Poultry and Beef Meat as Potential Seedbeds for Antimicrobial Resistant Enterotoxigenic Bacillus Species: A Materializing Epidemiological and Potential Severe Health Hazard

Although Bacillus cereus is of particular concern in food safety and public health, the role of other Bacillus species was overlooked. Therefore, we investigated the presence of eight enterotoxigenic genes, a hemolytic gene and phenotypic antibiotic resistance profiles of Bacillusspecies in retail meat samples. From 255 samples, 124 Bacillus isolates were recovered, 27 belonged to B. cereusand 97 were non-B. cereus species. Interestingly, the non-B. cereus isolates carried the virulence genes and exhibited phenotypic virulence characteristics as the B. cereus. However, correlation matrix analysis revealed the B. cereus group positively correlates with the presence of the genes hblA, hblC, and plc, and the detection of hemolysis (p \u3c 0.05), while the other Bacillus sp. groups are negatively correlated. Tests for antimicrobial resistance against ten antibiotics revealed extensive drug and multi-drug resistant isolates. Statistical analyses didn’t support a correlation of antibiotic resistance to tested virulence factors suggesting independence of these phenotypic markers and virulence genes. Of special interest was the isolation of Paenibacillus alvei and Geobacillus stearothermophilus from the imported meat samples being the first recorded. The isolation of non-B. cereus species carrying enterotoxigenic genes in meat within Egypt, suggests their impact on food safety and public health and should therefore not be minimised, posing an area that requires further research

Conserved collateral antibiotic susceptibility networks in diverse clinical strains of Escherichia coli.

There is urgent need to develop novel treatment strategies to reduce antimicrobial resistance. Collateral sensitivity (CS), where resistance to one antimicrobial increases susceptibility to other drugs, might enable selection against resistance during treatment. However, the success of this approach would depend on the conservation of CS networks across genetically diverse bacterial strains. Here, we examine CS conservation across diverse Escherichia coli strains isolated from urinary tract infections. We determine collateral susceptibilities of mutants resistant to relevant antimicrobials against 16 antibiotics. Multivariate statistical analyses show that resistance mechanisms, in particular efflux-related mutations, as well as the relative fitness of resistant strains, are principal contributors to collateral responses. Moreover, collateral responses shift the mutant selection window, suggesting that CS-informed therapies may affect evolutionary trajectories of antimicrobial resistance. Our data allow optimism for CS-informed therapy and further suggest that rapid detection of resistance mechanisms is important to accurately predict collateral responses

Markov chain Monte Carlo and expectation maximization approaches for estimation of haplotype frequencies for multiply infected human blood samples

Background Haplotypes are important in anti-malarial drug resistance because genes encoding drug resistance may accumulate mutations at several codons in the same gene, each mutation increasing the level of drug resistance and, possibly, reducing the metabolic costs of previous mutation. Patients often have two or more haplotypes in their blood sample which may make it impossible to identify exactly which haplotypes they carry, and hence to measure the type and frequency of resistant haplotypes in the malaria population. Results This study presents two novel statistical methods expectation–maximization (EM) and Markov chain Monte Carlo (MCMC) algorithms to investigate this issue. The performance of the algorithms is evaluated on simulated datasets consisting of patient blood characterized by their multiplicity of infection (MOI) and malaria genotype. The datasets are generated using different resistance allele frequencies (RAF) at each single nucleotide polymorphisms (SNPs) and different limit of detection (LoD) of the SNPs and the MOI. The EM and the MCMC algorithm are validated and appear more accurate, faster and slightly less affected by LoD of the SNPs and the MOI compared to previous related statistical approaches. Conclusions The EM and the MCMC algorithms perform well when analysing malaria genetic data obtained from infected human blood samples. The results are robust to genotyping errors caused by LoDs and function well even in the absence of MOI data on individual patients

Detecting and Estimating Signals in Noisy Cable Structures, I: Neuronal Noise Sources

In recent theoretical approaches addressing the problem of neural coding, tools from statistical estimation and information theory have been applied to quantify the ability of neurons to transmit information through their spike outputs. These techniques, though fairly general, ignore the specific nature of neuronal processing in terms of its known biophysical properties. However, a systematic study of processing at various stages in a biophysically faithful model of a single neuron can identify the role of each stage in information transfer. Toward this end, we carry out a theoretical analysis of the information loss of a synaptic signal propagating along a linear, one-dimensional, weakly active cable due to neuronal noise sources along the way, using both a signal reconstruction and a signal detection paradigm. Here we begin such an analysis by quantitatively characterizing three sources of membrane noise: (1) thermal noise due to the passive membrane resistance, (2) noise due to stochastic openings and closings of voltage-gated membrane channels (Na^+ and K^+), and (3) noise due to random, background synaptic activity. Using analytical expressions for the power spectral densities of these noise sources, we compare their magnitudes in the case of a patch of membrane from a cortical pyramidal cell and explore their dependence on different biophysical parameters

Increase in isolation of extended spectrum beta lactamase producing multidrug resistant non typhoidal Salmonellae in Pakistan.

Background:Increasing resistance to quinolones and ceftriaxone in non typhoidal Salmonellae is a global concern. Resistance to quinolone and 3rd generation cephalosporin amongst non typhoidal Salmonellae (NTS) from Pakistan has been reported in this study. Methods: Retrospective analysis of laboratory data was conducted (1990-2006). NTS were isolated and identified from clinical samples using standard microbiological techniques. Antimicrobial susceptibility testing was performed by Kirby Bauer. Extended spectrum beta lactamase production (ESBL) was detected using combined disc method. Ciprofloxacin sensitivity was detected by nalidixic acid screening method. Minimum inhibitory concentration (MIC) of ciprofloxacin was determined by agar dilution method. Statistical analysis was performed using SPSS version 13. Results: Analysis of 1967 NTS isolates showed a significant increase in ciprofloxacin resistance from 23% in 2002 to 50.5% in 2006, with increased mean MIC values from 0.6 to 1.3 ug/mL. Ceftriaxone resistant NTS also increased and ESBL production was seen in 98.7% isolates. These isolates exhibited high resistance against amoxicillin clavulanic acid (57%), gentamicin (69%), amikacin (44%) and piperacillin tazobactam (30%). No resistance to carbapenem was seen. Ceftriaxone resistance was significantly higher in childrenyear, in invasive isolates and in Salmonella Typhimurium. Conclusion: Increase in quinolone and ceftriaxone NTS is a serious threat to public health requiring continuous surveillance and use of appropriate screening tests for laboratory detection

Epidemiology of resistance and phenotypic characterization of carbapenem resistance mechanisms in Klebsiella pneumoniae isolates at Sahloul University Hospital-Sousse, Tunisia

Objective: To assess the prevalence of ESBL producing and carbapenem resistant Klebsiella pneumoniae isolated from in-come and out-come patients at Sahloul-university hospital.Methods: A retrospective study over a 3 years period (January 2012 and December 2014) focused on 2160 strains of Klebsiella pneumoniae. Statistical analysis was carried out using SPSS program. ESBL detection was performed using a double disc diffusion method and carbapenemase detection was realized by Rosco-Disk kit.Results: A total of 2160 Klebsiella pneumoniae strains were isolated during the period of the study, 26.2% (n=566) were ESBL-producers and 15.8% (n=342) showed resistance to carbapenem. The wards most affected by these strains were basically urology and intensive care units. Eighty four percent of studied strains (203/241) were resistant to temocillin, which correlate with the production of a class D (OXA-48-like) carbapenemase and 7% (17/241) showed sensitivity to EDTA and dipicolinic acid, which indicate the production of metallo-enzyme. The rate of resistance to colistin remains low.Conclusion: Resistance of Enterobacteriaceae, including K. pneumoniae, to third generation cephalosporins (3rd GC) and carbapenem through the mechanism of ESBL and carbapenemases production is becoming increasingly worrying. This suggests a morerational use of antibiotics, as well as the rigorous application of hygiene measurement.Keywords: Klebsiella pneumoniae, epidemiology, ESBL, carbapenemase, phenotypic screening

A multi-method approach to delineate and validate migratory corridors

Context: Managers are faced with numerous methods for delineating wildlife movement corridors, and often must make decisions with limited data. Delineated corridors should be robust to different data and models. Objectives: We present a multi-method approach for delineating and validating wildlife corridors using multiple data sources, which can be used conserve landscape connectivity. We used this approach to delineate and validate migration corridors for wildebeest (Connochaetes taurinus) in the Tarangire Ecosystem of northern Tanzania. Methods: We used two types of locational data (distance sampling detections and GPS collar locations), and three modeling methods (negative binomial regression, logistic regression, and Maxent), to generate resource selection functions (RSFs) and define resistance surfaces. We compared two corridor detection algorithms (cost-distance and circuit theory), to delineate corridors. We validated corridors by comparing random and wildebeest locations that fell within corridors, and cross-validated by data type. Results: Both data types produced similar RSFs. Wildebeest consistently selected migration habitat in flatter terrain farther from human settlements. Validation indicated three of the combinations of data type, modeling, and corridor detection algorithms (detection data with Maxent modeling, GPS collar data with logistic regression modeling, and GPS collar data with Maxent modeling, all using cost-distance) far outperformed the other seven. We merged the predictive corridors from these three data-method combinations to reveal habitat with highest probability of use. Conclusions: The use of multiple methods ensures that planning is able to prioritize conservation of migration corridors based on all available information