Identification of staphylococcal species based on variations in protein sequences (mass spectrometry) and DNA sequence (sodA microarray)

Integration of transcriptomics, proteomics and metabolomics data to reveal the biological mechanisms of abrin injury in human lung epithelial cells

BACKGROUND

Abrin toxin (AT) is a potent plant toxin that belongs to the type Ⅱ ribosome inactivating protein family and is recognized as an important toxin agent for potential bioweapons. Exposure to AT by way of aerosol is the most lethal route, but the mechanism of injury requires further investigation.

MATERIALS AND METHODS

In the present study, we performed a comprehensive analysis of transcriptomics, proteomics and metabolomics on the potential mechanism of abrin injury in human lung epithelial cells.

RESULTS

In total, 6838 genes, 314 proteins and 178 metabolites showed significant changes in human lung epithelial cells after AT treatment. Using molecular function, pathway, and network analysis, the genes and proteins regulated in AT-treated cells were mainly attributed to amino acid metabolism, lipid metabolism, and genetic information processing. Furthermore, a comprehensive analysis of the transcripts, proteins, and metabolites was performed. The results revealed that the correlated genes, proteins, and metabolism pathways regulated in AT-treated human lung epithelial cells were involved in tryptophan metabolism, biosynthesis of amino acids, and protein digestion and absorption.

CONCLUSION

This study provides large-scale omics data to develop new strategies for the prevention, rapid diagnosis, and treatment of AT poisoning, especially AT from aerosol.

Improved multiplex PCR primers for rapid identification of coagulase-negative staphylococci

Coagulase-negative staphylococci (CNS) are opportunistic pathogens that are currently emerging as causative agents of human disease. Though CNS are widespread in the clinic and food, their precise identification at species level is important. Here, using 16S rRNA sequencing, 55 staphylococcal isolates were identified as S. capitis, S. caprae, S. epidermidis, S. haemolyticus, S. pasteuri, S. saprophyticus, S. warneri, and S. xylosus. Although 16S rRNA sequencing is universally accepted as a standard for bacterial identification, the method did not effectively discriminate closely related species, and additional DNA sequencing was required. The divergence of the sodA gene sequence is higher than that of 16S rRNA. To devise a rapid and accurate identification method, sodA-specific primers were designed to demonstrate that species-specific multiplex polymerase chain reaction (PCR) can be used for the identification of CNS species. The accuracy of this method was higher than that of phenotypic identification; the method is simple and less time-consuming than 16S rRNA sequencing. Of the 55 CNS isolates, 92.72% were resistant to at least one antibiotic, and 60% were resistant to three or more antibiotics. CNS isolates produced diverse virulence-associated enzymes, including hemolysin (produced by 69.09% of the isolates), protease (65.45%), lipase (54.54%), lecithinase (36.36%), and DNase (29.09%); all isolates could form a biofilm. Because of the increasing pathogenic significance of CNS, the efficient multiplex PCR detection method developed in this study may contribute to studies for human health.

Personalized Proteomics: The Future of Precision Medicine

Medical diagnostics and treatment has advanced from a one size fits all science to treatment of the patient as a unique individual. Currently, this is limited solely to genetic analysis. However, epigenetic, transcriptional, proteomic, posttranslational modifications, metabolic, and environmental factors influence a patient’s response to disease and treatment. As more analytical and diagnostic techniques are incorporated into medical practice, the personalized medicine initiative transitions to precision medicine giving a holistic view of the patient’s condition. The high accuracy and sensitivity of mass spectrometric analysis of proteomes is well suited for the incorporation of proteomics into precision medicine. This review begins with an overview of the advance to precision medicine and the current state of the art in technology and instrumentation for mass spectrometry analysis. Thereafter, it focuses on the benefits and potential uses for personalized proteomic analysis in the diagnostic and treatment of individual patients. In conclusion, it calls for a synthesis between basic science and clinical researchers with practicing clinicians to design proteomic studies to generate meaningful and applicable translational medicine. As clinical proteomics is just beginning to come out of its infancy, this overview is provided for the new initiate.

Recent development of mass spectrometry and proteomics applications in identification and typing of bacteria

Identification and typing of bacteria occupy a large fraction of time and work in clinical microbiology laboratories. With the certification of some MS platforms in recent years, more applications and tests of MS‐based diagnosis methods for bacteria identification and typing have been created, not only on well‐accepted MALDI‐TOF‐MS‐based fingerprint matches, but also on solving the insufficiencies of MALDI‐TOF‐MS‐based platforms and advancing the technology to areas such as targeted MS identification and typing of bacteria, bacterial toxin identification, antibiotics susceptibility/resistance tests, and MS‐based diagnostic method development on unique bacteria such as Clostridium and Mycobacteria. This review summarizes the recent development in MS platforms and applications in bacteria identification and typing of common pathogenic bacteria.

Staphylococcus epidermidis as a cause of bacteremia

Staphylococcus epidermidis is a biofilm-producing commensal organism found ubiquitously on human skin and mucous membranes, as well as on animals and in the environment. Biofilm formation enables this organism to evade the host immune system. Colonization of percutaneous devices or implanted medical devices allows bacteria access to the bloodstream. Isolation of this organism from blood cultures may represent either contamination during the blood collection procedure or true bacteremia. S. epidermidis bloodstream infections may be indolent compared with other bacteria. Isolation of S. epidermidis from a blood culture may present a management quandary for clinicians. Over-treatment may lead to patient harm and increases in healthcare costs. There are numerous reports indicating the difficulty of predicting clinical infection in patients with positive blood cultures with this organism. No reliable phenotypic or genotypic algorithms currently exist to predict the pathogenicity of a S. epidermidis bloodstream infection. This review will discuss the latest advances in identification methods, global population structure, pathogenicity, biofilm formation, antimicrobial resistance and clinical significance of the detection of S. epidermidis in blood cultures. Previous studies that have attempted to discriminate between invasive and contaminating strains of S. epidermidis in blood cultures will be analyzed.

Solid and Suspension Microarrays for Microbial Diagnostics

Advancements in molecular technologies have provided new platforms that are being increasingly adopted for use in the clinical microbiology laboratory. Among these, microarray methods are particularly well suited for diagnostics as they allow multiplexing, or the ability to test for multiple targets simultaneously from the same specimen. Microarray technologies commonly used for the detection and identification of microbial targets include solid-state microarrays, electronic microarrays and bead suspension microarrays. Microarray methods have been applied to microbial detection, genotyping and antimicrobial resistance gene detection. Microarrays can offer a panel approach to diagnose specific patient presentations, such as respiratory or gastrointestinal infections, and can discriminate isolates by genotype for tracking epidemiology and outbreak investigations. And, as more information has become available on specific genes and pathways involved in antimicrobial resistance, we are beginning to be able to predict susceptibility patterns based on sequence detection for particular organisms. With further advances in automated microarray processing methods and genotype-phenotype prediction algorithms, these tests will become even more useful as an adjunct or replacement for conventional antimicrobial susceptibility testing, allowing for more rapid selection of targeted therapy for infectious diseases.

Reprint of "Assessment of marker proteins identified in whole cell extracts for bacterial speciation using liquid chromatography electrospray ionization tandem mass spectrometry"

Staphylococcal strains (CoNS) were speciated in this study. Digests of proteins released from whole cells were converted to tryptic peptides for analysis. Liquid chromatography electrospray ionization tandem mass spectrometry (LC-ESI MS/MS, Orbitrap) was employed for peptide analysis. Data analysis was performed employing the open-source software X!Tandem which uses sequenced genomes to generate a virtual peptide database for comparison to experimental data. The search database was modified to include the genomes of the 11 Staphylococcus species most commonly isolated from man. The number of total peptides matching each protein along with the number of peptides specifically matching to the homologue (or homologues) for strains of the same species were assessed. Any peptides not matching to the species examined were considered conflict peptides. The proteins typically identified with the largest percentage of sequence coverage, number of matched peptides and number of peptides corresponding to only the correct species were elongation factor Tu (EF Tu) and enolase (Enol). Additional proteins with consistently observed peptides as well as peptides matching only homologues from the same species were citrate synthase (CS) and 1-pyrroline-5-carboxylate dehydrogenase (1P5CD). Protein markers, previously identified from gel slices, (aconitate hydratase and oxoglutarate dehydrogenase) were found to provide low confidence scores when employing whole cell digests. The methodological approach described here provides a simple yet elegant way of identification of staphylococci. However, perhaps more importantly the technology should be applicable universally for identification of any bacterial species.

Assessment of marker proteins identified in whole cell extracts for bacterial speciation using liquid chromatography electrospray ionization tandem mass spectrometry

Staphylococcal strains (CoNS) were speciated in this study. Digests of proteins released from whole cells were converted to tryptic peptides for analysis. Liquid chromatography electrospray ionization tandem mass spectrometry (LC-ESI MS/MS, Orbitrap) was employed for peptide analysis. Data analysis was performed employing the open-source software X!Tandem which uses sequenced genomes to generate a virtual peptide database for comparison to experimental data. The search database was modified to include the genomes of the 11 Staphylococcus species most commonly isolated from man. The number of total peptides matching each protein along with the number of peptides specifically matching to the homologue (or homologues) for strains of the same species were assessed. Any peptides not matching to the species examined were considered conflict peptides. The proteins typically identified with the largest percentage of sequence coverage, number of matched peptides and number of peptides corresponding to only the correct species were elongation factor Tu (EF Tu) and enolase (Enol). Additional proteins with consistently observed peptides as well as peptides matching only homologues from the same species were citrate synthase (CS) and 1-pyrroline-5-carboxylate dehydrogenase (1P5CD). Protein markers, previously identified from gel slices, (aconitate hydratase and oxoglutarate dehydrogenase) were found to provide low confidence scores when employing whole cell digests. The methodological approach described here provides a simple yet elegant way of identification of staphylococci. However, perhaps more importantly the technology should be applicable universally for identification of any bacterial species.