to nanoflow LC-SRM by monitoring 339 peptides representing 132 enzymes in Pseudomonas putida KT2440 grown on various carbon sources. The results from the two LC-SRM platforms are highly correlated. In addition, the response curve study of 248 peptides demonstrates that microflow LC-SRM has comparable sensitivity for the majority of detected peptides and better mass spectrometry signal and chromatography stability than nanoflow LC-SRM., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer LB declared a past co-authorship with one of the authors GTB to the handling editor., (Copyright © 2020 Gao, Fillmore, Munoz, Bentley, Johnson, Kim, Meadows, Zucker, Burnet, Lipton, Bilbao, Orton, Kim, Moore, Robinson, Baker, Webb-Robertson, Guss, Gladden, Beckham, Magnuson and Burnum-Johnson.)

The development of Pseudomonas strains for industrial production of fuels and chemicals will require the integration of heterologous genes and pathways into the chromosome. Finding the most appropriate integration site to maximize strain performance is an essential part of the strain design process. We characterized seven chromosomal loci in Pseudomonas putida KT2440 for integration of a fluorescent protein expression construct. Insertion in five of the loci did not affect growth rate, but fluorescence varied by up to 27-fold. Three sites displaying a diversity of phenotypes with the fluorescent reporter were also chosen for the integration of a gene encoding a muconate importer. Depending on the integration locus, expression of the importer varied by approximately 3-fold and produced significant phenotypic differences. This work demonstrates the impact of the integration location on host viability, gene expression, and overall strain performance., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2020 The Authors.)

Antibodies play a central role in host immunity by directly inactivating or recognizing an invading pathogen to enhance different immune responses to combat the invader. However, the cellular responses of pathogens to the presence of antibodies are not well-characterized. Here, we used different mass spectrometry techniques to study the cellular responses of the pathogenic fungus Histoplasma capsulatum to monoclonal antibodies (mAb) against HSP60, the surface protein involved in infection. A proteomic analysis of H. capsulatum yeast cells revealed that mAb binding regulates a variety of metabolic and signaling pathways, including fatty acid metabolism, sterol metabolism, MAPK signaling and ubiquitin-mediated proteolysis. The regulation of the fatty acid metabolism was accompanied by increases in the level of polyunsaturated fatty acids, which further augmented the degree of unsaturated lipids in H. capsulatum 's membranes and energy storage lipids, such as triacylglycerols, phosphatidylcholines, phosphatidylethanolamines and phosphatidylinositols. MAb treatment also regulated sterol metabolism by increasing the levels of cholesterol and ergosterol in the cells. We also showed that global changes in the lipid profiles resulted in an increased susceptibility of H. capsulatum to the ergosterol-targeting drug amphotericin B. Overall, our data showed that mAb induction of global changes in the composition of H. capsulatum membranes can potentially impact antifungal treatment during histoplasmosis.

Outer membrane vesicles produced by Gram-negative bacteria have been studied for half a century but the possibility that Gram-positive bacteria secrete extracellular vesicles (EVs) was not pursued until recently due to the assumption that the thick peptidoglycan cell wall would prevent their release to the environment. However, following their discovery in fungi, which also have cell walls, EVs have now been described for a variety of Gram-positive bacteria. EVs purified from Gram-positive bacteria are implicated in virulence, toxin release, and transference to host cells, eliciting immune responses, and spread of antibiotic resistance. Listeria monocytogenes is a Gram-positive bacterium that causes listeriosis. Here we report that L. monocytogenes produces EVs with diameters ranging from 20 to 200 nm, containing the pore-forming toxin listeriolysin O (LLO) and phosphatidylinositol-specific phospholipase C (PI-PLC). Cell-free EV preparations were toxic to mammalian cells, the murine macrophage cell line J774.16, in a LLO-dependent manner, evidencing EV biological activity. The deletion of plcA increased EV toxicity, suggesting PI-PLC reduced LLO activity. Using simultaneous m etabolite, p rotein, and l ipid ex traction (MPLEx) multiomics we characterized protein, lipid, and metabolite composition of bacterial cells and secreted EVs and found that EVs carry the majority of listerial virulence proteins. Using immunogold EM we detected LLO at several organelles within infected human epithelial cells and with high-resolution fluorescence imaging we show that dynamic lipid structures are released from L. monocytogenes during infection. Our findings demonstrate that L. monocytogenes uses EVs for toxin release and implicate these structures in mammalian cytotoxicity., Competing Interests: The authors declare that they have no conflicts of interest with the contents of this article. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health., (© 2019 Coelho et al.)

Diverse pathogenic fungi secrete extracellular vesicles (EV) that contain macromolecules, including virulence factors that can modulate the host immune response. We recently demonstrated that the binding of monoclonal antibodies (mAb) modulates how Histoplasma capsulatum load and releases its extracellular vesicles (EV). In the present paper, we addressed a concentration-dependent impact on the fungus' EV loading and release with different mAb, as well as the pathophysiological role of these EV during the host-pathogen interaction. We found that the mAbs differentially regulate EV content in concentration-dependent and independent manners. Enzymatic assays demonstrated that laccase activity in EV from H. capsulatum opsonized with 6B7 was reduced, but urease activity was not altered. The uptake of H. capsulatum by macrophages pre-treated with EV, presented an antibody concentration-dependent phenotype. The intracellular killing of yeast cells was potently inhibited in macrophages pre-treated with EV from 7B6 (non-protective) mAb-opsonized H. capsulatum and this inhibition was associated with a decrease in the reactive-oxygen species generated by these macrophages. In summary, our findings show that opsonization quantitatively and qualitatively modifies H. capsulatum EV load and secretion leading to distinct effects on the host's immune effector mechanisms, supporting the hypothesis that EV sorting and secretion are dynamic mechanisms for a fine-tuned response by fungal cells.

Lysine acetylation is a common protein post-translational modification in bacteria and eukaryotes. Unlike phosphorylation, whose functional role in signaling has been established, it is unclear what regulatory mechanism acetylation plays and whether it is conserved across evolution. By performing a proteomic analysis of 48 phylogenetically distant bacteria, we discovered conserved acetylation sites on catalytically essential lysine residues that are invariant throughout evolution. Lysine acetylation removes the residue's charge and changes the shape of the pocket required for substrate or cofactor binding. Two-thirds of glycolytic and tricarboxylic acid (TCA) cycle enzymes are acetylated at these critical sites. Our data suggest that acetylation may play a direct role in metabolic regulation by switching off enzyme activity. We propose that protein acetylation is an ancient and widespread mechanism of protein activity regulation. IMPORTANCE Post-translational modifications can regulate the activity and localization of proteins inside the cell. Similar to phosphorylation, lysine acetylation is present in both eukaryotes and prokaryotes and modifies hundreds to thousands of proteins in cells. However, how lysine acetylation regulates protein function and whether such a mechanism is evolutionarily conserved is still poorly understood. Here, we investigated evolutionary and functional aspects of lysine acetylation by searching for acetylated lysines in a comprehensive proteomic data set from 48 phylogenetically distant bacteria. We found that lysine acetylation occurs in evolutionarily conserved lysine residues in catalytic sites of enzymes involved in central carbon metabolism. Moreover, this modification inhibits enzymatic activity. Our observations suggest that lysine acetylation is an evolutionarily conserved mechanism of controlling central metabolic activity by directly blocking enzyme active sites., (Copyright © 2017 Nakayasu et al.)

Fibrobacter succinogenes S85 is an anaerobic non-cellulosome utilizing cellulolytic bacterium originally isolated from the cow rumen microbial community. Efforts to elucidate its cellulolytic machinery have resulted in the proposal of numerous models which involve cell-surface attachment via a combination of cellulose-binding fibro-slime proteins and pili, the production of cellulolytic vesicles, and the entry of cellulose fibers into the periplasmic space. Here, we used a combination of RNA-sequencing, proteomics, and transmission electron microscopy (TEM) to further clarify the cellulolytic mechanism of F. succinogenes. Our RNA-sequence analysis shows that genes encoding type II and III secretion systems, fibro-slime proteins, and pili are differentially expressed on cellulose, relative to glucose. A subcellular fractionation of cells grown on cellulose revealed that carbohydrate active enzymes associated with cellulose deconstruction and fibro-slime proteins were greater in the extracellular medium, as compared to the periplasm and outer membrane fractions. TEMs of samples harvested at mid-exponential and stationary phases of growth on cellulose and glucose showed the presence of grooves in the cellulose between the bacterial cells and substrate, suggesting enzymes work extracellularly for cellulose degradation. Membrane vesicles were only observed in stationary phase cultures grown on cellulose. These results provide evidence that F. succinogenes attaches to cellulose fibers using fibro-slime and pili, produces cellulases, such as endoglucanases, that are secreted extracellularly using type II and III secretion systems, and degrades the cellulose into cellodextrins that are then imported back into the periplasm for further digestion by β-glucanases and other cellulases.

Bacterial species in the Enterobacteriaceae typically contain multiple paralogues of a small domain of unknown function (DUF1471) from a family of conserved proteins also known as YhcN or BhsA/McbA. Proteins containing DUF1471 may have a single or three copies of this domain. Representatives of this family have been demonstrated to play roles in several cellular processes including stress response, biofilm formation, and pathogenesis. We have conducted NMR and X-ray crystallographic studies of four DUF1471 domains from Salmonella representing three different paralogous DUF1471 subfamilies: SrfN, YahO, and SssB/YdgH (two of its three DUF1471 domains: the N-terminal domain I (residues 21-91), and the C-terminal domain III (residues 244-314)). Notably, SrfN has been shown to have a role in intracellular infection by Salmonella Typhimurium. These domains share less than 35% pairwise sequence identity. Structures of all four domains show a mixed α+β fold that is most similar to that of bacterial lipoprotein RcsF. However, all four DUF1471 sequences lack the redox sensitive cysteine residues essential for RcsF activity in a phospho-relay pathway, suggesting that DUF1471 domains perform a different function(s). SrfN forms a dimer in contrast to YahO and SssB domains I and III, which are monomers in solution. A putative binding site for oxyanions such as phosphate and sulfate was identified in SrfN, and an interaction between the SrfN dimer and sulfated polysaccharides was demonstrated, suggesting a direct role for this DUF1471 domain at the host-pathogen interface.

Chemical cross-linking of proteins followed by proteolysis and mass spectrometric analysis of the resulting cross-linked peptides provides powerful insight into the quaternary structure of protein complexes. Mixed-isotope cross-linking (a method for distinguishing intermolecular cross-links) was coupled with liquid chromatography, ion mobility spectrometry and mass spectrometry (LC-IMS-MS) to provide an additional separation dimension to the traditional cross-linking approach. This method produced multiplet m/z peaks that are aligned in the IMS drift time dimension and serve as signatures of intermolecular cross-linked peptides. We developed an informatics tool to use the amino acid sequence information inherent in the multiplet spacing for accurate identification of the cross-linked peptides. Because of the separation of cross-linked and non-cross-linked peptides in drift time, our LC-IMS-MS approach was able to confidently detect more intermolecular cross-linked peptides than LC-MS alone.

Background: Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. However, determining protein-coding genes for most new genomes is almost completely performed by inference using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function., Results: We experimentally annotated the bacterial pathogen Salmonella Typhimurium 14028, using "shotgun" proteomics to accurately uncover the translational landscape and post-translational features. The data provide protein-level experimental validation for approximately half of the predicted protein-coding genes in Salmonella and suggest revisions to several genes that appear to have incorrectly assigned translational start sites, including a potential novel alternate start codon. Additionally, we uncovered 12 non-annotated genes missed by gene prediction programs, as well as evidence suggesting a role for one of these novel ORFs in Salmonella pathogenesis. We also characterized post-translational features in the Salmonella genome, including chemical modifications and proteolytic cleavages. We find that bacteria have a much larger and more complex repertoire of chemical modifications than previously thought including several novel modifications. Our in vivo proteolysis data identified more than 130 signal peptide and N-terminal methionine cleavage events critical for protein function., Conclusion: This work highlights several ways in which application of proteomics data can improve the quality of genome annotations to facilitate novel biological insights and provides a comprehensive proteome map of Salmonella as a resource for systems analysis.