Community-Acquired Methicillin Resistant Staphylococcus aureus:Effects Of Subinhibitory Concentrations of Antibiotics on the Proteome Profile USA300. Pathogeneses and susceptibility

Staphylococcus aureus is a causative agent of many severe infections in the health care setting. Strains of increased virulence such as the community acquired methicillin-resistant S. aureus (CA-MRSA), USA300 clone, have recently emerged and have the ability to infect even healthy individuals and are difficult to treat. This report addresses the response of USA300 clone to two subinhibitory concentrations (0.25 and 0.5MICs) of four clinically relevant antibiotics, linezolid, tigecycline, oxacillin and vancomycin, by using MS/MS-proteomics approach, which let us the analyses the 980 differentially expressed proteins by bioinformatics studies. This study enables a comprehensive overview of the proteome of this hypervirulent and resistance CA-MRSA-USA300 clone, and its response to antibiotic pressure. Unlike previous genome-wide transcriptome studies where it monitored changes on mRNA but not on protein level that directly reflect physiologically relevant adaptations. We focused on several groups of main proteins associated to mechanism of action of antibiotics (including mechanism of resistance) an pathogenesis. Here, we provide evidence at the proteome adaptation of USA300 independently of the mechanism of action of every antibiotic and the possible therapeutic effect on the USA300 of higher subinhibitory concentrations of several clinical used antibiotics. The higher subinhibitory (0.5MIC) concentrations appeared to be effective. According to their effects on the proteins involved in pathogenesis proteins, the vancomycin showed to be the less effective and the tigecycline the most effective. Tigecycline got to down-regulated the expression of the main virulence factor α-haemolysin Hla. The contrary, oxacillin up-regulated the expression of the virulence factor involved in the pathogenesis phenol-soluble-modulins (PSM) and panton-valentine-leukocidin (PVL) subunit F Luk-F . Overview, the USA300 clone is able to adapt itself to antibiotic pressure of subinhibitory concentrations, trying to maintain the necessary proteins to its "alive", such as mechanism of resistance and virulence proteins, at the same time that increase the stress response after exposition the antibiotic pressure

Computational health engineering applied to model infectious diseases and antimicrobial resistance spread

Infectious diseases are the primary cause of mortality worldwide. The dangers of infectious disease are compounded with antimicrobial resistance, which remains the greatest concern for human health. Although novel approaches are under investigation, the World Health Organization predicts that by 2050, septicaemia caused by antimicrobial resistant bacteria could result in 10 million deaths per year. One of the main challenges in medical microbiology is to develop novel experimental approaches, which enable a better understanding of bacterial infections and antimicrobial resistance. After the introduction of whole genome sequencing, there was a great improvement in bacterial detection and identification, which also enabled the characterization of virulence factors and antimicrobial resistance genes. Today, the use of in silico experiments jointly with computational and machine learning offer an in depth understanding of systems biology, allowing us to use this knowledge for the prevention, prediction, and control of infectious disease. Herein, the aim of this review is to discuss the latest advances in human health engineering and their applicability in the control of infectious diseases. An in-depth knowledge of host?pathogen?protein interactions, combined with a better understanding of a host?s immune response and bacterial fitness, are key determinants for halting infectious diseases and antimicrobial resistance dissemination

Applications of Nanodiamonds in the Detection and Therapy of Infectious Diseases

We are constantly exposed to infectious diseases, and they cause millions of deaths per year. The World Health Organization (WHO) estimates that antibiotic resistance could cause 10 million deaths per year by 2050. Multidrug-resistant bacteria are the cause of infection in at least one in three people suffering from septicemia. While antibiotics are powerful agents against infectious diseases, the alarming increase in antibiotic resistance is of great concern. Alternatives are desperately needed, and nanotechnology provides a great opportunity to develop novel approaches for the treatment of infectious diseases. One of the most important factors in the prognosis of an infection caused by an antibiotic resistant bacteria is an early and rigorous diagnosis, jointly with the use of novel therapeutic systems that can specifically target the pathogen and limit the selection of resistant strains. Nanodiamonds can be used as antimicrobial agents due to some of their properties including size, shape, and biocompatibility, which make them highly suitable for the development of efficient and tailored nanotherapies, including vaccines or drug delivery systems. In this review, we discuss the beneficial findings made in the nanodiamonds field, focusing on diagnosis and treatment of infectious diseases. We also highlight the innovative platform that nanodiamonds confer for vaccine improvement, drug delivery, and shuttle systems, as well as their role in the generation of faster and more sensitive clinical diagnosis

Application and Perspectives of MALDI–TOF Mass Spectrometry in Clinical Microbiology Laboratories

Early diagnosis of severe infections requires of a rapid and reliable diagnosis to initiate appropriate treatment, while avoiding unnecessary antimicrobial use and reducing associated morbidities and healthcare costs. It is a fact that conventional methods usually require more than 24–48 h to culture and profile bacterial species. Mass spectrometry (MS) is an analytical technique that has emerged as a powerful tool in clinical microbiology for identifying peptides and proteins, which makes it a promising tool for microbial identification. Matrix assisted laser desorption ionization–time of flight MS (MALDI–TOF MS) offers a cost- and time-effective alternative to conventional methods, such as bacterial culture and even 16S rRNA gene sequencing, for identifying viruses, bacteria and fungi and detecting virulence factors and mechanisms of resistance. This review provides an overview of the potential applications and perspectives of MS in clinical microbiology laboratories and proposes its use as a first-line method for microbial identification and diagnosis

Computational health engineering applied to model infectious diseases and antimicrobial resistance spread

Infectious diseases are the primary cause of mortality worldwide. The dangers of infectious disease are compounded with antimicrobial resistance, which remains the greatest concern for human health. Although novel approaches are under investigation, the World Health Organization predicts that by 2050, septicaemia caused by antimicrobial resistant bacteria could result in 10 million deaths per year. One of the main challenges in medical microbiology is to develop novel experimental approaches, which enable a better understanding of bacterial infections and antimicrobial resistance. After the introduction of whole genome sequencing, there was a great improvement in bacterial detection and identification, which also enabled the characterization of virulence factors and antimicrobial resistance genes. Today, the use of in silico experiments jointly with computational and machine learning offer an in depth understanding of systems biology, allowing us to use this knowledge for the prevention, prediction, and control of infectious disease. Herein, the aim of this review is to discuss the latest advances in human health engineering and their applicability in the control of infectious diseases. An in-depth knowledge of host-pathogen-protein interactions, combined with a better understanding of a host's immune response and bacterial fitness, are key determinants for halting infectious diseases and antimicrobial resistance dissemination

Direct Urine Resistance Detection Using VITEK 2

Urinary tract infections (UTIs) are the most common infectious diseases in both communities and hospitals. With non-anatomical or functional abnormalities, UTIs are usually self-limiting, though women suffer more reinfections throughout their lives. Certainly, antibiotic treatment leads to a more rapid resolution of symptoms, but also it selects resistant uropathogens and adversely affects the gut and vaginal microbiota. As uropathogens are increasingly becoming resistant to currently available antibiotics, it could be time to explore alternative strategies for managing UTIs. Rapid identification and antimicrobial susceptibility testing (AST) allow fast and precise treatment. The objective of this study was to shorten the time of diagnosis of UTIs by combining pathogen screening through flow cytometry, microbial identification by matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF MS), and the VITEK 2 system for the direct analysis of urine samples. First, we selected positive urine samples by flow cytometry using UF5000, establishing the cut-off for positive at 150 bacteria/mL. After confirming the identification using MALDI-TOF MS and filtering the urine samples for Escherichia coli, we directly tested the AST N388 card using VITEK 2. We tested a total of 211 E. coli from urine samples. Cefoxitin, ertapenem, imipenem, gentamicin, nalidixic acid, ciprofloxacin, fosfomycin, and nitrofurantoin had no major important errors (MIE), and ampicillin, cefuroxime, and tobramycin showed higher MIEs. Cefepime, imipenem, and tobramycin had no major errors (ME). Fosfomycin was the antibiotic with the most MEs. The antibiotic with the most minor errors (mE) was ceftazidime. The total categorical agreement (CA) was 97.4% with a 95% CI of (96.8–97.9)95%. The direct AST from the urine samples proposed here was shorter by one day, without significant loss of sensibility regarding the standard diagnosis. Therefore, we hypothesize that this method is more realistic and better suited to human antibiotic concentrations