Microorganisms may colonize needleless connectors (NCs) on intravascular catheters, forming biofilms and predisposing patients to catheter-associated infection (CAI). Standard and silver-coated NCs were collected from catheterized intensive care unit patients to characterize biofilm formation using culture-dependent and culture-independent methods and to investigate the associations between NC usage and biofilm characteristics. Viable microorganisms were detected by plate counts from 46% of standard NCs and 59% of silver-coated NCs ( P = 0.11). There were no significant associations ( P > 0.05, chi-square test) between catheter type, side of catheter placement, number of catheter lumens, site of catheter placement, or NC placement duration and positive NC findings. There was an association ( P = 0.04, chi-square test) between infusion type and positive findings for standard NCs. Viable microorganisms exhibiting intracellular esterase activity were detected on >90% of both NC types ( P = 0.751), suggesting that a large percentage of organisms were not culturable using the conditions provided in this study. Amplification of the 16S rRNA gene from selected NCs provided a substantially larger number of operational taxonomic units per NC than did plate counts (26 to 43 versus 1 to 4 operational taxonomic units/NC, respectively), suggesting that culture-dependent methods may substantially underestimate microbial diversity on NCs. NC bacterial communities were clustered by patient and venous access type and may reflect the composition of the patient's local microbiome but also may contain organisms from the health care environment. NCs provide a portal of entry for a wide diversity of opportunistic pathogens to colonize the catheter lumen, forming a biofilm and increasing the potential for CAI, highlighting the importance of catheter maintenance practices to reduce microbial contamination.

Chlamydia psittaci is an obligate intracellular bacterium that can cause significant disease among a broad range of hosts. In humans, this organism may cause psittacosis, a respiratory disease that can spread to involve multiple organs, and in rare untreated cases may be fatal. There are ten known genotypes based on sequencing the major outer-membrane protein gene, ompA, of C. psittaci. Each genotype has overlapping host preferences and virulence characteristics. Recent studies have compared C. psittaci among other members of the Chlamydiaceae family and showed that this species frequently switches hosts and has undergone multiple genomic rearrangements. In this study, we sequenced five genomes of C. psittaci strains representing four genotypes, A, B, D and E. Due to the known association of the type III secretion system (T3SS) and polymorphic outer-membrane proteins (Pmps) with host tropism and virulence potential, we performed a comparative analysis of these elements among these five strains along with a representative genome from each of the remaining six genotypes previously sequenced. We found significant genetic variation in the Pmps and tbl3SS genes that may partially explain differences noted in C. psittaci host infection and disease.

Bordetella holmesii , a human pathogen, can confound the diagnosis of respiratory illness caused by Bordetella pertussis . We present the draft genome sequences of two B. holmesii isolates, one from blood, F627, and one from the nasopharynx, H558. Interestingly, important virulence genes that are present in B. pertussis are not found in B. holmesii .

Shiga toxin-producing Escherichia coli (STEC) are a common cause for food-borne diarrheal illness outbreaks and sporadic cases. Here, we report the availability of the draft genome sequences of 228 STEC strains representing 32 serotypes with known pulsed-field gel electrophoresis (PFGE) types and epidemiological relationships, as well as 12 strains representing other diarrheagenic E. coli pathotypes.

Background: Genomics diagnostic tests are done for a wide spectrum of complex genetics conditions such as autism and cancer. The growth of technology has not only aided in successfully decoding the genetic variants that causes or trigger these disorders. However, interpretation of these variants is not a trivial task even at a level of distinguish pathogenic vs benign variants. Methods: We used the clinically significant variants from ClinVar database to evaluate the performance of 14 most popular in-silico predictors using supervised learning methods. We implemented a feature selection and random forest classification algorithm to identify the best combination of predictors to evaluate the pathogenicity of a variant. Finally, we have also utilized this combination of predictors to reclassify the variants of unknown significance in MeCP2 gene that are associated with the Rett syndrome. Results: The results from analysis shows an optimized selection of prediction algorithm and developed a combinatory predictor method. Our combinatory approach of using both best performing independent and ensemble predictors reduces any algorithm biases in variant characterization. The reclassification of variants (such as VUS) in MECP2 gene associated with RETT syndrome suggest that the combinatory in-silico predictor approach had a higher success rate in categorizing their pathogenicity.

Burkholderia pseudomallei strain Bp1651, a human isolate, is resistant to all clinically relevant antibiotics. We report here on the finished genome sequence assembly and annotation of the two chromosomes of this strain. This genome sequence may assist in understanding the mechanisms of antimicrobial resistance for this pathogenic species.