Proteomic Applications in Antimicrobial Resistance and Clinical Microbiology Studies

ProkDBP: Toward more precise identification of prokaryotic DNA binding proteins

Prokaryotic DNA binding proteins (DBPs) play pivotal roles in governing gene regulation, DNA replication, and various cellular functions. Accurate computational models for predicting prokaryotic DBPs hold immense promise in accelerating the discovery of novel proteins, fostering a deeper understanding of prokaryotic biology, and facilitating the development of therapeutics targeting for potential disease interventions. However, existing generic prediction models often exhibit lower accuracy in predicting prokaryotic DBPs. To address this gap, we introduce ProkDBP, a novel machine learning-driven computational model for prediction of prokaryotic DBPs. For prediction, a total of nine shallow learning algorithms and five deep learning models were utilized, with the shallow learning models demonstrating higher performance metrics compared to their deep learning counterparts. The light gradient boosting machine (LGBM), coupled with evolutionarily significant features selected via random forest variable importance measure (RF-VIM) yielded the highest five-fold cross-validation accuracy. The model achieved the highest auROC (0.9534) and auPRC (0.9575) among the 14 machine learning models evaluated. Additionally, ProkDBP demonstrated substantial performance with an independent dataset, exhibiting higher values of auROC (0.9332) and auPRC (0.9371). Notably, when benchmarked against several cutting-edge existing models, ProkDBP showcased superior predictive accuracy. Furthermore, to promote accessibility and usability, ProkDBP (https://iasri-sg.icar.gov.in/prokdbp/) is available as an online prediction tool, enabling free access to interested users. This tool stands as a significant contribution, enhancing the repertoire of resources for accurate and efficient prediction of prokaryotic DBPs.

Uncovering virulence factors in Cronobacter sakazakii: insights from genetic screening and proteomic profiling

The increasing problem of antibiotic resistance has driven the search for virulence factors in pathogenic bacteria, which can serve as targets for the development of new antibiotics. Although whole-genome Tn5 transposon mutagenesis combined with phenotypic assays has been a widely used approach, its efficiency remains low due to labor-intensive processes. In this study, we aimed to identify specific genes and proteins associated with the virulence of Cronobacter sakazakii, a pathogenic bacterium known for causing severe infections, particularly in infants and immunocompromised individuals. By employing a combination of genetic screening, comparative proteomics, and in vivo validation using zebrafish and rat models, we rapidly screened highly virulent strains and identified two genes, rcsA and treR, as potential regulators of C. sakazakii toxicity toward zebrafish and rats. Proteomic profiling revealed upregulated proteins upon knockout of rcsA and treR, including FabH, GshA, GppA, GcvH, IhfB, RfaC, MsyB, and three unknown proteins. Knockout of their genes significantly weakened bacterial virulence, confirming their role as potential virulence factors. Our findings contribute to understanding the pathogenicity of C. sakazakii and provide insights into the development of targeted interventions and therapies against this bacterium.IMPORTANCEThe emergence of antibiotic resistance in pathogenic bacteria has become a critical global health concern, necessitating the identification of virulence factors as potential targets for the development of new antibiotics. This study addresses the limitations of conventional approaches by employing a combination of genetic screening, comparative proteomics, and in vivo validation to rapidly identify specific genes and proteins associated with the virulence of Cronobacter sakazakii, a highly pathogenic bacterium responsible for severe infections in vulnerable populations. The identification of two genes, rcsA and treR, as potential regulators of C. sakazakii toxicity toward zebrafish and rats and the proteomic profiling upon knockout of rcsA and treR provides novel insights into the mechanisms underlying bacterial virulence. The findings contribute to our understanding of C. sakazakii's pathogenicity, shed light on the regulatory pathways involved in bacterial virulence, and offer potential targets for the development of novel interventions against this highly virulent bacterium.

Mass spectrometry-based proteomics as an emerging tool in clinical laboratories

Mass spectrometry (MS)-based proteomics have been increasingly implemented in various disciplines of laboratory medicine to identify and quantify biomolecules in a variety of biological specimens. MS-based proteomics is continuously expanding and widely applied in biomarker discovery for early detection, prognosis and markers for treatment response prediction and monitoring. Furthermore, making these advanced tests more accessible and affordable will have the greatest healthcare benefit.This review article highlights the new paradigms MS-based clinical proteomics has created in microbiology laboratories, cancer research and diagnosis of metabolic disorders. The technique is preferred over conventional methods in disease detection and therapy monitoring for its combined advantages in multiplexing capacity, remarkable analytical specificity and sensitivity and low turnaround time.Despite the achievements in the development and adoption of a number of MS-based clinical proteomics practices, more are expected to undergo transition from bench to bedside in the near future. The review provides insights from early trials and recent progresses (mainly covering literature from the NCBI database) in the application of proteomics in clinical laboratories.

A novel strategy to characterize the pattern of β-lactam antibiotic-induced drug resistance in Acinetobacter baumannii

Carbapenem-resistant Acinetobacter baumannii (CRAb) is an urgent public health threat, according to the CDC. This pathogen has few treatment options and causes severe nosocomial infections with > 50% fatality rate. Although previous studies have examined the proteome of CRAb, there have been no focused analyses of dynamic changes to β-lactamase expression that may occur due to drug exposure. Here, we present our initial proteomic study of variation in β-lactamase expression that occurs in CRAb with different β-lactam antibiotics. Briefly, drug resistance to Ab (ATCC 19606) was induced by the administration of various classes of β-lactam antibiotics, and the cell-free supernatant was isolated, concentrated, separated by SDS-PAGE, digested with trypsin, and identified by label-free LC-MS-based quantitative proteomics. Thirteen proteins were identified and evaluated using a 1789 sequence database of Ab β-lactamases from UniProt, the majority of which were Class C β-lactamases (≥ 80%). Importantly, different antibiotics, even those of the same class (e.g. penicillin and amoxicillin), induced non-equivalent responses comprising various isoforms of Class C and D serine-β-lactamases, resulting in unique resistomes. These results open the door to a new approach of analyzing and studying the problem of multi-drug resistance in bacteria that rely strongly on β-lactamase expression.

Comparative proteome profiling of fusarium chlamydosporum and elucidation of pigment biosynthetic pathway under nitrogen stress

The main aim of this study was to understand the protein expression of F. chlamydosporum in two different medium composition in varying concentrations of nitrogen. The interesting phenomenon of producing diverse pigments by a single strain in different concentrations of Nitrogen made us further to explore the difference in the protein expression of the fungus when grown in these two media. For this, we had adopted non-gel-based method of protein separation by LC-MS/MS analysis followed by label free identification of proteins by SWATH analysis. The molecular and biological functions of each protein and their Gene Ontology annotations were analyzed by UniProt KB and KEGG pathway; the secondary metabolite pathways and the carbohydrate metabolic pathways were analyzed by DAVID bioinformatics tool. The positively regulated proteins biologically functioned for the secondary metabolite production in optimized medium were Diphosphomevalonate decarboxylase (terpenoid backbone biosynthesis), Phytoene synthase (carotenoid biosynthesis), 6,7-dimethyl-8-ribityllumazine synthase (riboflavin biosynthesis). The main characteristic change observed was that proteins related to carotenoid biosynthesis and terpenoid synthesis were not regulated in nitrogen limited medium. Except for the protein 6,7-dimethyl-8-ribityllumazine synthase, all the enzymes related to fatty acid biosynthesis and polyketide chain elongation were up regulated. Apart from the proteins related to secondary metabolite production, two novel proteins were found to be up regulated in Nitrogen Limited Medium; C-fem protein responsible for fungal pathogenesis and DAO domain containing protein which functions as a neuromodulator and catalyzes the synthesis of dopamine. SIGNIFICANCE: This particular strain of F. chlamydosporum of immense genetic and biochemical diversity represents an interesting example of a microorganism which can produce a variety of bioactive compounds and this can be exploited in various industries. The production of carotenoids and polyketides by this fungus when grown in the same media with different concentrations of Nitrogen has been published by us following which we analyzed the proteome sequence of the fungus in varying Nutrient conditions. Following the proteome analysis and expression, we could derive the pathway leading to the biosynthesis of varying secondary metabolites by the fungus which has not been published or studied so far.

Metagenomic-based surveillance systems for antibiotic resistance in non-clinical settings

The success of antibiotics as a therapeutic agent has led to their ineffectiveness. The continuous use and misuse in clinical and non-clinical areas have led to the emergence and spread of antibiotic-resistant bacteria and its genetic determinants. This is a multi-dimensional problem that has now become a global health crisis. Antibiotic resistance research has primarily focused on the clinical healthcare sectors while overlooking the non-clinical sectors. The increasing antibiotic usage in the environment - including animals, plants, soil, and water - are drivers of antibiotic resistance and function as a transmission route for antibiotic resistant pathogens and is a source for resistance genes. These natural compartments are interconnected with each other and humans, allowing the spread of antibiotic resistance via horizontal gene transfer between commensal and pathogenic bacteria. Identifying and understanding genetic exchange within and between natural compartments can provide insight into the transmission, dissemination, and emergence mechanisms. The development of high-throughput DNA sequencing technologies has made antibiotic resistance research more accessible and feasible. In particular, the combination of metagenomics and powerful bioinformatic tools and platforms have facilitated the identification of microbial communities and has allowed access to genomic data by bypassing the need for isolating and culturing microorganisms. This review aimed to reflect on the different sequencing techniques, metagenomic approaches, and bioinformatics tools and pipelines with their respective advantages and limitations for antibiotic resistance research. These approaches can provide insight into resistance mechanisms, the microbial population, emerging pathogens, resistance genes, and their dissemination. This information can influence policies, develop preventative measures and alleviate the burden caused by antibiotic resistance.

Antimicrobial impacts of zinc oxide nanoparticles on shiga toxin-producing Escherichia coli (serotype O26)

The antibacterial activity of zinc oxide nanoparticles (ZnO NPs) has received significant attention worldwide due to the emergence of multidrug-resistant microorganisms. Shiga toxin-producing Escherichia coli is a major foodborne pathogen that causes gastroenteritis that may be complicated by hemorrhagic colitis or hemolytic uremic syndrome. Therefore, this study aimed to evaluate the antimicrobial effect of ZnO NPs against E. coli O26 and its Shiga toxin type 2 (Stx2). Multidrug resistance phenotype was observed in E. coli O26, with co-resistance to several unrelated families of antimicrobial agents. Different concentrations of ZnO NPs nanoparticles (20 nm) were tested against different cell densities of E. coli O26 (108, 106 and 105 CFU/ml). The minimum inhibitory concentration (MIC) value was 1 mg/ml. Minimum bactericidal concentration (MBC) was 1.5 mg/ml, 2.5 mg/ml and 3 mg/ml, respectively, depending on ZnO NPs concentrations and bacterial cell density. Results showed a significant (P≤0.05) decrease in Stx2 level in a response to ZnO NPs treatment. As detected by quantitative real-time PCR, ZnO NPs down-regulated the expression of the Stx2 gene (P≤0.05). Moreover, various concentrations of ZnO NPs considerably reduced the total protein content in E. coli O26. There was a significant reduction in protein expression with increased ZnO NPs concentration compared to the non-treated control. Scanning electron micrographs (SEM) of the treated bacteria showed severe disruptive effects on E. coli O26 with increasing ZnO NPs concentration. The results revealed a strong correlation between the antibacterial effect and ZnO NPs concentrations. ZnO NPs exert their antibacterial activities through various mechanisms and could be used as a potent antibacterial agent against E. coli O26.

Next Generation and Other Sequencing Technologies in Diagnostic Microbiology and Infectious Diseases

Next-generation sequencing (NGS) technologies have become increasingly available for use in the clinical microbiology diagnostic environment. There are three main applications of these technologies in the clinical microbiology laboratory: whole genome sequencing (WGS), targeted metagenomics sequencing and shotgun metagenomics sequencing. These applications are being utilized for initial identification of pathogenic organisms, the detection of antimicrobial resistance mechanisms and for epidemiologic tracking of organisms within and outside hospital systems. In this review, we analyze these three applications and provide a comprehensive summary of how these applications are currently being used in public health, basic research, and clinical microbiology laboratory environments. In the public health arena, WGS is being used to identify and epidemiologically track food borne outbreaks and disease surveillance. In clinical hospital systems, WGS is used to identify multi-drug-resistant nosocomial infections and track the transmission of these organisms. In addition, we examine how metagenomics sequencing approaches (targeted and shotgun) are being used to circumvent the traditional and biased microbiology culture methods to identify potential pathogens directly from specimens. We also expand on the important factors to consider when implementing these technologies, and what is possible for these technologies in infectious disease diagnosis in the next 5 years.

Phenotypic screening of compound libraries as a platform for the identification of antibiotic adjuvants: Identification of colistin adjuvants from a natural product library

The identification of antibiotic adjuvants, small molecules that potentiate the activity of conventional antibiotics, provides an orthogonal approach to the development of new antibiotics in the fight against drug resistant bacterial infections. Methods to identify novel adjuvants could potentially aid efforts to overcome the increasing prevalence of resistance and stave off the onset of a "post-antibiotic era." Phenotypic whole cell screens allow for the identification of hits with the necessary properties to access their biomolecular target, and may also facilitate the discovery of novel adjuvant targets. A phenotypic screening platform is outlined, in which a natural product library was explored for activity with antibiotics from several mechanistically distinct classes against clinically important bacterial species. General approaches to delineating the mechanism of action of hit compounds identified from phenotypic screens are described, followed by specific approaches to uncovering the mechanism of action of the colistin adjuvants identified from the natural product screen.

Comparative Analysis of Serum Proteins Between Hepatitis B Virus Genotypes B and C Infection by DIA-Based Quantitative Proteomics

Purpose

In clinical practice, the clinicopathological profiles and outcomes of patients infected with hepatitis B virus (HBV) are different between genotypes B and C. However, little is known about the potential mechanism and differences in specific biological pathways associated with the different genotype. This study aimed to compare the serum protein profile between patients infected with HBV genotype B and those infected with HBV genotype C.

Patients and Methods

A total of 54 serum samples from patients with chronic HBV genotype B infection and those with chronic HBV genotype C infection, and healthy controls were used for the proteomic analysis (n = 18 samples in per group). Serum proteomic profiles were analyzed using data-independent acquisition (DIA)-based liquid chromatography-mass spectrometry to identify differentially expressed proteins (up- or downregulation of at least 1.5-fold) between serum samples from HBV patients infected with HBV genotype B and those infected with genotype C.

Results

We identified 1010 proteins, 53 of which were differentially expressed between the serum samples of the healthy controls and those of HBV genotype B infected patients, and 59 that were differentially expressed between the samples of the healthy controls and those of HBV genotype C infected patients. Furthermore, our results indicated that two proteins identified as being differentially expressed (VWF and C8B) have potential as biomarkers for distinguishing genotype B infected HBV patients from those infected with genotype C.

Conclusion

The results of our DIA-based quantitative proteomic analysis revealed that HBV genotypes B and C are associated with different molecular profiles and may provide fundamental information for further detailed investigations of the molecular mechanism underlying these differences.

Combating Childhood Infections in LMICs: evaluating the contribution of Big Data Big data, biomarkers and proteomics: informing childhood diarrhoeal disease management in Low- and Middle-Income Countries

Despite efforts to reduce the global burden of childhood diarrhoea, 50% of all cases globally occur in children under five years in Low–Income and Middle- Income Countries (LMICs) and knowledge gaps remain regarding the aetiological diagnosis, introduction of diarrhoeal vaccines, and the role of environmental enteric dysfunction and severe acute malnutrition. Biomarkers may assist in understanding disease processes, from diagnostics, to management of childhood diarrhoea and the sequelae to vaccine development. Proteomics has the potential to assist in the identification of new biomarkers to understand the processes in the development of childhood diarrhoea and to aid in developing new vaccines. Centralised repositories that enable mining of large data sets to better characterise risk factors, the proteome of both the patient and the different diarrhoeal pathogens, and the environment, could inform patient management and vaccine development, providing a systems biological approach to address the burden of childhood diarrhoea in LMICs.

Bacterial proteomics and its application for pathogenesis studies

Bacteria build their structures by implementing several macromolecules such as proteins, polysaccharides, phospholipids, and nucleic acids, which leads to preserve their lives and play an essential role in their pathogenesis. There are two genomic and proteomic methods to study various macromolecules of bacteria, which are complementary methods and provide comprehensive information. Proteomic approaches are used to identify proteins and their cell applications. Furthermore, to study bacterial proteins, macromolecules are involved in the bacteria's structures and functions. These protein-based methods provide comprehensive information about the cells, such as the external structures, internal compositions, post-translational modifications, and mechanisms of particular actions such as biofilm formation, antibiotic resistance, and adaptation to the environment, which are helpful in promoting bacterial pathogenesis. These methods use various devices such as MALDI-TOF MS, LC-MS, and two-dimensional electrophoresis, which are valuable tools for studying different structural and functional proteins of the bacteria and their mechanisms of pathogenesis that causes rapid, easy, and accurate diagnosis of the infections.

Induction of proteome changes involved in biofilm formation of Enterococcus faecalis in response to gentamicin

BACKGROUND

Enterococcus faecalis is a significant cause of nosocomial infections and other diseases, including endocarditis, bacteremia, and urinary tract infections. This microorganism forms biofilms to overcome difficult environmental conditions, such as lack of oxygen, lack of water, and the presence of antimicrobials. These biofilms make diseases difficult by changing their proteome contents, protecting the bacterium, and increasing their pathogenicity. This study aimed to evaluate gentamicin's effect on proteome changes and biofilm formation in E. faecalis.

METHOD

Twenty-five clinical isolates and one standard isolate were selected for the experiments. A label-free/gel-free proteomic and microtiter plate techniques were used to study proteome changes and biofilm formation, respectively.

RESULTS

Gentamicin significantly increased the biofilm formation in 62% of isolates and the rest of the isolates; no significant change was observed. The abundance of lactate utilization protein C, ribosomal RNA small subunit methyltransferase H, and protein translocase subunit SecA were increased. However, the abundances of proteins effective in cell division and metabolism, such as replication initiation protein and segregation and condensation protein A, were decreased.

CONCLUSION

The present study's findings exhibited that antibiotics might have adverse effects on treatment and increase microorganisms' pathogenicity. It was observed in gentamicin as induction of biofilm formation through different mechanisms, particularly changes in the expression of specific proteins in E. faecalis.

FBPAII and rpoBC, the Two Novel Secreted Proteins Identified by the Proteomic Approach from a Comparative Study between Antibiotic-Sensitive and Antibiotic-Resistant Helicobacter pylori-Associated Gastritis Strains

Helicobacter pylori infection is the leading cause of chronic gastritis, which can develop into gastric cancer. Eliminating H. pylori infection with antibiotics achieves the prevention of gastric cancer. Currently, the prevalence of H. pylori resistance to clarithromycin and metronidazole, and the dual resistance to metronidazole and clarithromycin (C_R, M_R, and C/M_R, respectively), remains at a high level worldwide. As a means of exploring new candidate proteins for the management of H. pylori infection, secreted proteins from antibiotic-susceptible and antibiotic-resistant H. pylori-associated gastritis strains were obtained by in-solution tryptic digestion coupled with nano-liquid chromatography tandem mass spectrometry (nano-LC-MS/MS). A total of 583, 582, 590, and 578 differential expressed proteins were identified from C_R, M_R, C/M_R, and antibiotic-sensitive strain (S_S) samples, respectively. Of these, 23 overlapping proteins were found by Venn diagram analysis. Based on heat map analyses, the most and least differing protein expressions were observed from C/M_R strains and S_S strains, respectively. Of the proteins secreted by the S_S strain, only nine were found. After predicting the protein interaction with metronidazole and clarithromycin via the STITCH database, the two most interesting proteins were found to be rpoBC and FBPAII. After quantitative real-time reverse transcription PCR (qRT-PCR) analysis, a downregulation of rpoB from M_R strains was observed, suggesting a relationship of rpoB to metronidazole sensitivity. Inversely, an upregulation of fba from C_R, M_R, and C/M_R strains was noticed, suggesting the paradoxical expression of FBPAII and the fba gene. This report is the first to demonstrate the association of these two novel secreted proteins, namely, rpoBC and FBPAII, with antibiotic-sensitive H. pylori -associated gastritis strains.

MALDI-TOF Mass Spectroscopy Applications in Clinical Microbiology

There is a range of proteomics methods to spot and analyze bacterial protein contents such as liquid chromatography-mass spectrometry (LC-MS), two-dimensional gel electrophoresis, and matrix-assisted laser desorption/ionization mass spectrometry (MALDI-TOF MS), which give comprehensive information about the microorganisms that may be helpful within the diagnosis and coverings of infections. Microorganism identification by mass spectrometry is predicted on identifying a characteristic spectrum of every species so matched with an outsized database within the instrument. MALDI-TOF MS is one of the diagnostic methods, which is a straightforward, quick, and precise technique, and is employed in microbial diagnostic laboratories these days and may replace other diagnostic methods. This method identifies various microorganisms such as bacteria, fungi, parasites, and viruses, which supply comprehensive information. One of the MALDI-TOF MS's crucial applications is bacteriology, which helps identify bacterial species, identify toxins, and study bacterial antibiotic resistance. By knowing these cases, we will act more effectively against bacterial infections.