The Challenge Non-Typhoidal Salmonella (CHANTS) Consortium: Development of a non-typhoidal Salmonella controlled human infection model: Report from a consultation group workshop, 05 July 2022, London, UK [version 2; peer review: 2 approved]

Invasive non-typhoidal Salmonella disease (iNTS) is a major cause of morbidity and mortality globally, particularly as a cause of bloodstream infection in children and immunocompromised adults in sub-Saharan Africa. Vaccines to prevent non-typhoidal Salmonella (NTS) would represent a valuable public health tool in this setting to avert cases and prevent expansion of antimicrobial resistance. Several NTS and combination typhoidal-NTS vaccine candidates are in early-stage development, although the pathway to licensure is unclear due to challenges in conducting large phase III field trials. Controlled human infection models (CHIM) present an opportunity to accelerate vaccine development for a range of enteric pathogens. Several recent typhoidal Salmonella CHIMs have been conducted safely and have played pivotal roles in progressing vaccine candidates to pre-qualification and licensure. The Challenge Non-Typhoidal Salmonella (CHANTS) consortium has been formed with funding from the Wellcome Trust, to deliver the first NTS CHIM, which can act as a platform for future vaccine evaluation. This paper reports the conclusions of a consultation group workshop convened with key stakeholders. The aims of this meeting were to: (1) define the rationale for an NTS CHIM (2) map the NTS vaccine pipeline (3) refine study design and (4) establish potential future use cases

GIVE: portable genome browsers for personal websites.

Growing popularity and diversity of genomic data demand portable and versatile genome browsers. Here, we present an open source programming library called GIVE that facilitates the creation of personalized genome browsers without requiring a system administrator. By inserting HTML tags, one can add to a personal webpage interactive visualization of multiple types of genomics data, including genome annotation, "linear" quantitative data, and genome interaction data. GIVE includes a graphical interface called HUG (HTML Universal Generator) that automatically generates HTML code for displaying user chosen data, which can be copy-pasted into user's personal website or saved and shared with collaborators. GIVE is available at: https://www.givengine.org/

Regional differences in recombination hotspots between two chicken populations

<p>Abstract</p> <p>Background</p> <p>Although several genetic linkage maps of the chicken genome have been published, the resolution of these maps is limited and does not allow the precise identification of recombination hotspots. The availability of more than 3.2 million SNPs in the chicken genome and the recent advances in high throughput genotyping techniques enabled us to increase marker density for the construction of a high-resolution linkage map of the chicken genome. This high-resolution linkage map allowed us to study recombination hotspots across the genome between two chicken populations: a purebred broiler line and a broiler × broiler cross. In total, 1,619 animals from the two different broiler populations were genotyped with 17,790 SNPs.</p> <p>Results</p> <p>The resulting linkage map comprises 13,340 SNPs. Although 360 polymorphic SNPs that had not been assigned to a known chromosome on chicken genome build WASHUC2 were included in this study, no new linkage groups were found. The resulting linkage map is composed of 31 linkage groups, with a total length of 3,054 cM for the sex-average map of the combined population. The sex-average linkage map of the purebred broiler line is 686 cM smaller than the linkage map of the broiler × broiler cross.</p> <p>Conclusions</p> <p>In this study, we present a linkage map of the chicken genome at a substantially higher resolution than previously published linkage maps. Regional differences in recombination hotspots between the two mapping populations were observed in several chromosomes near the telomere of the p arm; the sex-specific analysis revealed that these regional differences were mainly caused by female-specific recombination hotspots in the broiler × broiler cross.</p

Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell carcinoma: insights from the TRACERx Renal study

BACKGROUND: The aim of this work is to evaluate the performance of radiomics predictions for a range of molecular, genomic and clinical targets in patients with clear cell renal cell carcinoma (ccRCC) and demonstrate the impact of novel feature selection strategies and sub-segmentations on model interpretability. METHODS: Contrast-enhanced CT scans from the first 101 patients recruited to the TRACERx Renal Cancer study (NCT03226886) were used to derive radiomics classification models to predict 20 molecular, histopathology and clinical target variables. Manual 3D segmentation was used in conjunction with automatic sub-segmentation to generate radiomics features from the core, rim, high and low enhancing sub-regions, and the whole tumour. Comparisons were made between two classification model pipelines: a Conventional pipeline reflecting common radiomics practice, and a Proposed pipeline including two novel feature selection steps designed to improve model interpretability. For both pipelines nested cross-validation was used to estimate prediction performance and tune model hyper-parameters, and permutation testing was used to evaluate the statistical significance of the estimated performance measures. Further model robustness assessments were conducted by evaluating model variability across the cross-validation folds. RESULTS: Classification performance was significant (p  0.1. Five of these targets (necrosis on histology, presence of renal vein invasion, overall histological stage, linear evolutionary subtype and loss of 9p21.3 somatic alteration marker) had AUROC > 0.8. Models derived using the Proposed pipeline contained fewer feature groups than the Conventional pipeline, leading to more straightforward model interpretations without loss of performance. Sub-segmentations lead to improved performance and/or improved interpretability when predicting the presence of sarcomatoid differentiation and tumour stage. CONCLUSIONS: Use of the Proposed pipeline, which includes the novel feature selection methods, leads to more interpretable models without compromising prediction performance. TRIAL REGISTRATION: NCT03226886 (TRACERx Renal

Genome-wide linkage analysis of 972 bipolar pedigrees using single-nucleotide polymorphisms.

Because of the high costs associated with ascertainment of families, most linkage studies of Bipolar I disorder (BPI) have used relatively small samples. Moreover, the genetic information content reported in most studies has been less than 0.6. Although microsatellite markers spaced every 10 cM typically extract most of the genetic information content for larger multiplex families, they can be less informative for smaller pedigrees especially for affected sib pair kindreds. For these reasons we collaborated to pool family resources and carried out higher density genotyping. Approximately 1100 pedigrees of European ancestry were initially selected for study and were genotyped by the Center for Inherited Disease Research using the Illumina Linkage Panel 12 set of 6090 single-nucleotide polymorphisms. Of the ~1100 families, 972 were informative for further analyses, and mean information content was 0.86 after pruning for linkage disequilibrium. The 972 kindreds include 2284 cases of BPI disorder, 498 individuals with bipolar II disorder (BPII) and 702 subjects with recurrent major depression. Three affection status models (ASMs) were considered: ASM1 (BPI and schizoaffective disorder, BP cases (SABP) only), ASM2 (ASM1 cases plus BPII) and ASM3 (ASM2 cases plus recurrent major depression). Both parametric and non-parametric linkage methods were carried out. The strongest findings occurred at 6q21 (non-parametric pairs LOD 3.4 for rs1046943 at 119 cM) and 9q21 (non-parametric pairs logarithm of odds (LOD) 3.4 for rs722642 at 78 cM) using only BPI and schizoaffective (SA), BP cases. Both results met genome-wide significant criteria, although neither was significant after correction for multiple analyses. We also inspected parametric scores for the larger multiplex families to identify possible rare susceptibility loci. In this analysis, we observed 59 parametric LODs of 2 or greater, many of which are likely to be close to maximum possible scores. Although some linkage findings may be false positives, the results could help prioritize the search for rare variants using whole exome or genome sequencing

Novel and de novo PKD1 mutations identified by multiple restriction fragment-single strand conformation polymorphism (MRF-SSCP)

BACKGROUND: We have previously developed a long RT-PCR method for selective amplification of full-length PKD1 transcripts (13.6 kb) and a long-range PCR for amplification in the reiterated region (18 kb) covering exons 14 and 34 of the PKD1 gene. These have provided us with an opportunity to study PKD1 mutations especially in its reiterated region which is difficult to examine. In this report, we have further developed the method of multiple restriction fragment-single strand conformation polymorphism (MRF-SSCP) for analysis of PKD1 mutations in the patients with autosomal dominant polycystic kidney disease (ADPKD). Novel and de novo PKD1 mutations are identified and reported. METHODS: Full-length PKD1 cDNA isolated from the patients with ADPKD was fractionated into nine overlapping segments by nested-PCR. Each segment was digested with sets of combined restriction endonucleases before the SSCP analysis. The fragments with aberrant migration were mapped, isolated, and sequenced. The presence of mutation was confirmed by the long-range genomic DNA amplification in the PKD1 region, sequencing, direct mutation detection, and segregation analysis in the affected family. RESULTS: Five PKD1 mutations identified are two frameshift mutations caused by two di-nucleotide (c. 5225_5226delAG and c.9451_9452delAT) deletions, a nonsense (Q1828X, c.5693C>T) mutation, a splicing defect attributable to 31 nucleotide deletion (g.33184_33214del31), and an in-frame deletion (L3287del, c.10070_10072delCTC). All mutations occurred within the reiterated region of the gene involving exons 15, 26, 15, 19 and 29, respectively. Three mutations (one frameshift, splicing defect, and in-frame deletion) are novel and two (one frameshift and nonsense) known. In addition, two mutations (nonsense and splicing defect) are possibly de novo. CONCLUSION: The MRF-SSCP method has been developed to analyze PCR products generated by the long RT-PCR and nested-PCR technique for screening PKD1 mutations in the full-length cDNA. Five mutations identified were all in the reiterated region of this gene, three of which were novel. The presence of de novo PKD1 mutations indicates that this gene is prone to mutations

Efficient counting of k-mers in DNA sequences using a bloom filter

<p>Abstract</p> <p>Background</p> <p>Counting <it>k</it>-mers (substrings of length <it>k </it>in DNA sequence data) is an essential component of many methods in bioinformatics, including for genome and transcriptome assembly, for metagenomic sequencing, and for error correction of sequence reads. Although simple in principle, counting <it>k</it>-mers in large modern sequence data sets can easily overwhelm the memory capacity of standard computers. In current data sets, a large fraction-often more than 50%-of the storage capacity may be spent on storing <it>k</it>-mers that contain sequencing errors and which are typically observed only a single time in the data. These singleton <it>k</it>-mers are uninformative for many algorithms without some kind of error correction.</p> <p>Results</p> <p>We present a new method that identifies all the <it>k</it>-mers that occur more than once in a DNA sequence data set. Our method does this using a Bloom filter, a probabilistic data structure that stores all the observed <it>k</it>-mers implicitly in memory with greatly reduced memory requirements. We then make a second sweep through the data to provide exact counts of all nonunique <it>k</it>-mers. For example data sets, we report up to 50% savings in memory usage compared to current software, with modest costs in computational speed. This approach may reduce memory requirements for any algorithm that starts by counting <it>k</it>-mers in sequence data with errors.</p> <p>Conclusions</p> <p>A reference implementation for this methodology, BFCounter, is written in C++ and is GPL licensed. It is available for free download at <url>http://pritch.bsd.uchicago.edu/bfcounter.html</url></p

Differential analysis for high density tiling microarray data

<p>Abstract</p> <p>Background</p> <p>High density oligonucleotide tiling arrays are an effective and powerful platform for conducting unbiased genome-wide studies. The <it>ab initio </it>probe selection method employed in tiling arrays is unbiased, and thus ensures consistent sampling across coding and non-coding regions of the genome. These arrays are being increasingly used to study the associated processes of transcription, transcription factor binding, chromatin structure and their association. Studies of differential expression and/or regulation provide critical insight into the mechanics of transcription and regulation that occurs during the developmental program of a cell. The time-course experiment, which comprises an <it>in-vivo </it>system and the proposed analyses, is used to determine if annotated and un-annotated portions of genome manifest coordinated differential response to the induced developmental program.</p> <p>Results</p> <p>We have proposed a novel approach, based on a piece-wise function – to analyze genome-wide differential response. This enables segmentation of the response based on protein-coding and non-coding regions; for genes the methodology also partitions differential response with a 5' versus 3' versus intra-genic bias.</p> <p>Conclusion</p> <p>The algorithm built upon the framework of Significance Analysis of Microarrays, uses a generalized logic to define regions/patterns of coordinated differential change. By not adhering to the gene-centric paradigm, discordant differential expression patterns between exons and introns have been identified at a FDR of less than 12 percent. A co-localization of differential binding between RNA Polymerase II and tetra-acetylated histone has been quantified at a p-value < 0.003; it is most significant at the 5' end of genes, at a p-value < 10^-13. The prototype R code has been made available as supplementary material [see Additional file <supplr sid="S1">1</supplr>].</p> <suppl id="S1"> <title> <p>Additional file 1</p> </title> <text> <p>gsam_prototypercode.zip. File archive comprising of prototype R code for gSAM implementation including readme and examples.</p> </text> <file name="1471-2105-8-359-S1.zip"> <p>Click here for file</p> </file> </suppl

Symbionts as Major Modulators of Insect Health: Lactic Acid Bacteria and Honeybees

Lactic acid bacteria (LAB) are well recognized beneficial host-associated members of the microbiota of humans and animals. Yet LAB-associations of invertebrates have been poorly characterized and their functions remain obscure. Here we show that honeybees possess an abundant, diverse and ancient LAB microbiota in their honey crop with beneficial effects for bee health, defending them against microbial threats. Our studies of LAB in all extant honeybee species plus related apid bees reveal one of the largest collections of novel species from the genera Lactobacillus and Bifidobacterium ever discovered within a single insect and suggest a long (>80 mya) history of association. Bee associated microbiotas highlight Lactobacillus kunkeei as the dominant LAB member. Those showing potent antimicrobial properties are acquired by callow honey bee workers from nestmates and maintained within the crop in biofilms, though beekeeping management practices can negatively impact this microbiota. Prophylactic practices that enhance LAB, or supplementary feeding of LAB, may serve in integrated approaches to sustainable pollinator service provision. We anticipate this microbiota will become central to studies on honeybee health, including colony collapse disorder, and act as an exemplar case of insect-microbe symbiosis

Monitoring indirect impact of COVID-19 pandemic on services for cardiovascular diseases in the UK.

OBJECTIVE: To monitor hospital activity for presentation, diagnosis and treatment of cardiovascular diseases during the COVID-19) pandemic to inform on indirect effects. METHODS: Retrospective serial cross-sectional study in nine UK hospitals using hospital activity data from 28 October 2019 (pre-COVID-19) to 10 May 2020 (pre-easing of lockdown) and for the same weeks during 2018-2019. We analysed aggregate data for selected cardiovascular diseases before and during the epidemic. We produced an online visualisation tool to enable near real-time monitoring of trends. RESULTS: Across nine hospitals, total admissions and emergency department (ED) attendances decreased after lockdown (23 March 2020) by 57.9% (57.1%-58.6%) and 52.9% (52.2%-53.5%), respectively, compared with the previous year. Activity for cardiac, cerebrovascular and other vascular conditions started to decline 1-2 weeks before lockdown and fell by 31%-88% after lockdown, with the greatest reductions observed for coronary artery bypass grafts, carotid endarterectomy, aortic aneurysm repair and peripheral arterial disease procedures. Compared with before the first UK COVID-19 (31 January 2020), activity declined across diseases and specialties between the first case and lockdown (total ED attendances relative reduction (RR) 0.94, 0.93-0.95; total hospital admissions RR 0.96, 0.95-0.97) and after lockdown (attendances RR 0.63, 0.62-0.64; admissions RR 0.59, 0.57-0.60). There was limited recovery towards usual levels of some activities from mid-April 2020. CONCLUSIONS: Substantial reductions in total and cardiovascular activities are likely to contribute to a major burden of indirect effects of the pandemic, suggesting they should be monitored and mitigated urgently