A White-Box Machine Learning Approach for Revealing Antibiotic Mechanisms of Action.

Current machine learning techniques enable robust association of biological signals with measured phenotypes, but these approaches are incapable of identifying causal relationships. Here, we develop an integrated "white-box" biochemical screening, network modeling, and machine learning approach for revealing causal mechanisms and apply this approach to understanding antibiotic efficacy. We counter-screen diverse metabolites against bactericidal antibiotics in Escherichia coli and simulate their corresponding metabolic states using a genome-scale metabolic network model. Regression of the measured screening data on model simulations reveals that purine biosynthesis participates in antibiotic lethality, which we validate experimentally. We show that antibiotic-induced adenine limitation increases ATP demand, which elevates central carbon metabolism activity and oxygen consumption, enhancing the killing effects of antibiotics. This work demonstrates how prospective network modeling can couple with machine learning to identify complex causal mechanisms underlying drug efficacy.

Integrative omics indicate FMRP sequesters mRNA from translation and deadenylation in human neuronal cells.

How fragile X syndrome protein (FMRP) binds mRNAs and regulates mRNA metabolism remains unclear. Our previous work using human neuronal cells focused on mRNAs targeted for nonsense-mediated mRNA decay (NMD), which we showed are generally bound by FMRP and destabilized upon FMRP loss. Here, we identify >400 high-confidence FMRP-bound mRNAs, only ∼35% of which are NMD targets. Integrative transcriptomics together with SILAC-LC-MS/MS reveal that FMRP loss generally results in mRNA destabilization and more protein produced per FMRP target. We use our established RIP-seq technology to show that FMRP footprints are independent of protein-coding potential, target GC-rich and structured sequences, and are densest in 5' UTRs. Regardless of where within an mRNA FMRP binds, we find that FMRP protects mRNAs from deadenylation and directly binds the cytoplasmic poly(A)-binding protein. Our results reveal how FMRP sequesters polyadenylated mRNAs into stabilized and translationally repressed complexes, whose regulation is critical for neurogenesis and synaptic plasticity.

Multi-omics analysis reveals the potential pathogenesis and therapeutic targets of diabetic kidney disease.

Clinicians have long been interested in understanding the molecular basis of diabetic kidney disease (DKD)and its potential treatment targets. Its pathophysiology involves protein phosphorylation, one of the most recognizable post-transcriptional modifications, that can take part in many cellular functions and control different metabolic processes. In order to recognize the molecular and protein changes of DKD kidney, this study applied Tandem liquid chromatography-mass spectrometry (LC-MS/MS) and Next-Generation Sequencing, along with Tandem Mass Tags (TMT) labeling techniques to evaluate the mRNA, protein and modified phosphorylation sites between DKD mice and model ones. Based on Gene Ontology (GO) and KEGG pathway analyses of transcriptome and proteome, The molecular changes of DKD include accumulation of extracellular matrix, abnormally activated inflammatory microenvironment, oxidative stress and lipid metabolism disorders, leading to glomerulosclerosis and tubulointerstitial fibrosis. Oxidative stress has been emphasized as an important factor in DKD and progression to ESKD, which is directly related to podocyte injury, albuminuria and renal tubulointerstitial fibrosis. A histological study of phosphorylation further revealed that kinases were crucial. Three groups of studies have found that RAS signaling pathway, RAP1 signaling pathway, AMPK signaling pathway, PPAR signaling pathway and HIF-1 signaling pathway were crucial for the pathogenesis of DKD. Through this approach, it was discovered that targeting specific molecules, proteins, kinases and critical pathways could be a promising approach for treating DKD.

Galectin-3-Binding Protein Inhibits Extracellular Heparan 6-O-Endosulfatase Sulf-2.

Human extracellular 6-O-endosulfatases Sulf-1 and Sulf-2 are the only enzymes that post-synthetically alter the 6-O sulfation of heparan sulfate proteoglycans (HSPG), which regulates interactions of HSPG with many proteins. Oncogenicity of Sulf-2 in different cancers has been documented, and we have shown that Sulf-2 is associated with poor survival outcomes in head and neck squamous cell carcinoma (HNSCC). Despite its importance, limited information is available on direct protein-protein interactions of the Sulf-2 protein in the tumor microenvironment. In this study, we used monoclonal antibody (mAb) affinity purification and mass spectrometry to identify galectin-3-binding protein (LG3BP) as a highly specific binding partner of Sulf-2 in the conditioned media of HNSCC cell lines. We validated their direct interaction in vitro using recombinant proteins and have shown that the chondroitin sulfate (CS) covalently bound to the Sulf-2 influences the binding to LG3BP. We confirmed the importance of the CS chain for the interaction by generating a mutant Sulf-2 protein that lacks the CS. Importantly, we have shown that the LG3BP inhibits Sulf-2 activity in vitro in a concentration-dependent manner. As a consequence, the addition of LG3BP to a spheroid cell culture inhibited the invasion of the HNSCC cells into Matrigel. Thus, Sulf-2 interaction with LG3BP may regulate the physiological activity of the Sulf-2 enzyme as well as its activity in the tumor microenvironment.

Direct sequencing of total Saccharomyces cerevisiae tRNAs by LC-MS/MS.

Among RNAs, transfer RNAs (tRNAs) contain the widest variety of abundant posttranscriptional chemical modifications. These modifications are crucial for tRNAs to participate in protein synthesis, promoting proper tRNA structure and aminoacylation, facilitating anticodon:codon recognition, and ensuring the reading frame maintenance of the ribosome. While tRNA modifications were long thought to be stoichiometric, it is becoming increasingly apparent that these modifications can change dynamically in response to the cellular environment. The ability to broadly characterize the fluctuating tRNA modification landscape will be essential for establishing the molecular level contributions of individual sites of tRNA modification. The locations of modifications within individual tRNA sequences can be mapped using liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). In this approach, a single tRNA species is purified, treated with ribonucleases, and the resulting single-stranded RNA products are subject to LC-MS/MS analysis. The application of LC-MS/MS to study tRNAs is limited by the necessity of analyzing one tRNA at a time, because the digestion of total tRNA mixtures by commercially available ribonucleases produces many short digestion products unable to be uniquely mapped back to a single site within a tRNA. We overcame these limitations by taking advantage of the highly structured nature of tRNAs to prevent the full digestion by single-stranded RNA-specific ribonucleases. Folding total tRNA prior to digestion allowed us to sequence Saccharomyces cerevisiae tRNAs with up to 97% sequence coverage for individual tRNA species by LC-MS/MS. This method presents a robust avenue for directly detecting the distribution of modifications in total tRNAs.

Bioinertization of NanoLC/MS/MS Systems by Depleting Metal Ions From the Mobile Phases for Phosphoproteomics.

We have successfully developed a bioinertized nanoflow LC/MS/MS (nanoLC/MS/MS) system for the highly sensitive analysis of phosphopeptides by depleting metal ions from the mobile phase. We found that not only direct contact of phosphopeptides with metal components, but also indirect contact with nanoLC pumps through the mobile phase causes significant losses during the recovery of phosphopeptides. Moreover, electrospray ionization was adversely affected by the mobile phase containing multiple metal ions as well as by the sample solvents contaminated with metal ions used in immobilized metal ion affinity chromatography for phosphopeptide enrichment. To solve these problems, metal ions were depleted by inserting an online metal ion removal device containing metal-chelating membranes between the gradient mixer and the autosampler. As a result, the peak areas of the identified phosphopeptides increased an average of 9.9-fold overall and 77-fold for multiply phosphorylated peptides with the insertion of the online metal ion removal system. This strategy would be applicable to the highly sensitive analysis of other phosphorylated biomolecules by microscale-LC/MS/MS.

O-Glycomic and Proteomic Signatures of Spontaneous and Butyrate-Stimulated Colorectal Cancer Cell Line Differentiation.

Gut microbiota of the gastrointestinal tract provide health benefits to the human host via bacterial metabolites. Bacterial butyrate has beneficial effects on intestinal homeostasis and is the preferred energy source of intestinal epithelial cells, capable of inducing differentiation. It was previously observed that changes in the expression of specific proteins as well as protein glycosylation occur with differentiation. In this study, specific mucin O-glycans were identified that mark butyrate-induced epithelial differentiation of the intestinal cell line CaCo-2 (Cancer Coli-2), by applying porous graphitized carbon nano-liquid chromatography with electrospray ionization tandem mass spectrometry. Moreover, a quantitative proteomic approach was used to decipher changes in the cell proteome. It was found that the fully differentiated butyrate-stimulated cells are characterized by a higher expression of sialylated O-glycan structures, whereas fucosylation is downregulated with differentiation. By performing an integrative approach, we generated hypotheses about the origin of the observed O-glycome changes. These insights pave the way for future endeavors to study the dynamic O-glycosylation patterns in the gut, either produced via cellular biosynthesis or through the action of bacterial glycosidases as well as the functional role of these patterns in homeostasis and dysbiosis at the gut-microbiota interface.

Identification of the native Torpedo californica nicotinic acetylcholine receptor's glycan composition after a multi-step sequential purification method using MALDI-ToF MS.

The Cys-loop pentameric ligand-gated ion channels comprise a dynamic group of proteins that have been extensively studied for decades, yielding a wealth of findings at both the structural and functional levels. The nicotinic acetylcholine receptor (nAChR) is no exception, as it is part of this large protein family involved in proper organismal function. Our efforts have successfully produced a highly pure nAChR in detergent complex (nAChR-DC), enabling more robust studies to be conducted on it, including beginning to experiment with high-throughput crystallization. Our homogeneous product has been identified and extensively characterized with 100% identity using Nano Lc MS/MS and MALDI ToF/ToF for each nAChR subunit. Additionally, the N-linked glycans in the Torpedo californica-nAChR (Tc-nAChR) subunits have been identified. To study this, the Tc-nAChR subunits were digested with PNGase F and the released glycans were analyzed by MALDI-ToF. The MS results showed the presence of high-mannose N-glycan in all native Tc-nAChR subunits. Specifically, the oligommanose population Man8-9GlcNac2 with peaks at m/z 1742 and 1904 ([M + Na]+ ions) were observed.

On the excessive use of coefficient of variation as a metric of quantitation quality in proteomics.

The coefficient of variation (CV) is often used in proteomics as a proxy to characterize the performance of a quantitation method and/or the related software. In this note, we question the excessive reliance on this metric in quantitative proteomics that may result in erroneous conclusions. We support this note using a ground-truth Human-Yeast-E. coli dataset demonstrating in a number of cases that erroneous data processing methods may lead to a low CV which has nothing to do with these methods' performances in quantitation.

Global profiling of protein lactylation in Caenorhabditis elegans.

Lactylation, as a novel posttranslational modification, is essential for studying the functions and regulation of proteins in physiological and pathological processes, as well as for gaining in-depth knowledge on the occurrence and development of many diseases, including tumors. However, few studies have examined the protein lactylation of one whole organism. Thus, we studied the lactylation of global proteins in Caenorhabditis elegans to obtain an in vivo lactylome. Using an MS-based platform, we identified 1836 Class I (localization probabilities > 0.75) lactylated sites in 487 proteins. Bioinformatics analysis showed that lactylated proteins were mainly located in the cytoplasm and involved in the tricarboxylic acid cycle (TCA cycle) and other metabolic pathways. Then, we evaluated the conservation of lactylation in different organisms. In total, 41 C. elegans proteins were lactylated and homologous to lactylated proteins in humans and rats. Moreover, lactylation on H4K80 was conserved in three species. An additional 238 lactylated proteins were identified in C. elegans for the first time. This study establishes the first lactylome database in C. elegans and provides a basis for studying the role of lactylation.

Identification of a rare [Gγ(Aγδß)0] -thalassemia using tandem mass spectrometry.

Thalassemias are a group of inherited monogenic disorders characterized by defects in the synthesis of one or more of the globin chain subunits of the hemoglobin tetramer. Delta-beta (δß-) thalassemia has large deletions in the ß globin gene cluster involving δ- and ß-globin genes, leading to absent or reduced synthesis of both δ- and ß-globin chains. Here, we used direct globin-chain analysis using tandem mass spectrometry for the diagnosis of δß-thalassemia. Two cases from unrelated families were recruited for the study based on clinical and hematological evaluation. Peptides obtained after trypsin digestion of proteins extracted from red blood cell pellets from two affected individuals and their parents were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Mass spectrometric analysis revealed a severe reduction in δ, ß, and Aγ globin proteins with increased Gγ globin protein in the affected individuals. The diagnosis of Gγ(Aγδß)0 -thalassemia in the homozygous state in the affected individuals and in the heterozygous state in the parents was made from our results. The diagnosis was confirmed at the genetic level using multiplex ligation-dependent probe amplification (MLPA). Our findings demonstrate the utility of direct globin protein quantitation using LC-MS/MS to quantify individual globin proteins reflecting changes in globin production. This approach can be utilized for accurate and timely diagnosis of hemoglobinopathies, including rare variants, where existing diagnostic methods provide inconclusive results.

Oktoberfest: Open-source spectral library generation and rescoring pipeline based on Prosit.

Machine learning (ML) and deep learning (DL) models for peptide property prediction such as Prosit have enabled the creation of high quality in silico reference libraries. These libraries are used in various applications, ranging from data-independent acquisition (DIA) data analysis to data-driven rescoring of search engine results. Here, we present Oktoberfest, an open source Python package of our spectral library generation and rescoring pipeline originally only available online via ProteomicsDB. Oktoberfest is largely search engine agnostic and provides access to online peptide property predictions, promoting the adoption of state-of-the-art ML/DL models in proteomics analysis pipelines. We demonstrate its ability to reproduce and even improve our results from previously published rescoring analyses on two distinct use cases. Oktoberfest is freely available on GitHub (https://github.com/wilhelm-lab/oktoberfest) and can easily be installed locally through the cross-platform PyPI Python package.

Quantitative proteomics investigating the intrinsic adaptation mechanism of Aeromonas hydrophila to streptomycin.

Aeromonas hydrophila, a prevalent pathogen in the aquaculture industry, poses significant challenges due to its drug-resistant strains. Moreover, residues of antibiotics like streptomycin, extensively employed in aquaculture settings, drive selective bacterial evolution, leading to the progressive development of resistance to this agent. However, the underlying mechanism of its intrinsic adaptation to antibiotics remains elusive. Here, we employed a quantitative proteomics approach to investigate the differences in protein expression between A. hydrophila under streptomycin (SM) stress and nonstress conditions. Notably, bioinformatics analysis unveiled the potential involvement of metal pathways, including metal cluster binding, iron-sulfur cluster binding, and transition metal ion binding, in influencing A. hydrophila's resistance to SM. Furthermore, we evaluated the sensitivity of eight gene deletion strains related to streptomycin and observed the potential roles of petA and AHA_4705 in SM resistance. Collectively, our findings enhance the understanding of A. hydrophila's response behavior to streptomycin stress and shed light on its intrinsic adaptation mechanism.

Dysregulated proteome and N-glycoproteome in ALG1-deficient fibroblasts.

Asparagine-linked glycosylation 1 protein is a ß-1,4-mannosyltransferase, is encoded by the ALG1 gene, which catalyzes the first step of mannosylation in N-glycosylation. Pathogenic variants in ALG1 cause a rare autosomal recessive disorder termed as ALG1-CDG. We performed a quantitative proteomics and N-glycoproteomics study in fibroblasts derived from patients with one homozygous and two compound heterozygous pathogenic variants in ALG1. Several proteins that exhibited significant upregulation included insulin-like growth factor II and pleckstrin, whereas hyaluronan and proteoglycan link protein 1 was downregulated. These proteins are crucial for cell growth, survival and differentiation. Additionally, we observed a decrease in the expression of mitochondrial proteins and an increase in autophagy-related proteins, suggesting mitochondrial and cellular stress. N-glycoproteomics revealed the reduction in high-mannose and complex/hybrid glycopeptides derived from numerous proteins in patients explaining that defect in ALG1 has broad effects on glycosylation. Further, we detected an increase in several short oligosaccharides, including chitobiose (HexNAc2 ) trisaccharides (Hex-HexNAc2 ) and novel tetrasaccharides (NeuAc-Hex-HexNAc2 ) derived from essential proteins including LAMP1, CD44 and integrin. These changes in glycosylation were observed in all patients irrespective of their gene variants. Overall, our findings not only provide novel molecular insights into understanding ALG1-CDG but also offer short oligosaccharide-bearing peptides as potential biomarkers.

Technical challenges in defining RNA modifications.

It is well established that DNA base modifications play a key role in gene regulation during development and in response to environmental stress. This type of epigenetic control of development and environmental responses has been intensively studied over the past few decades. Similar to DNA, various RNA species also undergo modifications that play important roles in, for example, RNA splicing, protein translation, and the avoidance of immune surveillance by host. More than 160 different types of RNA modifications have been identified. In addition to base modifications, RNA modification also involves splicing of pre-mRNAs, leading to as many as tens of transcript isoforms from a single pre-RNA, especially in higher organisms. However, the function, prevalence and distribution of RNA modifications are poorly understood. The lack of a suitable method for the reliable identification of RNA modifications constitutes a significant challenge to studying their functions. This review focuses on the technologies that enable de novo identification of RNA base modifications and the alternatively spliced mRNA transcripts.

Mass Spectrometry-Based Proteomics of Poly(methylmethacrylate)-Embedded Bone.

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a widely employed technique in proteomics research for studying the proteome biology of various clinical samples. Hard tissues, such as bone and teeth, are routinely preserved using synthetic poly(methyl methacrylate) (PMMA) embedding resins that enable histological, immunohistochemical, and morphological examination. However, the suitability of PMMA-embedded hard tissues for large-scale proteomic analysis remained unexplored. This study is the first to report on the feasibility of PMMA-embedded bone samples for LC-MS/MS analysis. Conventional workflows yielded merely limited coverage of the bone proteome. Using advanced strategies of prefractionation by high-pH reversed-phase liquid chromatography in combination with isobaric tandem mass tag labeling resulted in proteome coverage exceeding 1000 protein identifications. The quantitative comparison with cryopreserved samples revealed that each sample preparation workflow had a distinct impact on the proteomic profile. However, workflow replicates exhibited a high reproducibility for PMMA-embedded samples. Our findings further demonstrate that decalcification prior to protein extraction, along with the analysis of solubilization fractions, is not preferred for PMMA-embedded bone. The biological applicability of the proposed workflow was demonstrated using samples of human PMMA-embedded alveolar bone and the iliac crest, which revealed anatomical site-specific proteomic profiles. Overall, these results establish a crucial foundation for large-scale proteomics studies contributing to our knowledge of bone biology.

Discovery of Species-Specific Proteotypic Peptides To Establish a Spectral Library Platform for Identification of Nontuberculosis Mycobacteria from Mass Spectrometry-Based Proteomics.

Nontuberculous mycobacteria are opportunistic bacteria pulmonary and extra-pulmonary infections in humans that closely resemble Mycobacterium tuberculosis. Although genome sequencing strategies helped determine NTMs, a common assay for the detection of coinfection by multiple NTMs with M. tuberculosis in the primary attempt of diagnosis is still elusive. Such a lack of efficiency leads to delayed therapy, an inappropriate choice of drugs, drug resistance, disease complications, morbidity, and mortality. Although a high-resolution LC-MS/MS-based multiprotein panel assay can be developed due to its specificity and sensitivity, it needs a library of species-specific peptides as a platform. Toward this, we performed an analysis of proteomes of 9 NTM species with more than 20 million peptide spectrum matches gathered from 26 proteome data sets. Our metaproteomic analyses determined 48,172 species-specific proteotypic peptides across 9 NTMs. Notably, M. smegmatis (26,008), M. abscessus (12,442), M. vaccae (6487), M. fortuitum (1623), M. avium subsp. paratuberculosis (844), M. avium subsp. hominissuis (580), and M. marinum (112) displayed >100 species-specific proteotypic peptides. Finally, these peptides and corresponding spectra have been compiled into a spectral library, FASTA, and JSON formats for future reference and validation in clinical cohorts by the biomedical community for further translation.

Offline Two-Dimensional Liquid Chromatography-Mass Spectrometry for Deep Annotation of the Fecal Metabolome Following Fecal Microbiota Transplantation.

Biological interpretation of untargeted LC-MS-based metabolomics data depends on accurate compound identification, but current techniques fall short of identifying most features that can be detected. The human fecal metabolome is complex, variable, incompletely annotated, and serves as an ideal matrix to evaluate novel compound identification methods. We devised an experimental strategy for compound annotation using multidimensional chromatography and semiautomated feature alignment and applied these methods to study the fecal metabolome in the context of fecal microbiota transplantation (FMT) for recurrent C. difficile infection. Pooled fecal samples were fractionated using semipreparative liquid chromatography and analyzed by an orthogonal LC-MS/MS method. The resulting spectra were searched against commercial, public, and local spectral libraries, and annotations were vetted using retention time alignment and prediction. Multidimensional chromatography yielded more than a 2-fold improvement in identified compounds compared to conventional LC-MS/MS and successfully identified several rare and previously unreported compounds, including novel fatty-acid conjugated bile acid species. Using an automated software-based feature alignment strategy, most metabolites identified by the new approach could be matched to features that were detected but not identified in single-dimensional LC-MS/MS data. Overall, our approach represents a powerful strategy to enhance compound identification and biological insight from untargeted metabolomics data.

NDUFA12 as a Functional Target of the Anticancer Compound Ertredin in Human Hepatoma Cells As Revealed by Label-Free Chemical Proteomics.

Many attempts have been made to develop new agents that target EGFR mutants or regulate downstream factors in various cancers. Cell-based screening showed that a natural small molecule, Ertredin, inhibited the growth of EGFRvIII mutant cancer cells. Previous studies have shown that Ertredin effectively inhibits anchorage-independent 3D growth of sphere-forming cells transfected with EGFRvIII mutant cDNA. However, the underlying mechanism remains unclear. In this study, we investigated the target protein of Ertredin by combining drug affinity-responsive target stability (DARTS) assays with liquid chromatography-mass spectrometry using label-free Ertredin as a bait and HepG2 cell lysates as a proteome pool. NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 12 (NDUFA12) was identified as an Ertredin-binding protein that was responsible for its biological activity. The interaction between NDUFA12 and Ertredin was validated by DARTS and cellular thermal shift assays. In addition, the genetic knockdown of the identified target, NDUFA12, was shown to suppress cell proliferation. NDUFA12 was identified as a biologically relevant target protein of Ertredin that is responsible for its antitumor activity, and these results provide insights into the role of NDUFA12 as a downstream factor in EGFRvIII mutants.

Delineating Bovine Milk Derived Microvesicles from Exosomes Using Proteomics.

In the work presented herein, a simple serial-pelleting purification strategy combined with a mass spectrometry-based proteomics analysis was developed as a means of discerning differences in extracellular vesicle (EV) populations found in bovine milk samples. A sequence of ultracentrifugation speeds was used to generate changes in the abundances of EV populations, allowing for the identification of associated proteins. A metric was developed to determine the relative abundances of proteins in large EVs (>200 nm) and small EVs (<200 nm). Of the 476 proteins consistently found in this study, 340 are associated with vesicular components. Of these, 156 were heavily enriched in large EVs, 155 shared between large and small EVs, and 29 heavily enriched in small EVs. Additionally, out of 68 proteins annotated as exosome proteins, 32 were enriched in large EVs, 27 shared between large and small EVs, 5 enriched in small EVs, and 7 were found to be nonvesicular contaminant proteins. The top correlated proteins in the small EV group were predominantly membrane-bound proteins, whereas the top correlated proteins in the large EV group were mostly cytosolic enzymes for molecular processing. This method provides a means of assessing the origins of vesicle components and provides new potential marker proteins within discrete vesicle populations.