Whole genome sequencing of human Borrelia burgdorferi isolates reveals linked blocks of accessory genome elements located on plasmids and associated with human dissemination.

Lyme disease is the most common vector-borne disease in North America and Europe. The clinical manifestations of Lyme disease vary based on the genospecies of the infecting Borrelia burgdorferi spirochete, but the microbial genetic elements underlying these associations are not known. Here, we report the whole genome sequence (WGS) and analysis of 299 B. burgdorferi (Bb) isolates derived from patients in the Eastern and Midwestern US and Central Europe. We develop a WGS-based classification of Bb isolates, confirm and extend the findings of previous single- and multi-locus typing systems, define the plasmid profiles of human-infectious Bb isolates, annotate the core and strain-variable surface lipoproteome, and identify loci associated with disseminated infection. A core genome consisting of ~900 open reading frames and a core set of plasmids consisting of lp17, lp25, lp36, lp28-3, lp28-4, lp54, and cp26 are found in nearly all isolates. Strain-variable (accessory) plasmids and genes correlate strongly with phylogeny. Using genetic association study methods, we identify an accessory genome signature associated with dissemination in humans and define the individual plasmids and genes that make up this signature. Strains within the RST1/WGS A subgroup, particularly a subset marked by the OspC type A genotype, have increased rates of dissemination in humans. OspC type A strains possess a unique set of strongly linked genetic elements including the presence of lp56 and lp28-1 plasmids and a cluster of genes that may contribute to their enhanced virulence compared to other genotypes. These features of OspC type A strains reflect a broader paradigm across Bb isolates, in which near-clonal genotypes are defined by strain-specific clusters of linked genetic elements, particularly those encoding surface-exposed lipoproteins. These clusters of genes are maintained by strain-specific patterns of plasmid occupancy and are associated with the probability of invasive infection.

A novel hybridization capture method for direct whole genome sequencing of clinical specimens to inform Legionnaires' disease investigations.

The unprecedented precision and resolution of whole genome sequencing (WGS) can provide definitive identification of infectious agents for epidemiological outbreak tracking. WGS approaches, however, are frequently impeded by low pathogen DNA recovery from available primary specimens or unculturable samples. A cost-effective hybrid capture assay for Legionella pneumophila WGS analysis directly on primary specimens was developed. DNA from a diverse range of sputum and autopsy specimens PCR-positive for L. pneumophila serogroup 1 (LPSG1) was enriched with this method, and WGS was performed. All tested specimens were determined to be enriched for Legionella reads (up to 209,000-fold), significantly improving the discriminatory power to compare relatedness when no clinical isolate was available. We found the WGS data from some enriched specimens to differ by less than five single-nucleotide polymorphisms (SNPs) when compared to the WGS data of a matched culture isolate. This testing and analysis retrospectively provided previously unconfirmed links to environmental sources for clinical specimens of sputum and autopsy lung tissue. The latter provided the additional information needed to identify the source of these culture-negative cases associated with the South Bronx 2015 Legionnaires' disease (LD) investigation in New York City. This new method provides a proof of concept for future direct clinical specimen hybrid capture enrichment combined with WGS and bioinformatic analysis during outbreak investigations.IMPORTANCELegionnaires' disease (LD) is a severe and potentially fatal type of pneumonia primarily caused by inhalation of Legionella-contaminated aerosols from man-made water or cooling systems. LD remains extremely underdiagnosed as it is an uncommon form of pneumonia and relies on clinicians including it in the differential and requesting specialized testing. Additionally, it is challenging to obtain clinical lower respiratory specimens from cases with LD, and when available, culture requires specialized media and growth conditions, which are not available in all microbiology laboratories. In the current study, a method for Legionella pneumophila using hybrid capture by RNA baiting was developed, which allowed us to generate sufficient genome resolution from L. pneumophila serogroup 1 PCR-positive clinical specimens. This new approach offers an additional tool for surveillance of future LD outbreaks where isolation of Legionella is not possible and may help solve previously unanswered questions from past LD investigations.

Widespread suppression of intragenic transcription initiation by H-NS.

Widespread intragenic transcription initiation has been observed in many species. Here we show that the Escherichia coli ehxCABD operon contains numerous intragenic promoters in both sense and antisense orientations. Transcription from these promoters is silenced by the histone-like nucleoid structuring (H-NS) protein. On a genome-wide scale, we show that 46% of H-NS-suppressed transcripts in E. coli are intragenic in origin. Furthermore, many intergenic promoters repressed by H-NS are for noncoding RNAs (ncRNAs). Thus, a major overlooked function of H-NS is to prevent transcription of spurious RNA. Our data provide a molecular description for the toxicity of horizontally acquired DNA and explain how this is counteracted by H-NS.

Whole-Genome Sequencing of SARS-CoV-2: Assessment of the Ion Torrent AmpliSeq Panel and Comparison with the Illumina MiSeq ARTIC Protocol.

Fast and effective methods are needed for sequencing of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome to track genetic mutations and to identify new and emerging variants during the ongoing pandemic. The objectives were to assess the performance of the SARS-CoV-2 AmpliSeq research panel and S5 plug-in analysis tools for whole-genome sequencing analysis of SARS-CoV-2 and to compare the results with those obtained with the MiSeq-based ARTIC analysis pipeline, using metrics such as depth, coverage, and concordance of single-nucleotide variant (SNV) calls. A total of 191 clinical specimens and a single cultured isolate were extracted and sequenced with AmpliSeq technology and analysis tools. Of the 191 clinical specimens, 83 (with threshold cycle [CT] values of 15.58 to 32.54) were also sequenced using an Illumina MiSeq-based method with the ARTIC analysis pipeline, for direct comparison. A total of 176 of the 191 clinical specimens sequenced on the S5XL system and prepared using the SARS-CoV-2 research panel had nearly complete coverage (>98%) of the viral genome, with an average depth of 5,031×. Similar coverage levels (>98%) were observed for 81/83 primary specimens that were sequenced with both methods tested. The sample with the lowest viral load (CT value of 32.54) achieved 89% coverage using the MiSeq method and failed to sequence with the AmpliSeq method. Consensus sequences produced by each method were identical for 81/82 samples in areas of equal coverage, with a single difference present in one sample. The AmpliSeq approach is as effective as the Illumina-based method using ARTIC v3 amplification for sequencing SARS-CoV-2 directly from patient specimens across a range of viral loads (CT values of 15.56 to 32.54 [median, 22.18]). The AmpliSeq workflow is very easily automated with the Ion Chef and S5 instruments and requires less training and experience with next-generation sequencing sample preparation than the Illumina workflow.

The role of chemical shift magnetic resonance imaging in differentiating osteoporotic benign and malignant vertebral marrow lesions.

PURPOSE: To evaluate the usefulness of chemical shift imaging (CSI) in differentiating benign osteoporotic and malignant vertebral marrow lesions. MATERIAL AND METHODS: Patients undergoing spinal magnetic resonance imaging (MRI) for back pain, which showed altered marrow signal intensity on conventional MRI sequences, were included in the study. Patients with acute traumatic vertebral fractures, infective spondylodiscitis, paravertebral collections, etc. were excluded. The patients underwent CSI. In-phase and opposed-phase images were taken to calculate the signal intensity ratio (SIR) of the abnormal vertebra. The SIR of the mean signal intensity measured on opposed-phase to mean signal intensity measured on in-phase images was measured and recorded. RESULTS: The studied population included 30 patients, in whom 58 vertebrae were accessed, which included 38 dorsal, 18 lumbar, 1 sacral, and 1 cervical. Out of 58 vertebrae, 46 (79%) were malignant and 12 (20%) were benign. The mean CSI/SIR of malignant lesions was 0.96 and the mean SIR of benign lesions was 0.76. CONCLUSIONS: Conventional MRI sequences cannot always differentiate between benign and malignant lesions. So newer sequences like CSI have been developed. CSI SIR can be used as a new tool in differentiating benign osteoporotic and malignant vertebral marrow lesions.

Origin of 3 Rabid Terrestrial Animals in Raccoon Rabies Virus-Free Zone, Long Island, New York, USA, 2016-2017.

During 2016-2017, three rabid terrestrial animals were discovered in the raccoon rabies virus-free zone of Long Island, New York, USA. Whole-genome sequencing and phylogenetic analyses revealed the likely origins of the viruses, enabling the rabies outbreak response (often costly and time-consuming) to be done less expensively and more efficiently.

Impact of Candida auris Infection in a Neutropenic Murine Model.

Candida auris has become a global public health threat due to its multidrug resistance and persistence. Currently, there are limited murine models to study C. auris infection. Those models use a combination of cyclophosphamide and cortisone acetate, suppressing both innate and adaptive immunity. Here, we compare C. auris infection in two neutrophil-depleted murine models in which innate immunity is targeted using the monoclonal antibodies 1A8 and RB6-8C5.

FlavorDB: a database of flavor molecules.

Flavor is an expression of olfactory and gustatory sensations experienced through a multitude of chemical processes triggered by molecules. Beyond their key role in defining taste and smell, flavor molecules also regulate metabolic processes with consequences to health. Such molecules present in natural sources have been an integral part of human history with limited success in attempts to create synthetic alternatives. Given their utility in various spheres of life such as food and fragrances, it is valuable to have a repository of flavor molecules, their natural sources, physicochemical properties, and sensory responses. FlavorDB (http://cosylab.iiitd.edu.in/flavordb) comprises of 25,595 flavor molecules representing an array of tastes and odors. Among these 2254 molecules are associated with 936 natural ingredients belonging to 34 categories. The dynamic, user-friendly interface of the resource facilitates exploration of flavor molecules for divergent applications: finding molecules matching a desired flavor or structure; exploring molecules of an ingredient; discovering novel food pairings; finding the molecular essence of food ingredients; associating chemical features with a flavor and more. Data-driven studies based on FlavorDB can pave the way for an improved understanding of flavor mechanisms.

Whole-Genome Single-Nucleotide Polymorphism (SNP) Analysis Applied Directly to Stool for Genotyping Shiga Toxin-Producing Escherichia coli: an Advanced Molecular Detection Method for Foodborne Disease Surveillance and Outbreak Tracking.

Whole-genome sequencing (WGS) of pathogens from pure culture provides unparalleled accuracy and comprehensive results at a cost that is advantageous compared with traditional diagnostic methods. Sequencing pathogens directly from a primary clinical specimen would help circumvent the need for culture and, in the process, substantially shorten the time to diagnosis and public health reporting. Unfortunately, this approach poses significant challenges because of the mixture of multiple sequences from a complex fecal biomass. The aim of this project was to develop a proof of concept protocol for the sequencing and genotyping of Shiga toxin-producing Escherichia coli (STEC) directly from stool specimens. We have developed an enrichment protocol that reliably achieves a substantially higher DNA yield belonging to E. coli, which provides adequate next-generation sequencing (NGS) data for downstream bioinformatics analysis. A custom bioinformatics pipeline was created to optimize and remove non-E. coli reads, assess the STEC versus commensal E. coli population in the samples, and build consensus sequences based on population allele frequency distributions. Side-by-side analysis of WGS from paired STEC isolates and matched primary stool specimens reveal that this method can reliably be implemented for many clinical specimens to directly genotype STEC and accurately identify clusters of disease outbreak when no STEC isolate is available for testing.

Translational control and Rho-dependent transcription termination are intimately linked in riboswitch regulation.

Riboswitches are regulatory elements that control gene expression by altering RNA structure upon the binding of specific metabolites. Although Bacillus subtilis riboswitches have been shown to control premature transcription termination, less is known about regulatory mechanisms employed by Escherichia coli riboswitches, which are predicted to regulate mostly at the level of translation initiation. Here, we present experimental evidence suggesting that the majority of known E. coli riboswitches control transcription termination by using the Rho transcription factor. In the case of the thiamin pyrophosphate-dependent thiM riboswitch, we find that Rho-dependent transcription termination is triggered as a consequence of translation repression. Using in vitro and in vivo assays, we show that the Rho-mediated regulation relies on RNA target elements located at the beginning of thiM coding region. Gene reporter assays indicate that relocating Rho target elements to a different gene induces transcription termination, demonstrating that such elements are modular domains controlling Rho. Our work provides strong evidence that translationally regulating riboswitches also regulate mRNA levels through an indirect control mechanism ensuring tight control of gene expression.

Candida albicans Elicits Pro-Inflammatory Differential Gene Expression in Intestinal Peyer's Patches.

The details of how gut-associated lymphoid tissues such as Peyer's patches (PPs) in the small intestine play a role in immune surveillance, microbial differentiation and the mucosal barrier protection in response to fungal organisms such as Candida albicans are still unclear. We particularly focus on PPs as they are the immune sensors and inductive sites of the gut that influence inflammation and tolerance. We have previously demonstrated that CD11c+ phagocytes that include dendritic cells and macrophages are located in the sub-epithelial dome within PPs sample C. albicans. To gain insight on how specific cells within PPs sense and respond to the sampling of fungi, we gavaged naïve mice with C. albicans strains ATCC 18804 and SC5314 as well as Saccharomyces cerevisiae. We measured the differential gene expression of sorted CD45+ B220+ B-cells, CD3+ T-cells and CD11c+ DCs within the first 24 h post-gavage using nanostring nCounter® technology. The results reveal that at 24 h, PP phagocytes were the cell type that displayed differential gene expression. These phagocytes were able to sample C. albicans and discriminate between strains. In particular, strain ATCC 18804 upregulated fungal-specific pro-inflammatory genes pertaining to innate and adaptive immune responses. Interestingly, PP CD11c+ phagocytes also differentially expressed genes in response to C. albicans that were important in the protection of the mucosal barrier. These results highlight that the mucosal barrier not only responds to C. albicans, but also aids in the protection of the host.

May-Thurner syndrome: an uncommon and incidental finding in a postpartum female.

May-Thurner syndrome or Cockett syndrome is a pathological condition that arises due to extrinsic compression on iliocaval venous territory, leading to venous outflow obstruction. Here, author presents an incidental finding of left common iliac vein extrinsic compression by right common iliac artery with collateral vessels in the pelvis in a postpartum female.

Protein Engineered Triblock Polymers Composed of Two SADs: Enhanced Mechanical Properties and Binding Abilities.

Recombinant methods have been used to engineer artificial protein triblock polymers composed of two different self-assembling domains (SADs) bearing one elastin (E) flanked by two cartilage oligomeric matrix protein coiled-coil (C) domains to generate CEC. To understand how the two C domains improve small molecule recognition and the mechanical integrity of CEC, we have constructed CL44AECL44A, which bears an impaired CL44A domain that is unstructured as a negative control. The CEC triblock polymer demonstrates increased small molecule binding and ideal elastic behavior for hydrogel formation. The negative control CL44AECL44A does not exhibit binding to small molecule and is inelastic at lower temperatures, affirming the favorable role of C domain and its helical conformation. While both CEC and CL44AECL44A assemble into micelles, CEC is more densely packed with C domains on the surface enabling the development of networks leading to hydrogel formation. Such protein engineered triblock copolymers capable of forming robust hydrogels hold tremendous promise for biomedical applications in drug delivery and tissue engineering.

The Ess1 prolyl isomerase is required for transcription termination of small noncoding RNAs via the Nrd1 pathway.

Genome-wide studies have identified abundant small, noncoding RNAs, including small nuclear RNAs, small nucleolar RNAs (snoRNAs), cryptic unstable transcripts (CUTs), and upstream regulatory RNAs (uRNAs), that are transcribed by RNA polymerase II (pol II) and terminated by an Nrd1-dependent pathway. Here, we show that the prolyl isomerase Ess1 is required for Nrd1-dependent termination of noncoding RNAs. Ess1 binds the carboxy-terminal domain (CTD) of pol II and is thought to regulate transcription by conformational isomerization of Ser-Pro bonds within the CTD. In ess1 mutants, expression of approximately 10% of the genome was altered, due primarily to defects in termination of snoRNAs, CUTs, stable unannotated transcripts, and uRNAs. Ess1 promoted dephosphorylation of Ser5 (but not Ser2) within the CTD, most likely by the Ssu72 phosphatase. We also provide evidence for a competition between Nrd1 and Pcf11 for CTD binding that is regulated by Ess1. These data indicate that a prolyl isomerase is required for specifying the "CTD code."

Self-Trained Convolutional Neural Network (CNN) for Tuberculosis Diagnosis in Medical Imaging.

Background Tuberculosis (TB) is a serious infectious disease that primarily affects the lungs. Despite advancements in the medical industry, TB remains a significant global health challenge. Early and accurate detection of TB is crucial for effective treatment and reducing transmission. This article presents a deep learning approach using convolutional neural networks (CNNs) to improve TB detection in chest X-ray images. Methods For the dataset, we collected 7000 images from Kaggle.com, of which 3500 exhibit tuberculosis evidence and the remaining 3500 are normal. Preprocessing techniques such as wavelet transformation, contrast-limited adaptive histogram equalisation (CLAHE), and gamma correction were applied to enhance the image quality. Random flipping, random rotation, random resizing, and random rescaling were among the techniques employed to increase dataset variability and model robustness. Convolutional, max-pooling, flatten, and dense layers comprised the CNN model architecture. For binary classification, sigmoid activation was utilised in the output layer and rectified linear unit (ReLU) activation in the input and hidden layers. Results The CNN model achieved an accuracy of ~96.57% in detecting TB from chest X-ray images, demonstrating the effectiveness of deep learning, particularly CNNs, in this application. Self-trained CNNs have optimised the results as compared to the transfer learning of various pre-trained models. Conclusion This study shows how well deep learning-in particular, CNNs-performs in the identification of tuberculosis. Subsequent efforts have to give precedence to optimising the model by obtaining more extensive datasets from the local hospitals and localities, which are vulnerable to TB, and stress the possibility of augmenting diagnostic knowledge in medical imaging via machine learning methodologies.

Observational study on the clinical profile and treatment outcome on long-term follow-up of COVID-19 associated mucormycosis.

MATERIALS AND METHODS: Patients diagnosed with COVID-19 associated mucormycosis were followed up for 6 months to study the clinical profile, readmissions, long-term treatment outcome and the mortality rate. RESULTS: Among 37 patients with COVID-19 associated mucormycosis, the mortality rate was 33.3 %, 42.9% and 100 % among patients with mild, moderate and severe COVID-19 infection. One month after discharge, among the 20 patients who survived, 10 (50 %) patients had worsening symptoms and required readmission. Nine patients required readmission for amphotericin and 1 patient was admitted for surgical intervention. On follow-up at 1 month, 30 % (6/20) patients became asymptomatic. However, at 3 months, 45 % (9/20) of the patients were asymptomatic. At 6 months of follow-up, 80 % (16/20) were asymptomatic. At 6 months, one each had residual abnormalities like visual loss in one eye, visual field deficit, change in voice and residual weakness of the limbs along with cranial nerve paresis. CONCLUSION: The follow-up study revealed that a significant number of patients required readmission within the first month, but most of the patients became asymptomatic by 6 months. The readmission rate was higher in patients who received a shorter duration of amphotericin.

Identification and characterization of small RNAs in Yersinia pestis.

Yersinia pestis, the etiologic agent of plague, is closely related to Yersinia pseudotuberculosis evolutionarily but has a very different mode of infection. The RNA-binding regulatory protein, Hfq, mediates regulation by small RNAs (sRNAs) and is required for virulence of both Y. pestis and Y. pseudotuberculosis. Moreover, Hfq is required for growth of Y. pestis, but not Y. pseudotuberculosis, at 37°C. Together, these observations suggest that sRNAs play important roles in the virulence and survival of Y. pestis, and that regulation by sRNAs may account for some of the differences between Y. pestis and Y. pseudotuberculosis. We have used a deep sequencing approach to identify 31 sRNAs in Y. pestis. The majority of these sRNAs are not conserved outside the Yersiniae. Expression of the sRNAs was confirmed by Northern analysis and we developed deep sequencing approaches to map 5' and 3' ends of many sRNAs simultaneously. Expression of the majority of the sRNAs we identified is dependent upon Hfq. We also observed temperature-dependent effects on the expression of many sRNAs, and differences in expression patterns between Y. pestis and Y. pseudotuberculosis. Thus, our data suggest that regulation by sRNAs plays an important role in the lifestyle switch from flea to mammalian host, and that regulation by sRNAs may contribute to the phenotypic differences between Y. pestis and Y. pseudotuberculosis.

Formulation development and optimization of sustained release matrix tablet of Itopride HCl by response surface methodology and its evaluation of release kinetics.

The objective of this present investigation was to develop and formulate sustained release (SR) matrix tablets of Itopride HCl, by using different polymer combinations and fillers, to optimize by Central Composite Design response surface methodology for different drug release variables and to evaluate drug release pattern of the optimized product. Sustained release matrix tablets of various combinations were prepared with cellulose-based polymers: hydroxy propyl methyl cellulose (HPMC) and polyvinyl pyrolidine (pvp) and lactose as fillers. Study of pre-compression and post-compression parameters facilitated the screening of a formulation with best characteristics that underwent here optimization study by response surface methodology (Central Composite Design). The optimized tablet was further subjected to scanning electron microscopy to reveal its release pattern. The in vitro study revealed that combining of HPMC K100M (24.65 MG) with pvp(20 mg)and use of LACTOSE as filler sustained the action more than 12 h. The developed sustained release matrix tablet of improved efficacy can perform therapeutically better than a conventional tablet.

Improved Residual Network based on norm-preservation for visual recognition.

Residual Network (ResNet) achieves deeper and wider networks with high-performance gains, representing a powerful convolutional neural network architecture. In this paper, we propose architectural refinements to ResNet that address the information flow through several layers of the network, including the input stem, downsampling block, projection shortcut, and identity blocks. We will show that our collective refinements facilitate stable backpropagation by preserving the norm of the error gradient within the residual blocks, which can reduce the optimization difficulties of training very deep networks. Our proposed modifications enhance the learning dynamics, resulting in high accuracy and inference performance by enforcing norm-preservation throughout the network training. The effectiveness of our method is verified by extensive experimental results on five computer vision tasks, including image classification (ImageNet and CIFAR-100), video classification (Kinetics-400), multi-label image recognition (MS-COCO), object detection and semantic segmentation (PASCAL VOC). We also empirically show consistent improvements in generalization performance when applying our modifications over different networks to provide new insights and inspire new architectures. The source code is publicly available at: https://github.com/bharatmahaur/LeNo.