Ensembl 2018

Pathway-based integration of multi-omics data reveals lipidomics alterations validated in an Alzheimer's disease mouse model and risk loci carriers

Alzheimer's disease (AD) is a highly prevalent neurodegenerative disorder. Despite increasing evidence of the importance of metabolic dysregulation in AD, the underlying metabolic changes that may impact amyloid plaque formation are not understood, particularly for late-onset AD. This study analyzed genome-wide association studies (GWAS), transcriptomics, and proteomics data obtained from several data repositories to obtain differentially expressed (DE) multi-omics elements in mouse models of AD. We characterized the metabolic modulation in these data sets using gene ontology, transcription factor, pathway, and cell-type enrichment analyses. A predicted lipid signature was extracted from genome-scale metabolic networks (GSMN) and subsequently validated in a lipidomic data set derived from cortical tissue of ABCA-7 null mice, a mouse model of one of the genes associated with late-onset AD. Moreover, a metabolome-wide association study (MWAS) was performed to further characterize the association between dysregulated lipid metabolism in human blood serum and genes associated with AD risk. We found 203 DE transcripts, 164 DE proteins, and 58 DE GWAS-derived mouse orthologs associated with significantly enriched metabolic biological processes. Lipid and bioenergetic metabolic pathways were significantly over-represented across the AD multi-omics data sets. Microglia and astrocytes were significantly enriched in the lipid-predominant AD-metabolic transcriptome. We also extracted a predicted lipid signature that was validated and robustly modeled class separation in the ABCA7 mice cortical lipidome, with 11 of these lipid species exhibiting statistically significant modulations. MWAS revealed 298 AD single nucleotide polymorphisms-metabolite associations, of which 70% corresponded to lipid classes. These results support the importance of lipid metabolism dysregulation in AD and highlight the suitability of mapping AD multi-omics data into GSMNs to identify metabolic alterations.

TNFRSF13B in B cell responses to organ transplantation

Antibodies directed against organ transplants are thought to pose the most vexing hurdle to enduring function and survival of the transplants, particularly organ xenotransplants, and accordingly basic and clinical investigation has focused on elucidating the specificity and pathogenicity of graft-specific antibodies. While much has been learned about these matters, far less is known about the B cells producing graft-specific antibodies and why these antibodies appear to injure some grafts but not others. With the goal of addressing those questions, we have investigated the properties of tumor necrosis factor receptor super family-13B (TNFRSF13B), which regulates various aspects of B cell responses. A full understanding of the functions of TNFRSF13B however is hindered by extreme polymorphism and by diversity of interactions of the protein. Nevertheless, TNFRSF13B variants have been found to exert distinct impact on natural and elicited antibody responses and host defense and mutations of TNFRSF13B have been found to influence the propensity for development of antibody-mediated rejection of organ transplants. Because B cell responses potentially limit application of xenotransplantation, understanding how TNFRSF13B diversity and TNFRSF13B variants govern immunity in xenotransplantation could inspire development of novel therapeutics that could in turn accelerate clinical implementation of xenotransplantation.

Characterization of a novel sRNA contributing to biofilm formation in Salmonella enterica serovar Typhimurium

Small RNAs (sRNAs) are short noncoding RNAs of ~50-200 nucleotides believed to primarily function in regulating crucial activities in bacteria during periods of cellular stress. This study examined the relevance of specific sRNAs on biofilm formation in nutrient starved Salmonella enterica serovar Typhimurium. Eight unique sRNAs were selected for deletion primarily based on their genomic location and/or putative targets. Quantitative and qualitative analyses confirm one of these, sRNA1186573, is required for efficient biofilm formation in S. enterica further highlighting the significance of sRNAs during Salmonella stress response.

Application of data fusion modeling for the prediction of auxin response elements in Zea mays for food security purposes

Food security will be affected by climate change worldwide, particularly in the developingworld, where the most important food products originate from plants. Plants are often exposed to environmental stresses that may affect their growth, development, yield, and foodquality. Auxin is a hormone that plays a critical role in improving plants' tolerance of environmental conditions. Auxin controls the expression of many stress-responsive genes inplants by interacting with specific cis-regulatory elements called auxin-responsive elements (AuxREs). In this work, we performed an in silico prediction of AuxREs in promotersof five auxin-responsive genes in Zea mays. We applied a data fusion approach based onthe combined use of Dempster-Shafer evidence theory and fuzzy sets. Auxin has a directimpact on cell membrane proteins. The short-term auxin response may be represented bythe regulation of transmembrane gene expression. The detection of an AuxRE in the promoter of prolyl oligopeptidase (POP) in Z. mays and the 3-fold overexpression of this geneunder auxin treatment for 30 min indicated the role of POP in maize auxin response. POP isregulated by auxin to perform stress adaptation. In addition, the detection of two AuxRETGTCTC motifs in the upstream sequence of the bx1 gene suggests that bx1 can be regulated by auxin. Auxin may also be involved in the regulation of dehydration-responsive element-binding and some members of the protein kinase superfamily.

Asteroid: a new algorithm to infer species trees from gene trees under high proportions of missing data

MOTIVATION

Missing data and incomplete lineage sorting (ILS) are two major obstacles to accurate species tree inference. Gene tree summary methods such as ASTRAL and ASTRID have been developed to account for ILS. However, they can be severely affected by high levels of missing data.

RESULTS

We present Asteroid, a novel algorithm that infers an unrooted species tree from a set of unrooted gene trees. We show on both empirical and simulated datasets that Asteroid is substantially more accurate than ASTRAL and ASTRID for very high proportions (>80%) of missing data. Asteroid is several orders of magnitude faster than ASTRAL for datasets that contain thousands of genes. It offers advanced features such as parallelization, support value computation and support for multi-copy and multifurcating gene trees.

AVAILABILITY AND IMPLEMENTATION

Asteroid is freely available at https://github.com/BenoitMorel/Asteroid.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

In Silico Structural Analysis Predicting the Pathogenicity of PLP1 Mutations in Multiple Sclerosis

The X chromosome gene PLP1 encodes myelin proteolipid protein (PLP), the most prevalent protein in the myelin sheath surrounding the central nervous system. X-linked dysmyelinating disorders such as Pelizaeus-Merzbacher disease (PMD) or spastic paraplegia type 2 (SPG2) are typically caused by point mutations in PLP1. Nevertheless, numerous case reports have shown individuals with PLP1 missense point mutations which also presented clinical symptoms and indications that were consistent with the diagnostic criteria of multiple sclerosis (MS), a disabling disease of the brain and spinal cord with no current cure. Computational structural biology methods were used to assess the impact of these mutations on the stability and flexibility of PLP structure in order to determine the role of PLP1 mutations in MS pathogenicity. The analysis showed that most of the variants can alter the functionality of the protein structure such as R137W variants which results in loss of helix and H140Y which alters the ordered protein interface. In silico genomic methods were also performed to predict the significance of these mutations associated with impairments in protein functionality and could suggest a better definition for therapeutic strategies and clinical application in MS patients.

Muscle Regeneration in Holothurians without the Upregulation of Muscle Genes

The holothurian Eupentacta fraudatrix is capable of fully restoring its muscles after transverse dissection. Although the regeneration of these structures is well studied at the cellular level, the molecular basis of the process remains poorly understood. To identify genes that may be involved in the regulation of muscle regeneration, the transcriptome of the longitudinal muscle band of E. fraudatrix has been sequenced at different time periods post-injury. An analysis of the map of biological processes and pathways has shown that most genes associated with myogenesis decrease their expression during the regeneration. The only exception is the genes united by the GO term "heart valve development". This may indicate the antiquity of mechanisms of mesodermal structure transformation, which was co-opted into various morphogeneses in deuterostomes. Two groups of genes that play a key role in the regeneration have been analyzed: transcription factors and matrix metalloproteinases. A total of six transcription factor genes (Ef-HOX5, Ef-ZEB2, Ef-RARB, Ef-RUNX1, Ef-SOX17, and Ef-ZNF318) and seven matrix metalloproteinase genes (Ef-MMP11, Ef-MMP13, Ef-MMP13-1, Ef-MMP16-2, Ef-MMP16-3, Ef-MMP24, and Ef-MMP24-1) showing differential expression during myogenesis have been revealed. The identified genes are assumed to be involved in the muscle regeneration in holothurians.

A novel compound heterozygous BEST1 gene mutation in two siblings causing autosomal recessive bestrophinopathy

PURPOSE

To describe the clinical features, imaging characteristics, and genetic test results associated with a novel compound heterozygous mutation of the BEST1 gene in two siblings with autosomal recessive bestrophinopathy.

METHODS

Two siblings underwent a complete ophthalmic examination, including dilated fundus examination, fundus photography, fundus autofluorescence imaging, spectral-domain optical coherence tomography, fluorescein angiography, electroretinography, and electrooculography. A clinical diagnosis of autosomal recessive bestrophinopathy was established based on ocular examination and multimodal retinal imaging. Subsequently, clinical exome sequencing consisting of a panel of 6670 genes was carried out to confirm the diagnosis and assess genetic alterations in the protein-coding region of the genome of the patients. The identified mutations were tested in the two affected siblings and one of their parents.

RESULTS

Two siblings (a 17-year-old female and a 15-year-old male) presented with reduced visual acuity and bilaterally symmetrical subretinal deposits of hyperautofluorescent materials in the posterior pole, which showed staining in the late phase of fluorescein angiogram. Spectral-domain optical coherence tomography demonstrated hyperreflective subretinal deposits and subretinal fluid accumulation. Both patients shared two mutations in the protein-coding region of the BEST1 gene, c.103G > A, p.(Glu35Lys) and c.313C > A, p.(Arg105Ser) (a novel disease-causing mutation). Sanger sequencing confirmed that the unaffected mother of the proband was carrying p.(Glu35Lys) variant in a heterozygous state.

CONCLUSIONS

We have identified and described the phenotype of a novel disease-causing mutation NM_004183.4:c.313C > A, p.(Arg105Ser) in a heterozygous state along with a previously reported mutation NM_004183.4:c.103G > A, p.(Glu35Lys) of the BEST1 gene in two related patients with autosomal recessive bestrophinopathy.

A Revised Perspective on the Evolution of Troponin I and Troponin T Gene Families in Vertebrates

The troponin (Tn) complex, responsible for the Ca2+ activation of striated muscle, is composed of three interacting protein subunits: TnC, TnI, and TnT, encoded by TNNC, TNNI, and TNNT genes. TNNI and TNNT are sister gene families, and in mammals the three TNNI paralogs (TNNI1, TNNI2, TNNI3), which encode proteins with tissue-specific expression, are each in close genomic proximity with one of the three TNNT paralogs (TNNT2, TNNT3, TNNT1, respectively). It has been widely presumed that all vertebrates broadly possess genes of these same three classes, although earlier work has overlooked jawless fishes (cyclostomes) and cartilaginous fishes (chimeras, rays, and sharks), which are distantly related to other jawed vertebrates. With a new phylogenetic and synteny analysis of a diverse array of vertebrates including these taxonomic groups, we define five distinct TNNI classes (TNNI1-5), with TNNI4 and TNNI5 being only present in non-amniote vertebrates and typically found in tandem, and four classes of TNNT (TNNT1-4). These genes are located in four genomic loci that were generated by the 2R whole-genome duplications. TNNI3, encoding "cardiac TnI" in tetrapods, was independently lost in cartilaginous and ray-finned fishes. Instead, ray-finned fishes predominantly express TNNI1 in the heart. TNNI5 is highly expressed in shark hearts and contains a N-terminal extension similar to that of TNNI3 found in tetrapod hearts. Given that TNNI3 and TNNI5 are distantly related, this supports the hypothesis that the N-terminal extension may be an ancestral feature of vertebrate TNNI and not an innovation unique to TNNI3, as has been commonly believed.

LncRNA weighted gene co-expression network analysis reveals novel biomarkers related to prostate cancer metastasis

BACKGROUND

Most prostate cancer patients die from metastasis and lack accurate efficacious biomarkers to monitor the disease behavior, optimize treatment and assess prognosis. Herein, we aimed to identify meaningful lncRNA biomarkers associated with prostate cancer metastatic progression.

METHODS

By repurposing microarray probes, 11,624 lncRNAs in prostate cancer were obtained from Gene Expression Omnibus  database (GSE46691, N = 545; GSE29079, N = 235; GSE94767, N = 130). Weighted gene co-expression network analysis was applied to determine the co-expression lncRNA network pertinent to metastasis. Hub lncRNAs were screened. RNA-seq and clinical data from the Cancer Genome Atlas prostate cancer (TCGA-PRAD) cohort (N = 531) were analyzed. Transwell assay and bioinformatic analysis were performed for mechanism research.

RESULTS

The high expression levels of nine hub lncRNAs (FTX, AC005261.1, NORAD, LINC01578, AC004542.2, ZFAS1, EBLN3P, THUMPD3-AS1, GAS5) were significantly associated with Gleason score and increased probability of metastatic progression. Among these lncRNAs, ZFAS1 had the consistent trends of expression in all of the analysis from different cohorts, and the Kaplan-Meier survival analyses showed higher expression of ZFAS1 was associated with shorter relapse free survival. In-vitro studies confirmed that downregulation of ZFAS1 decreased prostate cancer cell migration.

CONCLUSION

We offered some new insights into discovering lncRNA markers correlated with metastatic progression of prostate cancer using the WGCNA. Some may serve as potential prognostic biomarkers and therapeutic targets for advanced metastatic prostate cancer.

DeepTSS: multi-branch convolutional neural network for transcription start site identification from CAGE data

BACKGROUND

The widespread usage of Cap Analysis of Gene Expression (CAGE) has led to numerous breakthroughs in understanding the transcription mechanisms. Recent evidence in the literature, however, suggests that CAGE suffers from transcriptional and technical noise. Regardless of the sample quality, there is a significant number of CAGE peaks that are not associated with transcription initiation events. This type of signal is typically attributed to technical noise and more frequently to random five-prime capping or transcription bioproducts. Thus, the need for computational methods emerges, that can accurately increase the signal-to-noise ratio in CAGE data, resulting in error-free transcription start site (TSS) annotation and quantification of regulatory region usage. In this study, we present DeepTSS, a novel computational method for processing CAGE samples, that combines genomic signal processing (GSP), structural DNA features, evolutionary conservation evidence and raw DNA sequence with Deep Learning (DL) to provide single-nucleotide TSS predictions with unprecedented levels of performance.

RESULTS

To evaluate DeepTSS, we utilized experimental data, protein-coding gene annotations and computationally-derived genome segmentations by chromatin states. DeepTSS was found to outperform existing algorithms on all benchmarks, achieving 98% precision and 96% sensitivity (accuracy 95.4%) on the protein-coding gene strategy, with 96.66% of its positive predictions overlapping active chromatin, 98.27% and 92.04% co-localized with at least one transcription factor and H3K4me3 peak.

CONCLUSIONS

CAGE is a key protocol in deciphering the language of transcription, however, as every experimental protocol, it suffers from biological and technical noise that can severely affect downstream analyses. DeepTSS is a novel DL-based method for effectively removing noisy CAGE signal. In contrast to existing software, DeepTSS does not require feature selection since the embedded convolutional layers can readily identify patterns and only utilize the important ones for the classification task. This study highlights the key role that DL can play in Molecular Biology, by removing the inherent flaws of experimental protocols, that form the backbone of contemporary research. Here, we show how DeepTSS can unleash the full potential of an already popular and mature method such as CAGE, and push the boundaries of coding and non-coding gene expression regulator research even further.

Freddie: annotation-independent detection and discovery of transcriptomic alternative splicing isoforms using long-read sequencing

Alternative splicing (AS) is an important mechanism in the development of many cancers, as novel or aberrant AS patterns play an important role as an independent onco-driver. In addition, cancer-specific AS is potentially an effective target of personalized cancer therapeutics. However, detecting AS events remains a challenging task, especially if these AS events are novel. This is exacerbated by the fact that existing transcriptome annotation databases are far from being comprehensive, especially with regard to cancer-specific AS. Additionally, traditional sequencing technologies are severely limited by the short length of the generated reads, which rarely spans more than a single splice junction site. Given these challenges, transcriptomic long-read (LR) sequencing presents a promising potential for the detection and discovery of AS. We present Freddie, a computational annotation-independent isoform discovery and detection tool. Freddie takes as input transcriptomic LR sequencing of a sample alongside its genomic split alignment and computes a set of isoforms for the given sample. It then partitions the input reads into sets that can be processed independently and in parallel. For each partition, Freddie segments the genomic alignment of the reads into canonical exon segments. The goal of this segmentation is to be able to represent any potential isoform as a subset of these canonical exons. This segmentation is formulated as an optimization problem and is solved with a dynamic programming algorithm. Then, Freddie reconstructs the isoforms by jointly clustering and error-correcting the reads using the canonical segmentation as a succinct representation. The clustering and error-correcting step is formulated as an optimization problem-the Minimum Error Clustering into Isoforms (MErCi) problem-and is solved using integer linear programming (ILP). We compare the performance of Freddie on simulated datasets with other isoform detection tools with varying dependence on annotation databases. We show that Freddie outperforms the other tools in its accuracy, including those given the complete ground truth annotation. We also run Freddie on a transcriptomic LR dataset generated in-house from a prostate cancer cell line with a matched short-read RNA-seq dataset. Freddie results in isoforms with a higher short-read cross-validation rate than the other tested tools. Freddie is open source and available at https://github.com/vpc-ccg/freddie/.

Investigation of MicroRNA Biomarkers in Equine Distal Interphalangeal Joint Osteoarthritis

Osteoarthritis of the equine distal interphalangeal joint is a common cause of lameness. MicroRNAs from biofluids are promising biomarkers and therapeutic candidates. Synovial fluid samples from horses with mild and severe equine distal interphalangeal joint osteoarthritis were submitted for small RNA sequencing. The results demonstrated that miR-92a was downregulated in equine synovial fluid from horses with severe osteoarthritis and there was a significant increase in COMP, COL1A2, RUNX2 and SOX9 following miR-92a mimic treatment of equine chondrocytes in monolayer culture. This is the first equine study to evaluate the role of miR-92a in osteoarthritic chondrocytes in vitro.

Human iPSC-hepatocyte modeling of alpha-1 antitrypsin heterozygosity reveals metabolic dysregulation and cellular heterogeneity

Individuals homozygous for the "Z" mutation in alpha-1 antitrypsin deficiency are known to be at increased risk for liver disease. It has also become clear that some degree of risk is similarly conferred by the heterozygous state. A lack of model systems that recapitulate heterozygosity in human hepatocytes has limited the ability to study the impact of a single Z alpha-1 antitrypsin (ZAAT) allele on hepatocyte biology. Here, we describe the derivation of syngeneic induced pluripotent stem cells (iPSCs) engineered to determine the effects of ZAAT heterozygosity in iPSC-hepatocytes (iHeps). We find that heterozygous MZ iHeps exhibit an intermediate disease phenotype and share with ZZ iHeps alterations in AAT protein processing and downstream perturbations including altered endoplasmic reticulum (ER) and mitochondrial morphology, reduced mitochondrial respiration, and branch-specific activation of the unfolded protein response in cell subpopulations. Our model of MZ heterozygosity thus provides evidence that a single Z allele is sufficient to disrupt hepatocyte homeostatic function.

SPiP: Splicing Prediction Pipeline, a machine learning tool for massive detection of exonic and intronic variant effects on mRNA splicing

Modeling splicing is essential for tackling the challenge of variant interpretation as each nucleotide variation can be pathogenic by affecting pre-mRNA splicing via disruption/creation of splicing motifs such as 5'/3' splice sites, branch sites, or splicing regulatory elements. Unfortunately, most in silico tools focus on a specific type of splicing motif, which is why we developed the Splicing Prediction Pipeline (SPiP) to perform, in one single bioinformatic analysis based on a machine learning approach, a comprehensive assessment of the variant effect on different splicing motifs. We gathered a curated set of 4616 variants scattered all along the sequence of 227 genes, with their corresponding splicing studies. The Bayesian analysis provided us with the number of control variants, that is, variants without impact on splicing, to mimic the deluge of variants from high-throughput sequencing data. Results show that SPiP can deal with the diversity of splicing alterations, with 83.13% sensitivity and 99% specificity to detect spliceogenic variants. Overall performance as measured by area under the receiving operator curve was 0.986, better than SpliceAI and SQUIRLS (0.965 and 0.766) for the same data set. SPiP lends itself to a unique suite for comprehensive prediction of spliceogenicity in the genomic medicine era. SPiP is available at: https://sourceforge.net/projects/splicing-prediction-pipeline/.

Tissue-Specific Human Extracellular Matrix Scaffolds Promote Pancreatic Tumour Progression and Chemotherapy Resistance

Over 80% of patients with pancreatic ductal adenocarcinoma (PDAC) are diagnosed at a late stage and are locally advanced or with concurrent metastases. The aggressive phenotype and relative chemo- and radiotherapeutic resistance of PDAC is thought to be mediated largely by its prominent stroma, which is supported by an extracellular matrix (ECM). Therefore, we investigated the impact of tissue-matched human ECM in driving PDAC and the role of the ECM in promoting chemotherapy resistance. Decellularized human pancreata and livers were recellularized with PANC-1 and MIA PaCa-2 (PDAC cell lines), as well as PK-1 cells (liver-derived metastatic PDAC cell line). PANC-1 cells migrated into the pancreatic scaffolds, MIA PaCa-2 cells were able to migrate into both scaffolds, whereas PK-1 cells were able to migrate into the liver scaffolds only. These differences were supported by significant deregulations in gene and protein expression between the pancreas scaffolds, liver scaffolds, and 2D culture. Moreover, these cell lines were significantly more resistant to gemcitabine and doxorubicin chemotherapy treatments in the 3D models compared to 2D cultures, even after confirmed uptake by confocal microscopy. These results suggest that tissue-specific ECM provides the preserved native cues for primary and metastatic PDAC cells necessary for a more reliable in vitro cell culture.

Mercaptopurine induced myelosuppression in a child with a NUDT15 rs116855232 homozygous variant

Introduction

Mercaptopurine (6-MP) is the backbone of the consolidation and maintenance therapy for paediatric acute lymphoblastic leukaemia (ALL). Nevertheless, it can cause critical myelosuppression. Predicting adverse reactions to 6-MP often involves the investigation of pharmacogenetic variants; in particular thiopurine S-methyltransferase ( TPMT) and nudix hydrolase 15 ( NUDT15). Lately, NUDT15 variants have been shown to play a significant pharmacogenetic role in predicting 6-MP intolerance in children of Asian descent.

Case Report

We present a six-year-old male child of Indian origin with persistent cytopenia after treatment. This prompted targeted sequencing of the genes TPMT and NUD15. The results revealed two copies of the variant of NUD15 rs116855232, that is, NUDT15*2 genotype.

Management and Outcome

Since the NUDT15*2 allele classified the patient as a poor metabolizer, he was restarted on a low dose of 6-MP, which he tolerated.

Discussion

Individuals with the NUDT15*2allele (*2/*2 genotype) are poor metabolizers of thiopurines which results in an adverse reaction to 6-MP. About 3.5% of Indians show variations in the TPMT gene as compared to 19.4% variations observed in NUDT15, which makes the latter a more reliable disease marker.

Unified methods in collecting, preserving, and archiving coral bleaching and restoration specimens to increase sample utility and interdisciplinary collaboration

Coral reefs are declining worldwide primarily because of bleaching and subsequent mortality resulting from thermal stress. Currently, extensive efforts to engage in more holistic research and restoration endeavors have considerably expanded the techniques applied to examine coral samples. Despite such advances, coral bleaching and restoration studies are often conducted within a specific disciplinary focus, where specimens are collected, preserved, and archived in ways that are not always conducive to further downstream analyses by specialists in other disciplines. This approach may prevent the full utilization of unexpended specimens, leading to siloed research, duplicative efforts, unnecessary loss of additional corals to research endeavors, and overall increased costs. A recent US National Science Foundation-sponsored workshop set out to consolidate our collective knowledge across the disciplines of Omics, Physiology, and Microscopy and Imaging regarding the methods used for coral sample collection, preservation, and archiving. Here, we highlight knowledge gaps and propose some simple steps for collecting, preserving, and archiving coral-bleaching specimens that can increase the impact of individual coral bleaching and restoration studies, as well as foster additional analyses and future discoveries through collaboration. Rapid freezing of samples in liquid nitrogen or placing at -80 °C to -20 °C is optimal for most Omics and Physiology studies with a few exceptions; however, freezing samples removes the potential for many Microscopy and Imaging-based analyses due to the alteration of tissue integrity during freezing. For Microscopy and Imaging, samples are best stored in aldehydes. The use of sterile gloves and receptacles during collection supports the downstream analysis of host-associated bacterial and viral communities which are particularly germane to disease and restoration efforts. Across all disciplines, the use of aseptic techniques during collection, preservation, and archiving maximizes the research potential of coral specimens and allows for the greatest number of possible downstream analyses.

Sensitisation of cancer cells to radiotherapy by serine and glycine starvation

BACKGROUND

Cellular metabolism is an integral component of cellular adaptation to stress, playing a pivotal role in the resistance of cancer cells to various treatment modalities, including radiotherapy. In response to radiotherapy, cancer cells engage antioxidant and DNA repair mechanisms which mitigate and remove DNA damage, facilitating cancer cell survival. Given the reliance of these resistance mechanisms on amino acid metabolism, we hypothesised that controlling the exogenous availability of the non-essential amino acids serine and glycine would radiosensitise cancer cells.

METHODS

We exposed colorectal, breast and pancreatic cancer cell lines/organoids to radiation in vitro and in vivo in the presence and absence of exogenous serine and glycine. We performed phenotypic assays for DNA damage, cell cycle, ROS levels and cell death, combined with a high-resolution untargeted LCMS metabolomics and RNA-Seq.

RESULTS

Serine and glycine restriction sensitised a range of cancer cell lines, patient-derived organoids and syngeneic mouse tumour models to radiotherapy. Comprehensive metabolomic and transcriptomic analysis of central carbon metabolism revealed that amino acid restriction impacted not only antioxidant response and nucleotide synthesis but had a marked inhibitory effect on the TCA cycle.

CONCLUSION

Dietary restriction of serine and glycine is a viable radio-sensitisation strategy in cancer.

Molecular evaluation of gene mutation profiles and copy number variations in pediatric acute myeloid leukemia

BACKGROUND

The objectives of this study were to investigate the mutation profiles of targeted genes and copy number variations (CNVs) in normal cytogenetics (CN) pediatric acute myeloid leukemia (AML).

METHODS

This prospective study was conducted from October 2018 to December 2020. The next-generation sequencing (NGS) and chromosomal microarray analyses (CMA) were performed in pediatric CN-AML patients.

RESULTS

Out of 94 children (aged ≤18 years), 70 patients with AML (24 excluded) underwent conventional karyotyping/cytogenetic analyses. Forty-five (64.3%) of patients had abnormal/ recurrent cytogenetic abnormalities and 25 (35.7%) had normal cytogenetics. Twenty-three out of 25 CN-AML were further processed for gene mutation profile and CNVs using NGS and CMA, respectively. Twenty-two out of 23 (95.7%) patients were detected to have mutations in various genes. The common mutations were: NRAS, NPM1, CEBPA, KRAS, KIT, RUNX1, NOTCH1, WT1, GATA1, GATA2, FLT3, KMT2D, FLT3-TKD, and PHF6. Copy number variations (CNVs) were detected in nine patients (39%), and eight (34.8%) had a long contiguous stretch of homozygosity (LCSH) /loss of heterozygosity (LOH). An LCSH was detected on chromosomes 5, 7, 11, and 19. The gains were more common than losses (8 vs 2). The gains were observed on chromosomes 8, 9, 14, 19, 21, and 22, and the losses were detected on chromosomes 7 and 10. Monosomy was observed in three patients. Three patients (monosomy7, n = 2, and FLT-ITD, n = 1) were reclassified into the high-risk category. Post-induction, complete remission was achieved in all evaluable patients.

CONCLUSION

CN-AML patients have genetic abnormalities that can be detected by more advanced techniques like NGS and CMA. These genetic abnormalities play a role in risk stratification that may remain hidden in otherwise CN-AML.

Early-life farm exposures and eczema among adults in the Agricultural Lung Health Study

Background

Several studies conducted in Europe have suggested a protective association between early-life farming exposures and childhood eczema or atopic dermatitis; few studies have examined associations in adults.

Objectives

To investigate associations between early-life exposures and eczema among 3217 adult farmers and farm spouses (mean age 62.8 years) in a case-control study nested within an US agricultural cohort.

Methods

We used sampling-weighted logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (95%CIs) for associations between early-life exposures and self-reported doctor-diagnosed eczema (273 cases) and polytomous logistic regression to estimate ORs (95%CIs) for a 4-level outcome combining information on eczema and atopy (specific IgE≥0.35). Additionally, we explored genetic and gene-environment associations with eczema.

Results

Although early-life farming exposures were not associated with eczema overall, several early-life exposures were associated with a reduced risk of having both eczema and atopy. Notably, results suggest stronger protective associations among individuals with both eczema and atopy than among those with either atopy alone or eczema alone. For example, ORs (95%CIs) for having a mother who did farm work while pregnant were 1.01 (0.60-1.69) for eczema alone and 0.80 (0.65-0.99) for atopy alone, but 0.54 (0.33-0.80) for having both eczema and atopy. A genetic risk score based on previously identified atopic dermatitis variants was strongly positively associated with eczema, and interaction testing suggested protective effects of several early-life farming exposures only in individuals at lower genetic risk.

Conclusions

In utero and childhood farming exposures are associated with decreased odds of having eczema with atopy in adults.

Postnatal state transition of cardiomyocyte as a primary step in heart maturation

Postnatal heart maturation is the basis of normal cardiac function and provides critical insights into heart repair and regenerative medicine. While static snapshots of the maturing heart have provided much insight into its molecular signatures, few key events during postnatal cardiomyocyte maturation have been uncovered. Here, we report that cardiomyocytes (CMs) experience epigenetic and transcriptional decline of cardiac gene expression immediately after birth, leading to a transition state of CMs at postnatal day 7 (P7) that was essential for CM subtype specification during heart maturation. Large-scale single-cell analysis and genetic lineage tracing confirm the presence of transition state CMs at P7 bridging immature state and mature states. Silencing of key transcription factor JUN in P1-hearts significantly repressed CM transition, resulting in perturbed CM subtype proportions and reduced cardiac function in mature hearts. In addition, transplantation of P7-CMs into infarcted hearts exhibited cardiac repair potential superior to P1-CMs. Collectively, our data uncover CM state transition as a key event in postnatal heart maturation, which not only provides insights into molecular foundations of heart maturation, but also opens an avenue for manipulation of cardiomyocyte fate in disease and regenerative medicine.

Monoclonal Antibody Sequence Variants Disguised as Fragments: Identification, Characterization, and Their Removal by Purification Process Optimization

During early stage development of a therapeutic IgG1 monoclonal antibody, high levels of low molecular weight (LMW) peaks were observed by high performance size-exclusion chromatography and capillary electrophoresis. Further characterization of the LMW peak enriched HPSEC fractions using reversed phase liquid chromatography coupled to mass spectrometry showed these LMW species were 47 kDa and 50 kDa in size. However, the measured masses could not be matched to any fragments resulting from peptide bond hydrolysis. To identify these unknown LMW species, molecular characterization methods were employed, including high-throughput sequencing of RNA. Transcriptomic analysis revealed the LMW species were generated by mis-splicing events in the heavy chain transcript, which produced truncated heavy chain products that assembled with the light chain to mimic the appearance of fragments identified by routine purity assays. In an effort to improve product quality, an optimized purification process was developed. Characterization of the process intermediates confirmed removal of both LMW species by the optimized process. Our study demonstrates that deep-dive analytical characterization of biotherapeutics is critical to ensure product quality and inform process development. Transcriptomic analysis tools can help identify the cause of unknown species, and plays a key role in product and process characterization.

Follistatin-like 1 and its paralogs in heart development and cardiovascular disease

Cardiovascular diseases (CVDs) are a group of disorders affecting the heart and blood vessels and a leading cause of death worldwide. Thus, there is a need to identify new cardiokines that may protect the heart from damage as reported in GBD 2017 Causes of Death Collaborators (2018) (The Lancet 392:1736-1788). Follistatin-like 1 (FSTL1) is a cardiokine that is highly expressed in the heart and released to the serum after cardiac injury where it is associated with CVD and predicts poor outcome. The action of FSTL1 likely depends not only on the tissue source but also post-translation modifications that are target tissue- and cell-specific. Animal studies examining the effect of FSTL1 in various models of heart disease have exploded over the past 15 years and primarily report a protective effect spanning from inhibiting inflammation via transforming growth factor, preventing remodeling and fibrosis to promoting angiogenesis and hypertrophy. A better understanding of FSTL1 and its homologs is needed to determine whether this protein could be a useful novel biomarker to predict poor outcome and death and whether it has therapeutic potential. The aim of this review is to provide a comprehensive description of the literature for this family of proteins in order to better understand their role in normal physiology and CVD.

Plant Age and Soil Texture Rather Than the Presence of Root Hairs Cause Differences in Maize Resource Allocation and Root Gene Expression in the Field

Understanding the biological roles of root hairs is key to projecting their contributions to plant growth and to assess their relevance for plant breeding. The objective of this study was to assess the importance of root hairs for maize nutrition, carbon allocation and root gene expression in a field experiment. Applying wild type and root hairless rth3 maize grown on loam and sand, we examined the period of growth including 4-leaf, 9-leaf and tassel emergence stages, accompanied with a low precipitation rate. rth3 maize had lower shoot growth and lower total amounts of mineral nutrients than wild type, but the concentrations of mineral elements, root gene expression, or carbon allocation were largely unchanged. For these parameters, growth stage accounted for the main differences, followed by substrate. Substrate-related changes were pronounced during tassel emergence, where the concentrations of several elements in leaves as well as cell wall formation-related root gene expression and C allocation decreased. In conclusion, the presence of root hairs stimulated maize shoot growth and total nutrient uptake, but other parameters were more impacted by growth stage and soil texture. Further research should relate root hair functioning to the observed losses in maize productivity and growth efficiency.

HSV-1 and influenza infection induce linear and circular splicing of the long NEAT1 isoform

The herpes simplex virus 1 (HSV-1) virion host shut-off (vhs) protein cleaves both cellular and viral mRNAs by a translation-initiation-dependent mechanism, which should spare circular RNAs (circRNAs). Here, we show that vhs-mediated degradation of linear mRNAs leads to an enrichment of circRNAs relative to linear mRNAs during HSV-1 infection. This was also observed in influenza A virus (IAV) infection, likely due to degradation of linear host mRNAs mediated by the IAV PA-X protein and cap-snatching RNA-dependent RNA polymerase. For most circRNAs, enrichment was not due to increased circRNA synthesis but due to a general loss of linear RNAs. In contrast, biogenesis of a circRNA originating from the long isoform (NEAT1_2) of the nuclear paraspeckle assembly transcript 1 (NEAT1) was induced both in HSV-1 infection-in a vhs-independent manner-and in IAV infection. This was associated with induction of novel linear splicing of NEAT1_2 both within and downstream of the circRNA. NEAT1_2 forms a scaffold for paraspeckles, nuclear bodies located in the interchromatin space, must likely remain unspliced for paraspeckle assembly and is up-regulated in HSV-1 and IAV infection. We show that NEAT1_2 splicing and up-regulation can be induced by ectopic co-expression of the HSV-1 immediate-early proteins ICP22 and ICP27, potentially linking increased expression and splicing of NEAT1_2. To identify other conditions with NEAT1_2 splicing, we performed a large-scale screen of published RNA-seq data. This uncovered both induction of NEAT1_2 splicing and poly(A) read-through similar to HSV-1 and IAV infection in cancer cells upon inhibition or knockdown of CDK7 or the MED1 subunit of the Mediator complex phosphorylated by CDK7. In summary, our study reveals induction of novel circular and linear NEAT1_2 splicing isoforms as a common characteristic of HSV-1 and IAV infection and highlights a potential role of CDK7 in HSV-1 or IAV infection.

An automatic hypothesis generation for plausible linkage between xanthium and diabetes

There has been a significant increase in text mining implementation for biomedical literature in recent years. Previous studies introduced the implementation of text mining and literature-based discovery to generate hypotheses of potential candidates for drug development. By conducting a hypothesis-generation step and using evidence from published journal articles or proceedings, previous studies have managed to reduce experimental time and costs. First, we applied the closed discovery approach from Swanson's ABC model to collect publications related to 36 Xanthium compounds or diabetes. Second, we extracted biomedical entities and relations using a knowledge extraction engine, the Public Knowledge Discovery Engine for Java or PKDE4J. Third, we built a knowledge graph using the obtained bio entities and relations and then generated paths with Xanthium compounds as source nodes and diabetes as the target node. Lastly, we employed graph embeddings to rank each path and evaluated the results based on domain experts' opinions and literature. Among 36 Xanthium compounds, 35 had direct paths to five diabetes-related nodes. We ranked 2,740,314 paths in total between 35 Xanthium compounds and three diabetes-related phrases: type 1 diabetes, type 2 diabetes, and diabetes mellitus. Based on the top five percentile paths, we concluded that adenosine, choline, beta-sitosterol, rhamnose, and scopoletin were potential candidates for diabetes drug development using natural products. Our framework for hypothesis generation employs a closed discovery from Swanson's ABC model that has proven very helpful in discovering biological linkages between bio entities. The PKDE4J tools we used to capture bio entities from our document collection could label entities into five categories: genes, compounds, phenotypes, biological processes, and molecular functions. Using the BioPREP model, we managed to interpret the semantic relatedness between two nodes and provided paths containing valuable hypotheses. Lastly, using a graph-embedding algorithm in our path-ranking analysis, we exploited the semantic relatedness while preserving the graph structure properties.

The relationship of mRNA with protein expression in CD8+ T cells associates with gene class and gene characteristics

T cells are key players in our defence against infections and malignancies. When T cells differentiate or become activated, they undergo substantial alterations in gene expression. Even though RNA expression levels are now well documented throughout different stages of T cells, it is not well understood how mRNA expression translates into the protein landscape. By combining paired RNA sequencing and mass spectrometry data of primary human CD8+ T cells, we report that mRNA expression is a poor proxy for the overall protein output, irrespective of the differentiation or activation status. Yet, gene class stratification revealed a function-specific correlation of mRNA with protein expression. This gene class-specific expression pattern associated with differences in gene characteristics such as sequence conservation and untranslated region (UTR) lengths. In addition, the presence of AU-rich elements in the 3'UTR associated with alterations in mRNA and protein abundance T cell activation dependent, gene class-specific manner. In conclusion, our study highlights the role of gene characteristics as a determinant for gene expression in T cells.

Lateral confined growth of cells activates Lef1 dependent pathways to regulate cell-state transitions

Long-term sustained mechano-chemical signals in tissue microenvironment regulate cell-state transitions. In recent work, we showed that laterally confined growth of fibroblasts induce dedifferentiation programs. However, the molecular mechanisms underlying such mechanically induced cell-state transitions are poorly understood. In this paper, we identify Lef1 as a critical somatic transcription factor for the mechanical regulation of de-differentiation pathways. Network optimization methods applied to time-lapse RNA-seq data identify Lef1 dependent signaling as potential regulators of such cell-state transitions. We show that Lef1 knockdown results in the down-regulation of fibroblast de-differentiation and that Lef1 directly interacts with the promoter regions of downstream reprogramming factors. We also evaluate the potential upstream activation pathways of Lef1, including the Smad4, Atf2, NFkB and Beta-catenin pathways, thereby identifying that Smad4 and Atf2 may be critical for Lef1 activation. Collectively, we describe an important mechanotransduction pathway, including Lef1, which upon activation, through progressive lateral cell confinement, results in fibroblast de-differentiation.

A transcriptomic analysis of the effects of macrophage polarization and endotoxin tolerance on the response to Salmonella

Salmonella is an intracellular pathogen causing significant morbidity and mortality. Its ability to grow inside macrophages is important to virulence, and is dependent on the activation state of the macrophages. Classically activated M1 macrophages are non-permissive for Salmonella growth, while alternatively activated M2 macrophages are permissive for Salmonella growth. Here we showed that endotoxin-primed macrophages (MEP), such as those associated with sepsis, showed similar levels of Salmonella resistance to M1 macrophages after 2 hr of intracellular infection, but at the 4 hr and 24 hr time points were susceptible like M2 macrophages. To understand this mechanistically, transcriptomic sequencing, RNA-Seq, was performed. This showed that M1 and MEP macrophages that had not been exposed to Salmonella, demonstrated a process termed here as primed activation, in expressing relatively higher levels of particular anti-infective genes and pathways, including the JAK-STAT (Janus kinase-signal transducer and activator of transcription) pathway. In contrast, in M2 macrophages these genes and pathways were largely expressed only in response to infection. Conversely, in response to infection, M1 macrophages, but not MEP macrophages, modulated additional genes known to be associated with susceptibility to Salmonella infection, possibly contributing to the differences in resistance at later time points. Application of the JAK inhibitor Ruxolitinib before infection reduced resistance in M1 macrophages, supporting the importance of early JAK-STAT signalling in M1 resistance to Salmonella.

EnsembleSplice: ensemble deep learning model for splice site prediction

BACKGROUND

Identifying splice site regions is an important step in the genomic DNA sequencing pipelines of biomedical and pharmaceutical research. Within this research purview, efficient and accurate splice site detection is highly desirable, and a variety of computational models have been developed toward this end. Neural network architectures have recently been shown to outperform classical machine learning approaches for the task of splice site prediction. Despite these advances, there is still considerable potential for improvement, especially regarding model prediction accuracy, and error rate.

RESULTS

Given these deficits, we propose EnsembleSplice, an ensemble learning architecture made up of four (4) distinct convolutional neural networks (CNN) model architecture combination that outperform existing splice site detection methods in the experimental evaluation metrics considered including the accuracies and error rates. We trained and tested a variety of ensembles made up of CNNs and DNNs using the five-fold cross-validation method to identify the model that performed the best across the evaluation and diversity metrics. As a result, we developed our diverse and highly effective splice site (SS) detection model, which we evaluated using two (2) genomic Homo sapiens datasets and the Arabidopsis thaliana dataset. The results showed that for of the Homo sapiens EnsembleSplice achieved accuracies of 94.16% for one of the acceptor splice sites and 95.97% for donor splice sites, with an error rate for the same Homo sapiens dataset, 4.03% for the donor splice sites and 5.84% for the acceptor splice sites datasets.

CONCLUSIONS

Our five-fold cross validation ensured the prediction accuracy of our models are consistent. For reproducibility, all the datasets used, models generated, and results in our work are publicly available in our GitHub repository here: https://github.com/OluwadareLab/EnsembleSplice.

A novel heterozygous mutation in the hydroxymethylbilane synthase gene in a case with acute intermittent porphyria

Porphyrias are rare metabolic disorders caused by inherited or acquired enzymatic defects in the heme biosynthetic pathway. They are grouped into acute hepatic porphyrias and photocutaneous porphyrias. Acute intermittent porphyria, the most prevalent subtype of acute hepatic porphyrias, is caused by a mutation in the hydroxymethylbilane synthase gene. In this work, a case of a 13 year-old Indian female presenting with multi-organ involvement (Neurological: episodic seizures, behavioral abnormalities, acute onset progressive flaccid-motor quadriparesis, multiple cranial nerve palsies, respiratory paralysis, dysautonomia, and posterior reversible encephalopathy syndrome; Gastrointestinal: recurrent attacks of abdominal pain, nausea/vomiting, isolated transaminitis, and acute pancreatitis; and Renal: metabolic alkalosis and refractory dyselectrolytemia) which resulted in significant diagnostic dilemmas. She was eventually diagnosed as a case of acute intermittent porphyria harboring a novel hydroxymethylbilane synthase gene mutation (p.Arg173Trp).

Genome Wide Association Study with Imputed Whole Genome Sequence Data Identifies a 431 kb Risk Haplotype on CFA18 for Congenital Laryngeal Paralysis in Alaskan Sled Dogs

Congenital laryngeal paralysis (CLP) is an inherited disorder that affects the ability of the dog to exercise and precludes it from functioning as a working sled dog. Though CLP is known to occur in Alaskan sled dogs (ASDs) since 1986, the genetic mutation underlying the disease has not been reported. Using a genome-wide association study (GWAS), we identified a 708 kb region on CFA 18 harboring 226 SNPs to be significantly associated with CLP. The significant SNPs explained 47.06% of the heritability of CLP. We narrowed the region to 431 kb through autozygosity mapping and found 18 of the 20 cases to be homozygous for the risk haplotype. Whole genome sequencing of two cases and a control ASD, and comparison with the genome of 657 dogs from various breeds, confirmed the homozygous status of the risk haplotype to be unique to the CLP cases. Most of the dogs that were homozygous for the risk allele had blue eyes. Gene annotation and a gene-based association study showed that the risk haplotype encompasses genes implicated in developmental and neurodegenerative disorders. Pathway analysis showed enrichment of glycoproteins and glycosaminoglycans biosynthesis, which play a key role in repairing damaged nerves. In conclusion, our results suggest an important role for the identified candidate region in CLP.

Robust Genetic Analysis of the X-Linked Anophthalmic (Ie) Mouse

Anophthalmia (missing eye) describes a failure of early embryonic ocular development. Mutations in a relatively small set of genes account for 75% of bilateral anophthalmia cases, yet 25% of families currently are left without a molecular diagnosis. Here, we report our experimental work that aimed to uncover the developmental and genetic basis of the anophthalmia characterising the X-linked Ie (eye-ear reduction) X-ray-induced allele in mouse that was first identified in 1947. Histological analysis of the embryonic phenotype showed failure of normal eye development after the optic vesicle stage with particularly severe malformation of the ventral retina. Linkage analysis mapped this mutation to a ~6 Mb region on the X chromosome. Short- and long-read whole-genome sequencing (WGS) of affected and unaffected male littermates confirmed the Ie linkage but identified no plausible causative variants or structural rearrangements. These analyses did reduce the critical candidate interval and revealed evidence of multiple variants within the ancestral DNA, although none were found that altered coding sequences or that were unique to Ie. To investigate early embryonic events at a genetic level, we then generated mouse ES cells derived from male Ie embryos and wild type littermates. RNA-seq and accessible chromatin sequencing (ATAC-seq) data generated from cultured optic vesicle organoids did not reveal any large differences in gene expression or accessibility of putative cis-regulatory elements between Ie and wild type. However, an unbiased TF-footprinting analysis of accessible chromatin regions did provide evidence of a genome-wide reduction in binding of transcription factors associated with ventral eye development in Ie, and evidence of an increase in binding of the Zic-family of transcription factors, including Zic3, which is located within the Ie-refined critical interval. We conclude that the refined Ie critical region at chrX: 56,145,000-58,385,000 contains multiple genetic variants that may be linked to altered cis regulation but does not contain a convincing causative mutation. Changes in the binding of key transcription factors to chromatin causing altered gene expression during development, possibly through a subtle mis-regulation of Zic3, presents a plausible cause for the anophthalmia phenotype observed in Ie, but further work is required to determine the precise causative allele and its genetic mechanism.

CC Genotype of GNAS c.393C>T (rs7121) Polymorphism Has a Protective Effect against Development of BK Viremia and BKV-Associated Nephropathy after Renal Transplant

The GNAS gene encodes the alpha-subunit of the stimulatory G-protein (Gαs) in humans and mice. The single-nucleotide polymorphism of GNAS, c.393C>T, is associated with an elevated production of Gαs and an increased formation of cyclic adenosine monophosphate (cAMP). In the present study, we analyzed the effect of this GNAS polymorphism on a renal allograft outcome. We screened a cohort of 436 renal allograft recipients, who were retrospectively followed up for up to 5 years after transplant. GNAS genotypes were determined with polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) assays. The 393T allele was detected in 319 (73%) recipients (113 recipients with TT and 206 with CT genotype) and the CC genotype in 117 (27%). The CC genotype was associated with a significantly lower frequency of BK viremia (CC, 17 recipients (15%); T 84 (26%)); p = 0.01; TT, 27 vs. CC, 17, p = 0.07; TT, 27 vs. CT, 57, p = 0. 46; CT, 57 vs. CC, 17, p = 0.01) and BKV-associated nephropathy (CC, 3 recipients (3%); T, 27 (8%); p = 0.03; TT,10 vs. CC, 3, p = 0.04; TT, 10 vs. CT,17, p = 0.85; CT, 17 vs. CC,3, p = 0.04) after transplant. BKV-associated nephropathy-free survival was significantly better among CC genotype carriers than among T allele carriers (p = 0.043; TT vs. CC, p = 0.03; CT vs. CC, p = 0.04; TT vs. CT, p = 0.83). Multivariate analysis indicated an independent protective effect of the CC genotype against the development of both BK viremia (relative risk. 0.54; p = 0.04) and BKV-associated nephropathy after renal transplant (relative risk. 0.27; p = 0.036). The GNAS 393 CC genotype seems to protect renal allograft recipients against the development of BK viremia and BKV-associated nephropathy.

PD-1 combination therapy with IL-2 modifies CD8+ T cell exhaustion program

Combination therapy with PD-1 blockade and IL-2 is highly effective during chronic lymphocytic choriomeningitis virus infection1. Here we examine the underlying basis for this synergy. We show that PD-1 + IL-2 combination therapy, in contrast to PD-1 monotherapy, substantially changes the differentiation program of the PD-1+TCF1+ stem-like CD8+ T cells and results in the generation of transcriptionally and epigenetically distinct effector CD8+ T cells that resemble highly functional effector CD8+ T cells seen after an acute viral infection. The generation of these qualitatively superior CD8+ T cells that mediate viral control underlies the synergy between PD-1 and IL-2. Our results show that the PD-1+TCF1+ stem-like CD8+ T cells, also referred to as precursors of exhausted CD8+ T cells, are not fate-locked into the exhaustion program and their differentiation trajectory can be changed by IL-2 signals. These virus-specific effector CD8+ T cells emerging from the stem-like CD8+ T cells after combination therapy expressed increased levels of the high-affinity IL-2 trimeric (CD25-CD122-CD132) receptor. This was not seen after PD-1 blockade alone. Finally, we show that CD25 engagement with IL-2 has an important role in the observed synergy between IL-2 cytokine and PD-1 blockade. Either blocking CD25 with an antibody or using a mutated version of IL-2 that does not bind to CD25 but still binds to CD122 and CD132 almost completely abrogated the synergistic effects observed after PD-1 + IL-2 combination therapy. There is considerable interest in PD-1 + IL-2 combination therapy for patients with cancer2,3, and our fundamental studies defining the underlying mechanisms of how IL-2 synergizes with PD-1 blockade should inform these human translational studies.

Genomic data integration and user-defined sample-set extraction for population variant analysis

BACKGROUND

Population variant analysis is of great importance for gathering insights into the links between human genotype and phenotype. The 1000 Genomes Project established a valuable reference for human genetic variation; however, the integrative use of the corresponding data with other datasets within existing repositories and pipelines is not fully supported. Particularly, there is a pressing need for flexible and fast selection of population partitions based on their variant and metadata-related characteristics.

RESULTS

Here, we target general germline or somatic mutation data sources for their seamless inclusion within an interoperable-format repository, supporting integration among them and with other genomic data, as well as their integrated use within bioinformatic workflows. In addition, we provide VarSum, a data summarization service working on sub-populations of interest selected using filters on population metadata and/or variant characteristics. The service is developed as an optimized computational framework with an Application Programming Interface (API) that can be called from within any existing computing pipeline or programming script. Provided example use cases of biological interest show the relevance, power and ease of use of the API functionalities.

CONCLUSIONS

The proposed data integration pipeline and data set extraction and summarization API pave the way for solid computational infrastructures that quickly process cumbersome variation data, and allow biologists and bioinformaticians to easily perform scalable analysis on user-defined partitions of large cohorts from increasingly available genetic variation studies. With the current tendency to large (cross)nation-wide sequencing and variation initiatives, we expect an ever growing need for the kind of computational support hereby proposed.

Deep sequencing of short capped RNAs reveals novel families of noncoding RNAs

In eukaryotes, capped RNAs include long transcripts such as messenger RNAs and long noncoding RNAs, as well as shorter transcripts such as spliceosomal RNAs, small nucleolar RNAs, and enhancer RNAs. Long capped transcripts can be profiled using cap analysis gene expression (CAGE) sequencing and other methods. Here, we describe a sequencing library preparation protocol for short capped RNAs, apply it to a differentiation time course of the human cell line THP-1, and systematically compare the landscape of short capped RNAs to that of long capped RNAs. Transcription initiation peaks associated with genes in the sense direction have a strong preference to produce either long or short capped RNAs, with one out of six peaks detected in the short capped RNA libraries only. Gene-associated short capped RNAs have highly specific 3' ends, typically overlapping splice sites. Enhancers also preferentially generate either short or long capped RNAs, with 10% of enhancers observed in the short capped RNA libraries only. Enhancers producing either short or long capped RNAs show enrichment for GWAS-associated disease SNPs. We conclude that deep sequencing of short capped RNAs reveals new families of noncoding RNAs and elucidates the diversity of transcripts generated at known and novel promoters and enhancers.

Airway basal cells show a dedifferentiated KRT17highPhenotype and promote fibrosis in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a fatal disease with limited treatment options. In this study, we focus on the properties of airway basal cells (ABC) obtained from patients with IPF (IPF-ABC). Single cell RNA sequencing (scRNAseq) of bronchial brushes revealed extensive reprogramming of IPF-ABC towards a KRT17high PTENlow dedifferentiated cell type. In the 3D organoid model, compared to ABC obtained from healthy volunteers, IPF-ABC give rise to more bronchospheres, de novo bronchial structures resembling lung developmental processes, induce fibroblast proliferation and extracellular matrix deposition in co-culture. Intratracheal application of IPF-ABC into minimally injured lungs of Rag2-/- or NRG mice causes severe fibrosis, remodeling of the alveolar compartment, and formation of honeycomb cyst-like structures. Connectivity MAP analysis of scRNAseq of bronchial brushings suggested that gene expression changes in IPF-ABC can be reversed by SRC inhibition. After demonstrating enhanced SRC expression and activity in these cells, and in IPF lungs, we tested the effects of saracatinib, a potent SRC inhibitor previously studied in humans. We demonstrate that saracatinib modified in-vitro and in-vivo the profibrotic changes observed in our 3D culture system and novel mouse xenograft model.

The role of extracellular vesicle miRNAs and tRNAs in synovial fibroblast senescence

Extracellular vesicles are mediators of intercellular communication with critical roles in cellular senescence and ageing. In arthritis, senescence is linked to the activation of a pro-inflammatory phenotype contributing to chronic arthritis pathogenesis. We hypothesised that senescent osteoarthritic synovial fibroblasts induce senescence and a pro-inflammatory phenotype in non-senescent osteoarthritic fibroblasts, mediated through extracellular vesicle cargo. Small RNA-sequencing and mass spectrometry proteomics were performed on extracellular vesicles isolated from the secretome of non-senescent and irradiation-induced senescent synovial fibroblasts. β-galactosidase staining confirmed senescence in SFs. RNA sequencing identified 17 differentially expressed miRNAs, 11 lncRNAs, 14 tRNAs and one snoRNA and, 21 differentially abundant proteins were identified by mass spectrometry. Bioinformatics analysis of miRNAs identified fibrosis, cell proliferation, autophagy, and cell cycle as significant pathways, tRNA analysis was enriched for signaling pathways including FGF, PI3K/AKT and MAPK, whilst protein analysis identified PAX3-FOXO1, MYC and TFGB1 as enriched upstream regulators involved in senescence and cell cycle arrest. Finally, treatment of non-senescent synovial fibroblasts with senescent extracellular vesicles confirmed the bystander effect, inducing senescence in non-senescent cells potentially through down regulation of NF-κβ and cAMP response element signaling pathways thus supporting our hypothesis. Understanding the exact composition of EV-derived small RNAs of senescent cells in this way will inform our understanding of their roles in inflammation, intercellular communication, and as active molecules in the senescence bystander effect.

The RNA-Binding Landscape of HAX1 Protein Indicates Its Involvement in Translation and Ribosome Assembly

HAX1 is a human protein with no known homologues or structural domains. Mutations in the HAX1 gene cause severe congenital neutropenia through mechanisms that are poorly understood. Previous studies reported the RNA-binding capacity of HAX1, but the role of this binding in physiology and pathology remains unexplained. Here, we report the transcriptome-wide characterization of HAX1 RNA targets using RIP-seq and CRAC, indicating that HAX1 binds transcripts involved in translation, ribosome biogenesis, and rRNA processing. Using CRISPR knockouts, we find that HAX1 RNA targets partially overlap with transcripts downregulated in HAX1 KO, implying a role in mRNA stabilization. Gene ontology analysis demonstrated that genes differentially expressed in HAX1 KO (including genes involved in ribosome biogenesis and translation) are also enriched in a subset of genes whose expression correlates with HAX1 expression in four analyzed neoplasms. The functional connection to ribosome biogenesis was also demonstrated by gradient sedimentation ribosome profiles, which revealed differences in the small subunit:monosome ratio in HAX1 WT/KO. We speculate that changes in HAX1 expression may be important for the etiology of HAX1-linked diseases through dysregulation of translation.

Spatio-temporal analysis of prostate tumors in situ suggests pre-existence of treatment-resistant clones

The molecular mechanisms underlying lethal castration-resistant prostate cancer remain poorly understood, with intratumoral heterogeneity a likely contributing factor. To examine the temporal aspects of resistance, we analyze tumor heterogeneity in needle biopsies collected before and after treatment with androgen deprivation therapy. By doing so, we are able to couple clinical responsiveness and morphological information such as Gleason score to transcriptome-wide data. Our data-driven analysis of transcriptomes identifies several distinct intratumoral cell populations, characterized by their unique gene expression profiles. Certain cell populations present before treatment exhibit gene expression profiles that match those of resistant tumor cell clusters, present after treatment. We confirm that these clusters are resistant by the localization of active androgen receptors to the nuclei in cancer cells post-treatment. Our data also demonstrates that most stromal cells adjacent to resistant clusters do not express the androgen receptor, and we identify differentially expressed genes for these cells. Altogether, this study shows the potential to increase the power in predicting resistant tumors.

RSC and GRFs confer promoter directionality by restricting divergent noncoding transcription

The directionality of gene promoters-the ratio of protein-coding over divergent noncoding transcription-is highly variable. How promoter directionality is controlled remains poorly understood. Here, we show that the chromatin remodelling complex RSC and general regulatory factors (GRFs) dictate promoter directionality by attenuating divergent transcription relative to protein-coding transcription. At gene promoters that are highly directional, depletion of RSC leads to a relative increase in divergent noncoding transcription and thus to a decrease in promoter directionality. We find that RSC has a modest effect on nucleosome positioning upstream in promoters at the sites of divergent transcription. These promoters are also enriched for the binding of GRFs such as Reb1 and Abf1. Ectopic targeting of divergent transcription initiation sites with GRFs or the dCas9 DNA-binding protein suppresses divergent transcription. Our data suggest that RSC and GRFs play a pervasive role in limiting divergent transcription relative to coding direction transcription. We propose that any DNA-binding factor, when stably associated with cryptic transcription start sites, forms a barrier which represses divergent transcription, thereby promoting promoter directionality.

Hemocytes are essential for Drosophila melanogaster post-embryonic development, independent of control of the microbiota

Proven roles for hemocytes (blood cells) have expanded beyond the control of infections in Drosophila. Despite this, the crucial role of hemocytes in post-embryonic development has long thought to be limited to control of microorganisms during metamorphosis. This has previously been shown by rescue of adult development in hemocyte-ablation models under germ-free conditions. Here, we show that hemocytes have an essential role in post-embryonic development beyond their ability to control the microbiota. Using a newly generated strong hemocyte-specific driver line for the GAL4/UAS system, we show that specific ablation of hemocytes is early pupal lethal, even under axenic conditions. Genetic rescue experiments prove that this is a hemocyte-specific phenomenon. RNA-seq data suggests that dysregulation of the midgut is a prominent consequence of hemocyte ablation in larval stages, resulting in reduced gut lengths. Dissection suggests that multiple processes may be affected during metamorphosis. We believe this previously unreported role for hemocytes during metamorphosis is a major finding for the field.

Rhythmicity is linked to expression cost at the protein level but to expression precision at the mRNA level

Many genes have nycthemeral rhythms of expression, i.e. a 24-hours periodic variation, at either mRNA or protein level or both, and most rhythmic genes are tissue-specific. Here, we investigate and discuss the evolutionary origins of rhythms in gene expression. Our results suggest that rhythmicity of protein expression could have been favored by selection to minimize costs. Trends are consistent in bacteria, plants and animals, and are also supported by tissue-specific patterns in mouse. Unlike for protein level, cost cannot explain rhythm at the RNA level. We suggest that instead it allows to periodically reduce expression noise. Noise control had the strongest support in mouse, with limited evidence in other species. We have also found that genes under stronger purifying selection are rhythmically expressed at the mRNA level, and we propose that this is because they are noise sensitive genes. Finally, the adaptive role of rhythmic expression is supported by rhythmic genes being highly expressed yet tissue-specific. This provides a good evolutionary explanation for the observation that nycthemeral rhythms are often tissue-specific.

For many genes, their expression, i.e. the production of RNA and proteins, is rhythmic with a 24-hour period. Here, we study and discuss the evolutionary origins of these rhythms. Our analyses of data from different species suggest that the rhythmicity of protein level may have been favored by selection for cost minimization. Furthermore, we have shown that cost cannot explain the rhythmic variations in RNA levels. Instead, we suggest that it periodically reduces the stochasticity of gene expression. We also found that genes under stronger purifying selection are rhythmically expressed at the mRNA level, and propose that this is because they are noise-sensitive genes. Finally, rhythmic expression involves genes that are often highly expressed and tissue-specific. This provides a good evolutionary explanation for the tissue-specificity of these rhythms.

Gnocis: An integrated system for interactive and reproducible analysis and modelling of cis-regulatory elements in Python 3

Gene expression is regulated through cis-regulatory elements (CREs), among which are promoters, enhancers, Polycomb/Trithorax Response Elements (PREs), silencers and insulators. Computational prediction of CREs can be achieved using a variety of statistical and machine learning methods combined with different feature space formulations. Although Python packages for DNA sequence feature sets and for machine learning are available, no existing package facilitates the combination of DNA sequence feature sets with machine learning methods for the genome-wide prediction of candidate CREs. We here present Gnocis, a Python package that streamlines the analysis and the modelling of CRE sequences by providing extensible APIs and implementing the glue required for combining feature sets and models for genome-wide prediction. Gnocis implements a variety of base feature sets, including motif pair occurrence frequencies and the k-spectrum mismatch kernel. It integrates with Scikit-learn and TensorFlow for state-of-the-art machine learning. Gnocis additionally implements a broad suite of tools for the handling and preparation of sequence, region and curve data, which can be useful for general DNA bioinformatics in Python. We also present Deep-MOCCA, a neural network architecture inspired by SVM-MOCCA that achieves moderate to high generalization without prior motif knowledge. To demonstrate the use of Gnocis, we applied multiple machine learning methods to the modelling of D. melanogaster PREs, including a Convolutional Neural Network (CNN), making this the first study to model PREs with CNNs. The models are readily adapted to new CRE modelling problems and to other organisms. In order to produce a high-performance, compiled package for Python 3, we implemented Gnocis in Cython. Gnocis can be installed using the PyPI package manager by running ‘pip install gnocis’. The source code is available on GitHub, at https://github.com/bjornbredesen/gnocis.

Purifying selection enduringly acts on the sequence evolution of highly expressed proteins in Escherichia coli

The evolutionary speed of a protein sequence is constrained by its expression level, with highly expressed proteins evolving relatively slowly. This negative correlation between expression levels and evolutionary rates (known as the E–R anticorrelation) has already been widely observed in past macroevolution between species from bacteria to animals. However, it remains unclear whether this seemingly general law also governs recent evolution, including past and de novo, within a species. However, the advent of genomic sequencing and high-throughput phenotyping, particularly for bacteria, has revealed fundamental gaps between the 2 evolutionary processes and has provided empirical data opposing the possible underlying mechanisms which are widely believed. These conflicts raise questions about the generalization of the E–R anticorrelation and the relevance of plausible mechanisms. To explore the ubiquitous impact of expression levels on molecular evolution and test the relevance of the possible underlying mechanisms, we analyzed the genome sequences of 99 strains of Escherichia coli for evolution within species in nature. We also analyzed genomic mutations accumulated under laboratory conditions as a model of de novo evolution within species. Here, we show that E–R anticorrelation is significant in both past and de novo evolution within species in E. coli. Our data also confirmed ongoing purifying selection on highly expressed genes. Ongoing selection included codon-level purifying selection, supporting the relevance of the underlying mechanisms. However, the impact of codon-level purifying selection on the constraints in evolution within species might be smaller than previously expected from evolution between species.