Dengue: pathogenesis, prevention and treatment – A mini review

Dengue is a threatening tropical disease which has become the cause of significant mortality, morbidity and economic burden. Dengue is an epidemic in over 100 countries, and it causes up to 25000 deaths every year. There is no specific cure available for the disease, hence fluid resuscitation is the only ultimate treatment given to patients in severe conditions. Dengue is more threatening in Southeast Asia, where it is the leading cause of deaths in children, and where all four serotypes of the dengue virus and the vector, Aedes aegypti, are endemic. In last few decades, an overwhelming increase was seen in dengue infections around the world and it is estimated that two fifths of the world's population is now at risk from dengue with the mortality rate of about 5%. To control dengue infection, combination of care measures are utilized which depends on the symptoms and severity of the fever, including oral rehydration solution or isotonic intravenous fluids and/or blood transfusions. Currently, the only effective way of preventing the dengue epidemics is eliminating the vector. This review covers pathogenesis, prevention and treatment of dengue infection

Navigating the brain: the role of exosomal shuttles in precision therapeutics

Brain diseases have become one of the leading roots of mortality and disability worldwide, contributing a significant part of the disease burden on healthcare systems. The blood-brain barrier (BBB) is a primary physical and biological obstacle that allows only small molecules to pass through it. Its selective permeability is a significant challenge in delivering therapeutics into the brain for treating brain dysfunction. It is estimated that only 2% of the new central nervous system (CNS) therapeutic compounds can cross the BBB and achieve their therapeutic targets. Scientists are exploring various approaches to develop effective cargo delivery vehicles to promote better therapeutics targeting the brain with minimal off-target side effects. Despite different synthetic carriers, one of the natural brain cargo delivery systems, “exosomes,” are now employed to transport drugs through the BBB. Exosomes are naturally occurring small extracellular vesicles (EVs) with unique advantages as a therapeutic delivery system for treating brain disorders. They have beneficial innate aspects of biocompatibility, higher stability, ability to cross BBB, low cytotoxicity, low immunogenicity, homing potential, targeted delivery, and reducing off-site target effects. In this review, we will discuss the limitations of synthetic carriers and the utilization of naturally occurring exosomes as brain-targeted cargo delivery vehicles and highlight the methods for modifying exosome surfaces and drug loading into exosomes. We will also enlist neurodegenerative disorders targeted with genetically modified exosomes for their treatment

Evaluation of machine learning and rules-based approaches for predicting antimicrobial resistance profiles in gram-negative bacilli from whole genome sequence data

The time-to-result for culture-based microorganism recovery and phenotypic antimicrobial susceptibility testing necessitates initial use of empiric (frequently broad-spectrum) antimicrobial therapy. If the empiric therapy is not optimal, this can lead to adverse patient outcomes and contribute to increasing antibiotic resistance in pathogens. New, more rapid technologies are emerging to meet this need. Many of these are based on identifying resistance genes, rather than directly assaying resistance phenotypes, and thus require interpretation to translate the genotype into treatment recommendations. These interpretations, like other parts of clinical diagnostic workflows, are likely to be increasingly automated in the future. We set out to evaluate the two major approaches that could be amenable to automation pipelines: rules-based methods and machine learning methods. The rules-based algorithm makes predictions based upon current, curated knowledge of Enterobacteriaceae resistance genes. The machine-learning algorithm predicts resistance and susceptibility based on a model built from a training set of variably resistant isolates. As our test set, we used whole genome sequence data from 78 clinical Enterobacteriaceae isolates, previously identified to represent a variety of phenotypes, from fully-susceptible to pan-resistant strains for the antibiotics tested. We tested three antibiotic resistance determinant databases for their utility in identifying the complete resistome for each isolate. The predictions of the rules-based and machine learning algorithms for these isolates were compared to results of phenotype-based diagnostics. The rules based and machine-learning predictions achieved agreement with standard-of-care phenotypic diagnostics of 89.0 and 90.3%, respectively, across twelve antibiotic agents from six major antibiotic classes. Several sources of disagreement between the algorithms were identified. Novel variants of known resistance factors and incomplete genome assembly confounded the rules-based algorithm, resulting in predictions based on gene family, rather than on knowledge of the specific variant found. Low-frequency resistance caused errors in the machine-learning algorithm because those genes were not seen or seen infrequently in the test set. We also identified an example of variability in the phenotype-based results that led to disagreement with both genotype-based methods. Genotype-based antimicrobial susceptibility testing shows great promise as a diagnostic tool, and we outline specific research goals to further refine this methodology

Superficieibacter electus gen. nov., sp. nov., an extended-spectrum β-lactamase possessing member of the enterobacteriaceae family, isolated from Intensive Care Unit surfaces

<p>Two Gram-negative bacilli strains, designated BP-1(T) and BP-2, were recovered from two different Intensive Care Unit surfaces during a longitudinal survey in Pakistan. Both strains were unidentified using the bioMerieux VITEK MS IVD v2.3.3 and Bruker BioTyper MALDI-TOF mass spectrometry platforms. To more precisely determine the taxonomic identity of BP-1(T) and BP-2, we employed a biochemical and phylogenomic approach. The 16S rRNA gene sequence of strain BP-1(T) had the highest identity to Citrobacter farmeri CDC 2991-81(T) (98.63%) Citrobacter amalonaticus CECT 863(T) (98.56%), Citrobacter sedlakii NBRC 105722(T) (97.74%) and Citrobacter rodentium NBRC 105723(T) (97.74%). The biochemical utilization scheme of BP-1(T) using the Analytic Profile Index for Enterobacteriaceae (API20E) indicated its enzymatic functions are unique within the Enterobacteriaceae but most closely resemble Kluyvera spp., Enterobacter cloacae and Citrobacter koseri/farmeri. Phylogenomic analysis of the shared genes between BP-1(T), BP-2 and type strains from Kluyvera, Citrobacter, Escherichia, Salmonella, Kosakonia, Siccibacter and Shigella indicate that BP-1(T) and BP-2 isolates form a distinct branch from these genera. Average Nucleotide Identity analysis indicates that BP-1(T) and BP-2 are the same species. The biochemical and phylogenomic analysis indicate strains BP-1(T) and BP-2 represent a novel species from a new genus within the Enterobacteriaceae family, for which the name Superficieibacter electus gen. nov., sp. nov., is proposed. The type strain is BP-1(T) (= ATCC BAA-2937, = NBRC 113412).</p

Phenotypic and genotypic characterization of linezolid-resistant Enterococcus faecium from the USA and Pakistan

OBJECTIVES: Linezolid is an important therapeutic option for the treatment of infections caused by VRE. Linezolid is a synthetic antimicrobial and resistance to this antimicrobial agent remains relatively rare. As a result, data on the comparative genomics of linezolid resistance determinants in Enterococcus faecium are relatively sparse. METHODS: To address this knowledge gap in E. faecium, we deployed phenotypic antibiotic susceptibility testing and Illumina WGS on hospital surface (environmental) and clinical isolates from the USA and Pakistan. RESULTS: We found complete concordance between isolate source country and mechanism of linezolid resistance, with all the US isolates possessing a 23S rRNA gene mutation and the Pakistan isolates harbouring two to three acquired antibiotic resistance genes. These resistance genes include the recently elucidated efflux-pump genes optrA and poxtA and a novel cfr-like variant. Although there was no difference in the linezolid MIC between the US and Pakistan isolates, there was a significant difference in the geometric mean of the MIC between the Pakistan isolates that had two versus three of the acquired antibiotic resistance genes. In five of the Pakistan E. faecium that possessed all three of the resistance genes, we found no difference in the local genetic context of poxtA and the cfr-like gene, but we identified different genetic contexts surrounding optrA. CONCLUSIONS: These results demonstrate that E. faecium from different geographical regions employ alternative strategies to counter selective pressure of increasing clinical linezolid use

Intensive care unit sinks are persistently colonized with multidrug resistant bacteria and mobilizable, resistance-conferring plasmids

Contamination of hospital sinks with microbial pathogens presents a serious potential threat to patients, but our understanding of sink colonization dynamics is largely based on infection outbreaks. Here, we investigate the colonization patterns of multidrug-resistant organisms (MDROs) in intensive care unit sinks and water from two hospitals in the USA and Pakistan collected over 27 months of prospective sampling. Using culture-based methods, we recovered 822 bacterial isolates representing 104 unique species and genomospecies. Genomic analyses revealed long-term colonization b