Microbial Signatures in COVID-19: Distinguishing Mild and Severe Disease via Gut Microbiota.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has significantly impacted global healthcare, underscoring the importance of exploring the virus's effects on infected individuals beyond treatments and vaccines. Notably, recent findings suggest that SARS-CoV-2 can infect the gut, thereby altering the gut microbiota. This study aimed to analyze the gut microbiota composition differences between COVID-19 patients experiencing mild and severe symptoms. We conducted 16S rRNA metagenomic sequencing on fecal samples from 49 mild and 43 severe COVID-19 cases upon hospital admission. Our analysis identified a differential abundance of specific bacterial species associated with the severity of the disease. Severely affected patients showed an association with Enterococcus faecium, Akkermansia muciniphila, and others, while milder cases were linked to Faecalibacterium prausnitzii, Alistipes putredinis, Blautia faecis, and additional species. Furthermore, a network analysis using SPIEC-EASI indicated keystone taxa and highlighted structural differences in bacterial connectivity, with a notable disruption in the severe group. Our study highlights the diverse impacts of SARS-CoV-2 on the gut microbiome among both mild and severe COVID-19 patients, showcasing a spectrum of microbial responses to the virus. Importantly, these findings align, to some extent, with observations from other studies on COVID-19 gut microbiomes, despite variations in methodologies. The findings from this study, based on retrospective data, establish a foundation for future prospective research to confirm the role of the gut microbiome as a predictive biomarker for the severity of COVID-19.

Cross-regulation of antibody responses against the SARS-CoV-2 Spike protein and commensal microbiota via molecular mimicry.

The commensal microflora provides a repertoire of antigens that illicit mucosal antibodies. In some cases, these antibodies can cross-react with host proteins, inducing autoimmunity, or with other microbial antigens. We demonstrate that the oral microbiota can induce salivary anti-SARS-CoV-2 Spike IgG antibodies via molecular mimicry. Anti-Spike IgG antibodies in the saliva correlated with enhanced abundance of Streptococcus salivarius 1 month after anti-SARS-CoV-2 vaccination. Several human commensal bacteria, including S. salivarius, were recognized by SARS-CoV-2-neutralizing monoclonal antibodies and induced cross-reactive anti-Spike antibodies in mice, facilitating SARS-CoV-2 clearance. A specific S. salivarius protein, RSSL-01370, contains regions with homology to the Spike receptor-binding domain, and immunization of mice with RSSL-01370 elicited anti-Spike IgG antibodies in the serum. Additionally, oral S. salivarius supplementation enhanced salivary anti-Spike antibodies in vaccinated individuals. Altogether, these data show that distinct species of the human microbiota can express molecular mimics of SARS-CoV-2 Spike protein, potentially enhancing protective immunity.

Snapper: high-sensitive detection of methylation motifs based on Oxford Nanopore reads.

MOTIVATION: The Oxford Nanopore technology has a great potential for the analysis of methylated motifs in genomes, including whole-genome methylome profiling. However, we found that there are no methylation motifs detection algorithms, which would be sensitive enough and return deterministic results. Thus, the MEME suit does not extract all Helicobacter pylori methylation sites de novo even using the iterative approach implemented in the most up-to-date methylation analysis tool Nanodisco. RESULTS: We present Snapper, a new highly sensitive approach, to extract methylation motif sequences based on a greedy motif selection algorithm. Snapper does not require manual control during the enrichment process and has enrichment sensitivity higher than MEME coupled with Tombo or Nanodisco instruments that was demonstrated on H.pylori strain J99 studied earlier by the PacBio technology and on four external datasets representing different bacterial species. We used Snapper to characterize the total methylome of a new H.pylori strain A45. At least four methylation sites that have not been described for H.pylori earlier were revealed. We experimentally confirmed the presence of a new CCAG-specific methyltransferase and inferred a gene encoding a new CCAAK-specific methyltransferase. AVAILABILITY AND IMPLEMENTATION: Snapper is implemented using Python and is freely available as a pip package named "snapper-ont." Also, Snapper and the demo dataset are available in Zenodo (10.5281/zenodo.10117651).

Role of DNA modifications in Mycoplasma gallisepticum.

The epigenetics of bacteria, and bacteria with a reduced genome in particular, is of great interest, but is still poorly understood. Mycoplasma gallisepticum, a representative of the class Mollicutes, is an excellent model of a minimal cell because of its reduced genome size, lack of a cell wall, and primitive cell organization. In this study we investigated DNA modifications of the model object Mycoplasma gallisepticum and their roles. We identified DNA modifications and methylation motifs in M. gallisepticum S6 at the genome level using single molecule real time (SMRT) sequencing. Only the ANCNNNNCCT methylation motif was found in the M. gallisepticum S6 genome. The studied bacteria have one functional system for DNA modifications, the Type I restriction-modification (RM) system, MgaS6I. We characterized its activity, affinity, protection and epigenetic functions. We demonstrated the protective effects of this RM system. A common epigenetic signal for bacteria is the m6A modification we found, which can cause changes in DNA-protein interactions and affect the cell phenotype. Native methylation sites are underrepresented in promoter regions and located only near the -35 box of the promoter, which does not have a significant effect on gene expression in mycoplasmas. To study the epigenetics effect of m6A for genome-reduced bacteria, we constructed a series of M. gallisepticum strains expressing EGFP under promoters with the methylation motifs in their different elements. We demonstrated that m6A modifications of the promoter located only in the -10-box affected gene expression and downregulated the expression of the corresponding gene.

Deeper insights into transcriptional features of cancer-associated fibroblasts: An integrated meta-analysis of single-cell and bulk RNA-sequencing data.

Cancer-associated fibroblasts (CAFs) have long been known as one of the most important players in tumor initiation and progression. Even so, there is an incomplete understanding of the identification of CAFs among tumor microenvironment cells as the list of CAF marker genes varies greatly in the literature, therefore it is imperative to find a better way to identify reliable markers of CAFs. To this end, we summarized a large number of single-cell RNA-sequencing data of multiple tumor types and corresponding normal tissues. As a result, for 9 different types of cancer, we identified CAF-specific gene expression signatures and found 10 protein markers that showed strongly positive staining of tumor stroma according to the analysis of IHC images from the Human Protein Atlas database. Our results give an insight into selecting the most appropriate combination of cancer-associated fibroblast markers. Furthermore, comparison of different approaches for studying differences between cancer-associated and normal fibroblasts (NFs) illustrates the superiority of transcriptome analysis of fibroblasts obtained from fresh tissue samples. Using single-cell RNA sequencing data, we identified common differences in gene expression patterns between normal and cancer-associated fibroblasts, which do not depend on the type of tumor.

Gene Silencing through CRISPR Interference in Mycoplasmas.

Mycoplasmas are pathogenic, genome-reduced bacteria. The development of such fields of science as system and synthetic biology is closely associated with them. Despite intensive research of different representatives of this genus, genetic manipulations remain challenging in mycoplasmas. Here we demonstrate a single-plasmid transposon-based CRISPRi system for the repression of gene expression in mycoplasmas. We show that selected expression determinants provide a level of dCas9 that does not lead to a significant slow-down of mycoplasma growth. For the first time we describe the proteomic response of genome-reduced bacteria to the expression of exogenous dcas9. The functionality of the resulting vector is confirmed by targeting the three genes coding transcription factors-fur, essential spxA, whiA, and histone-like protein hup1 in Mycoplasma gallisepticum. As a result, the expression level of each gene was decreased tenfold and influenced the mRNA level of predicted targets of transcription factors. To illustrate the versatility of this vector, we performed a knockdown of metabolic genes in a representative member of another cluster of the Mycoplasma genus-Mycoplasma hominis. The developed CRISPRi system is a powerful tool to discover the functioning of genes that are essential, decipher regulatory networks and that can help to identify novel drug targets to control Mycoplasma infections.

UniqPy: A tool for estimation of short-chain fatty acids composition by gas-chromatography/mass-spectrometry with headspace extraction.

Short-chain fatty acids are metabolites widely presented in many natural sources, including human feces and blood. Estimation of their composition is a common procedure, usually performed using nuclear magnetic resonance or gas chromatography with a flame ionization detector. However, the commonly used methods often depend on specific sample preparation, such as filtration and homogenization. The gas-chromatography/mass-spectrometry (GC/MS) method with headspace extraction allows sample preparation to be kept to a minimum regardless of the physical state of the sample, which can be potentially useful in metabolomics research of complex natural samples such as blood or feces. In this work, we have demonstrated the applicability of Headspace GC-MS for estimating short chain fatty acid (SCFA) composition. The main problem here is the complex, non-linear dependence between the composition of the compounds in the source phase and the relative pressures in the vapor phase, which are directly measured by this method. We have implemented a thermodynamic model that performs the reverse transformation of relative abundances in the vapor phase to relative concentrations in the liquid phase, and have tested it on some synthetic SCFA mixtures. The developed method is available as a pip package called UniqPy and can be used to describe liquid-vapor equilibrium for any multicomponent system if a sufficient amount of training data is provided. The gas chromatography method with headspace extraction in conjunction with the UniqPy data transformation showed satisfactory quantification accuracy for propionic acid, butyric acid, isobutyric acid, and valeric acid (R-squared > 0.96). The applicability of the method was additionally demonstrated on a series of fecal samples.

The Dynamics of Mycoplasma gallisepticum Nucleoid Structure at the Exponential and Stationary Growth Phases.

The structure and dynamics of bacterial nucleoids play important roles in regulating gene expression. Bacteria of class Mollicutes and, in particular, mycoplasmas feature extremely reduced genomes. They lack multiple structural proteins of the nucleoid, as well as regulators of gene expression. We studied the organization of Mycoplasma gallisepticum nucleoids in the stationary and exponential growth phases at the structural and protein levels. The growth phase transition results in the structural reorganization of M. gallisepticum nucleoid. In particular, it undergoes condensation and changes in the protein content. The observed changes corroborate with the previously identified global rearrangement of the transcriptional landscape in this bacterium during the growth phase transition. In addition, we identified that the glycolytic enzyme enolase functions as a nucleoid structural protein in this bacterium. It is capable of non-specific DNA binding and can form fibril-like complexes with DNA.

Benchmarking germline CNV calling tools from exome sequencing data.

Whole-exome sequencing is an attractive alternative to microarray analysis because of the low cost and potential ability to detect copy number variations (CNV) of various sizes (from 1-2 exons to several Mb). Previous comparison of the most popular CNV calling tools showed a high portion of false-positive calls. Moreover, due to a lack of a gold standard CNV set, the results are limited and incomparable. Here, we aimed to perform a comprehensive analysis of tools capable of germline CNV calling available at the moment using a single CNV standard and reference sample set. Compiling variants from previous studies with Bayesian estimation approach, we constructed an internal standard for NA12878 sample (pilot National Institute of Standards and Technology Reference Material) including 110,050 CNV or non-CNV exons. The standard was used to evaluate the performance of 16 germline CNV calling tools on the NA12878 sample and 10 correlated exomes as a reference set with respect to length distribution, concordance, and efficiency. Each algorithm had a certain range of detected lengths and showed low concordance with other tools. Most tools are focused on detection of a limited number of CNVs one to seven exons long with a false-positive rate below 50%. EXCAVATOR2, exomeCopy, and FishingCNV focused on detection of a wide range of variations but showed low precision. Upon unified comparison, the tools were not equivalent. The analysis performed allows choosing algorithms or ensembles of algorithms most suitable for a specific goal, e.g. population studies or medical genetics.

ß-N-Methylamino-L-Alanine (BMAA) Causes Severe Stress in Nostoc sp. PCC 7120 Cells under Diazotrophic Conditions: A Proteomic Study.

Non-proteinogenic neurotoxic amino acid ß-N-methylamino-L-alanine (BMAA) is synthesized by cyanobacteria, diatoms, and dinoflagellates, and is known to be a causative agent of human neurodegenerative diseases. Different phytoplankton organisms' ability to synthesize BMAA could indicate the importance of this molecule in the interactions between microalgae in nature. We were interested in the following: what kinds of mechanisms underline BMAA's action on cyanobacterial cells in different nitrogen supply conditions. Herein, we present a proteomic analysis of filamentous cyanobacteria Nostoc sp. PCC 7120 cells that underwent BMAA treatment in diazotrophic conditions. In diazotrophic growth conditions, to survive, cyanobacteria can use only biological nitrogen fixation to obtain nitrogen for life. Note that nitrogen fixation is an energy-consuming process. In total, 1567 different proteins of Nostoc sp. PCC 7120 were identified by using LC-MS/MS spectrometry. Among them, 123 proteins belonging to different functional categories were selected-due to their notable expression differences-for further functional analysis and discussion. The presented proteomic data evidences that BMAA treatment leads to very strong (up to 80%) downregulation of α (NifD) and ß (NifK) subunits of molybdenum-iron protein, which is known to be a part of nitrogenase. This enzyme is responsible for catalyzing nitrogen fixation. The genes nifD and nifK are under transcriptional control of a global nitrogen regulator NtcA. In this study, we have found that BMAA impacts in a total of 22 proteins that are under the control of NtcA. Moreover, BMAA downregulates 18 proteins that belong to photosystems I or II and light-harvesting complexes; BMAA treatment under diazotrophic conditions also downregulates five subunits of ATP synthase and enzyme NAD(P)H-quinone oxidoreductase. Therefore, we can conclude that the disbalance in energy and metabolite amounts leads to severe intracellular stress that induces the upregulation of stress-activated proteins, such as starvation-inducible DNA-binding protein, four SOS-response enzymes, and DNA repair enzymes, nine stress-response enzymes, and four proteases. The presented data provide new leads into the ecological impact of BMAA on microalgal communities that can be used in future investigations.

New Insights into Therapy-Induced Progression of Cancer.

The malignant tumor is a complex heterogeneous set of cells functioning in a no less heterogeneous microenvironment. Like any dynamic system, cancerous tumors evolve and undergo changes in response to external influences, including therapy. Initially, most tumors are susceptible to treatment. However, remaining cancer cells may rapidly reestablish the tumor after a temporary remission. These new populations of malignant cells usually have increased resistance not only to the first-line agent, but also to the second- and third-line drugs, leading to a significant decrease in patient survival. Multiple studies describe the mechanism of acquired therapy resistance. In past decades, it became clear that, in addition to the simple selection of pre-existing resistant clones, therapy induces a highly complicated and tightly regulated molecular response that allows tumors to adapt to current and even subsequent therapeutic interventions. This review summarizes mechanisms of acquired resistance, such as secondary genetic alterations, impaired function of drug transporters, and autophagy. Moreover, we describe less obvious molecular aspects of therapy resistance in cancers, including epithelial-to-mesenchymal transition, cell cycle alterations, and the role of intercellular communication. Understanding these molecular mechanisms will be beneficial in finding novel therapeutic approaches for cancer therapy.

Identification of Clinically Significant Prostate Cancer by Combined PCA3 and AMACR mRNA Detection in Urine Samples.

PURPOSE: Preclinical evaluation of PCA3 and AMACR transcript simultaneous detection in urine to diagnose clinical significant prostate cancer (prostate cancer with Gleason score ≥7) in a Russian cohort. PATIENTS AND METHODS: We analyzed urine samples of patients with a total serum PSA ≥2 ng/mL: 31 men with prostate cancer scheduled for radical prostatectomy, 128 men scheduled for first diagnostic biopsy (prebiopsy cohort). PCA3, AMACR, PSA and GPI transcripts were detected by multiplex reverse transcription quantitative polymerase chain reaction, and the results were used for scores for calculation and statistical analysis. RESULTS: There was no significant difference between clinically significant and nonsignificant prostate cancer PCA3 scores. However, there was a significant difference in the AMACR score (patients scheduled for radical prostatectomy p=0.0088, prebiopsy cohort p=0.029). We estimated AUCs, optimal cutoffs, sensitivities and specificities for PCa and csPCa detection in the prebiopsy cohort by tPSA, PCA3 score, PCPT Risk Calculator and classification models based on tPSA, PCA3 score and AMACR score. In the clinically significant prostate cancer ROC analysis, the PCA3 score AUC was 0.632 (95%CI: 0.511-0.752), the AMACR score AUC was 0.711 (95%CI: 0.617-0.806) and AUC of classification model based on the PCA3 score, the AMACR score and total PSA was 0.72 (95%CI: 0.58-0.83). In addition, the correlation of the AMACR score with the ratio of total RNA and RNA of prostate cells in urine was shown (tau=0.347, p=6.542e-09). Significant amounts of nonprostate RNA in urine may be a limitation for the AMACR score use. CONCLUSION: The AMACR score is a good predictor of clinically significant prostate cancer. Significant amounts of nonprostate RNA in urine may be a limitation for the AMACR score use. Evaluation of the AMACR score and classification models based on it for clinically significant prostate cancer detection with larger samples and a follow-up analysis is promising.

Correction to: Draft genome sequences of Hirudo medicinalis and salivary transcriptome of three closely related medicinal leeches.

An amendment to this paper has been published and can be accessed via the original article.

Proteomic Insights into Starvation of Nitrogen-Replete Cells of Nostoc sp. PCC 7120 under ß-N-Methylamino-L-Alanine (BMAA) Treatment.

All cyanobacteria produce a neurotoxic non-protein amino acid ß-N-methylamino-L-alanine (BMAA). However, the biological function of BMAA in the regulation of cyanobacteria metabolism still remains undetermined. It is known that BMAA suppresses the formation of heterocysts in diazotrophic cyanobacteria under nitrogen starvation conditions, and BMAA induces the formation of heterocyst-like cells under nitrogen excess conditions, by causing the expression of heterocyst-specific genes that are usually "silent" under nitrogen-replete conditions, as if these bacteria receive a nitrogen deficiency intracellular molecular signal. In order to find out the molecular mechanisms underlying this unexpected BMAA effect, we studied the proteome of cyanobacterium Nostoc sp. PCC 7120 grown under BMAA treatment in nitrogen-replete medium. Experiments were performed in two experimental settings: (1) in control samples consisted of cells grown without the BMAA treatment and (2) the treated samples consisted of cells grown with addition of an aqueous solution of BMAA (20 µM). In total, 1567 different proteins of Nostoc sp. PCC 7120 were identified by LC-MS/MS spectrometry. Among them, 80 proteins belonging to different functional categories were chosen for further functional analysis and interpretation of obtained proteomic data. Here, we provide the evidence that a pleiotropic regulatory effect of BMAA on the proteome of cyanobacterium was largely different under conditions of nitrogen-excess compared to its effect under nitrogen starvation conditions (that was studied in our previous work). The most significant difference in proteome expression between the BMAA-treated and untreated samples under different growth conditions was detected in key regulatory protein PII (GlnB). BMAA downregulates protein PII in nitrogen-starved cells and upregulates this protein in nitrogen-replete conditions. PII protein is a key signal transduction protein and the change in its regulation leads to the change of many other regulatory proteins, including different transcriptional factors, enzymes and transporters. Complex changes in key metabolic and regulatory proteins (RbcL, RbcS, Rca, CmpA, GltS, NodM, thioredoxin 1, RpbD, ClpP, MinD, RecA, etc.), detected in this experimental study, could be a reason for the appearance of the "starvation" state in nitrogen-replete conditions in the presence of BMAA. In addition, 15 proteins identified in this study are encoded by genes, which are under the control of NtcA-a global transcriptional regulator-one of the main protein partners and transcriptional regulators of PII protein. Thereby, this proteomic study gives a possible explanation of cyanobacterium starvation under nitrogen-replete conditions and BMAA treatment. It allows to take a closer look at the regulation of cyanobacteria metabolism affected by this cyanotoxin.

The First Proteomics Study of Nostoc sp. PCC 7120 Exposed to Cyanotoxin BMAA under Nitrogen Starvation.

The oldest prokaryotic photoautotrophic organisms, cyanobacteria, produce many different metabolites. Among them is the water-soluble neurotoxic non-protein amino acid beta-N-methylamino-L-alanine (BMAA), whose biological functions in cyanobacterial metabolism are of fundamental scientific and practical interest. An early BMAA inhibitory effect on nitrogen fixation and heterocyst differentiation was shown in strains of diazotrophic cyanobacteria Nostoc sp. PCC 7120, Nostocpunctiforme PCC 73102 (ATCC 29133), and Nostoc sp. strain 8963 under conditions of nitrogen starvation. Herein, we present a comprehensive proteomic study of Nostoc (also called Anabaena) sp. PCC 7120 in the heterocyst formation stage affecting by BMAA treatment under nitrogen starvation conditions. BMAA disturbs proteins involved in nitrogen and carbon metabolic pathways, which are tightly co-regulated in cyanobacteria cells. The presented evidence shows that exogenous BMAA affects a key nitrogen regulatory protein, PII (GlnB), and some of its protein partners, as well as glutamyl-tRNA synthetase gltX and other proteins that are involved in protein synthesis, heterocyst differentiation, and nitrogen metabolism. By taking into account the important regulatory role of PII, it becomes clear that BMAA has a severe negative impact on the carbon and nitrogen metabolism of starving Nostoc sp. PCC 7120 cells. BMAA disturbs carbon fixation and the carbon dioxide concentrating mechanism, photosynthesis, and amino acid metabolism. Stress response proteins and DNA repair enzymes are upregulated in the presence of BMAA, clearly indicating severe intracellular stress. This is the first proteomic study of the effects of BMAA on diazotrophic starving cyanobacteria cells, allowing a deeper insight into the regulation of the intracellular metabolism of cyanobacteria by this non-protein amino acid.

Draft genome sequences of Hirudo medicinalis and salivary transcriptome of three closely related medicinal leeches.

BACKGROUND: Salivary cell secretion (SCS) plays a critical role in blood feeding by medicinal leeches, making them of use for certain medical purposes even today. RESULTS: We annotated the Hirudo medicinalis genome and performed RNA-seq on salivary cells isolated from three closely related leech species, H. medicinalis, Hirudo orientalis, and Hirudo verbana. Differential expression analysis verified by proteomics identified salivary cell-specific gene expression, many of which encode previously unknown salivary components. However, the genes encoding known anticoagulants have been found to be expressed not only in salivary cells. The function-related analysis of the unique salivary cell genes enabled an update of the concept of interactions between salivary proteins and components of haemostasis. CONCLUSIONS: Here we report a genome draft of Hirudo medicinalis and describe identification of novel salivary proteins and new homologs of genes encoding known anticoagulants in transcriptomes of three medicinal leech species. Our data provide new insights in genetics of blood-feeding lifestyle in leeches.

Phigaro: high-throughput prophage sequence annotation.

SUMMARY: Phigaro is a standalone command-line application that is able to detect prophage regions taking raw genome and metagenome assemblies as an input. It also produces dynamic annotated 'prophage genome maps' and marks possible transposon insertion spots inside prophages. It is applicable for mining prophage regions from large metagenomic datasets. AVAILABILITY AND IMPLEMENTATION: Source code for Phigaro is freely available for download at https://github.com/bobeobibo/phigaro along with test data. The code is written in Python. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Comprehensive Functional Analysis of Escherichia coli Ribosomal RNA Methyltransferases.

Ribosomal RNAs in all organisms are methylated. The functional role of the majority of modified nucleotides is unknown. We systematically questioned the influence of rRNA methylation in Escherichia coli on a number of characteristics of bacterial cells with the help of a set of rRNA methyltransferase (MT) gene knockout strains from the Keio collection. Analysis of ribosomal subunits sedimentation profiles of the knockout strains revealed a surprisingly small number of rRNA MT that significantly affected ribosome assembly. Accumulation of the assembly intermediates was observed only for the rlmE knockout strain whose growth was retarded most significantly among other rRNA MT knockout strains. Accumulation of the 17S rRNA precursor was observed for rsmA(ksgA) knockout cells as well as for cells devoid of functional rsmB and rlmC genes. Significant differences were found among the WT and the majority of rRNA MT knockout strains in their ability to sustain exogenous protein overexpression. While the majority of the rRNA MT knockout strains supported suboptimal reporter gene expression, the strain devoid of the rsmF gene demonstrated a moderate increase in the yield of ectopic gene expression. Comparative 2D protein gel analysis of rRNA MT knockout strains revealed only minor perturbations of the proteome.

Identification of Antimicrobial Peptides from Novel Lactobacillus fermentum Strain.

Antimicrobial peptides (AMPs) are natural antagonistic tools of many bacteria and are considered as attractive antimicrobial agents for the treatment of bacteria with multidrug resistance. Lactic acid bacteria from the gastrointestinal tract of animals and human produce various AMPs inhibiting the growth of pathogens. Here we report the isolation and identification of novel Lactobacillus fermentum strain HF-D1 from the human gut producing AMPs which prevents the growth of P. aeruginosa and S. marcescens. The active fraction of peptides was obtained from the culture liquid by precipitation at 80% saturation of ammonium sulphate. For peptides identification, the precipitate was treated with guanidine hydrochloride to desorb from proteins, separated with ultrafiltration on spin columns with 10,000 MWCO, desalted with a reversed-phase chromatography and subjected to LC-MS/MS analysis. The in silico analysis of the identified 1111 peptides by using ADAM, CAMPR3 and AMPA prediction servers led to identification of the linear peptide with highly probable antimicrobial activity and further investigation of its antibacterial activity mechanism is promising. By using the dereplication algorithm, the peptide highly similar to non-ribosomal cyclic AMPs originally isolated from Staphylococcus epidermidis has been identified. This indicates that L. fermentum HF-D1 represents a novel strain producing antimicrobial peptides targeting P. aeruginosa and S. marcescens.

Challenges of the Human Proteome Project: 10-Year Experience of the Russian Consortium.

This manuscript collects all the efforts of the Russian Consortium, bottlenecks revealed in the course of the C-HPP realization, and ways of their overcoming. One of the main bottlenecks in the C-HPP is the insufficient sensitivity of proteomic technologies, hampering the detection of low- and ultralow-copy number proteins forming the "dark part" of the human proteome. In the frame of MP-Challenge, to increase proteome coverage we suggest an experimental workflow based on a combination of shotgun technology and selected reaction monitoring with two-dimensional alkaline fractionation. Further, to detect proteins that cannot be identified by such technologies, nanotechnologies such as combined atomic force microscopy with molecular fishing and/or nanowire detection may be useful. These technologies provide a powerful tool for single molecule analysis, by analogy with nanopore sequencing during genome analysis. To systematically analyze the functional features of some proteins (CP50 Challenge), we created a mathematical model that predicts the number of proteins differing in amino acid sequence: proteoforms. According to our data, we should expect about 100 000 different proteoforms in the liver tissue and a little more in the HepG2 cell line. The variety of proteins forming the whole human proteome significantly exceeds these results due to post-translational modifications (PTMs). As PTMs determine the functional specificity of the protein, we propose using a combination of gene-centric transcriptome-proteomic analysis with preliminary fractionation by two-dimensional electrophoresis to identify chemically modified proteoforms. Despite the complexity of the proposed solutions, such integrative approaches could be fruitful for MP50 and CP50 Challenges in the framework of the C-HPP.