Target repositioning using multi-layer networks and machine learning: The case of prostate cancer.

The discovery of novel therapeutic targets, defined as proteins which drugs can interact with to induce therapeutic benefits, typically represent the first and most important step of drug discovery. One solution for target discovery is target repositioning, a strategy which relies on the repurposing of known targets for new diseases, leading to new treatments, less side effects and potential drug synergies. Biological networks have emerged as powerful tools for integrating heterogeneous data and facilitating the prediction of biological or therapeutic properties. Consequently, they are widely employed to predict new therapeutic targets by characterizing potential candidates, often based on their interactions within a Protein-Protein Interaction (PPI) network, and their proximity to genes associated with the disease. However, over-reliance on PPI networks and the assumption that potential targets are necessarily near known genes can introduce biases that may limit the effectiveness of these methods. This study addresses these limitations in two ways. First, by exploiting a multi-layer network which incorporates additional information such as gene regulation, metabolite interactions, metabolic pathways, and several disease signatures such as Differentially Expressed Genes, mutated genes, Copy Number Alteration, and structural variants. Second, by extracting relevant features from the network using several approaches including proximity to disease-associated genes, but also unbiased approaches such as propagation-based methods, topological metrics, and module detection algorithms. Using prostate cancer as a case study, the best features were identified and utilized to train machine learning algorithms to predict 5 novel promising therapeutic targets for prostate cancer: IGF2R, C5AR, RAB7, SETD2 and NPBWR1.

A Machine Learning Approach to Identify Key Residues Involved in Protein-Protein Interactions Exemplified with SARS-CoV-2 Variants.

Human infection with the coronavirus disease 2019 (COVID-19) is mediated by the binding of the spike protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to the human angiotensin-converting enzyme 2 (ACE2). The frequent mutations in the receptor-binding domain (RBD) of the spike protein induced the emergence of variants with increased contagion and can hinder vaccine efficiency. Hence, it is crucial to better understand the binding mechanisms of variant RBDs to human ACE2 and develop efficient methods to characterize this interaction. In this work, we present an approach that uses machine learning to analyze the molecular dynamics simulations of RBD variant trajectories bound to ACE2. Along with the binding free energy calculation, this method was used to characterize the major differences in ACE2-binding capacity of three SARS-CoV-2 RBD variants-namely the original Wuhan strain, Omicron BA.1, and the more recent Omicron BA.5 sublineages. Our analyses assessed the differences in binding free energy and shed light on how it affects the infectious rates of different variants. Furthermore, this approach successfully characterized key binding interactions and could be deployed as an efficient tool to predict different binding inhibitors to pave the way for new preventive and therapeutic strategies.

SOS genes are rapidly induced while translesion synthesis polymerase activity is temporally regulated.

The DNA damage inducible SOS response in bacteria serves to increase survival of the species at the cost of mutagenesis. The SOS response first initiates error-free repair followed by error-prone repair. Here, we have employed a multi-omics approach to elucidate the temporal coordination of the SOS response. Escherichia coli was grown in batch cultivation in bioreactors to ensure highly controlled conditions, and a low dose of the antibiotic ciprofloxacin was used to activate the SOS response while avoiding extensive cell death. Our results show that expression of genes involved in error-free and error-prone repair were both induced shortly after DNA damage, thus, challenging the established perception that the expression of error-prone repair genes is delayed. By combining transcriptomics and a sub-proteomics approach termed signalomics, we found that the temporal segregation of error-free and error-prone repair is primarily regulated after transcription, supporting the current literature. Furthermore, the heterology index (i.e., the binding affinity of LexA to the SOS box) was correlated to the maximum increase in gene expression and not to the time of induction of SOS genes. Finally, quantification of metabolites revealed increasing pyrimidine pools as a late feature of the SOS response. Our results elucidate how the SOS response is coordinated, showing a rapid transcriptional response and temporal regulation of mutagenesis on the protein and metabolite levels.

Unveiling the crucial neuronal role of the proteasomal ATPase subunit gene PSMC5 in neurodevelopmental proteasomopathies.

Neurodevelopmental proteasomopathies represent a distinctive category of neurodevelopmental disorders (NDD) characterized by genetic variations within the 26S proteasome, a protein complex governing eukaryotic cellular protein homeostasis. In our comprehensive study, we identified 23 unique variants in PSMC5 , which encodes the AAA-ATPase proteasome subunit PSMC5/Rpt6, causing syndromic NDD in 38 unrelated individuals. Overexpression of PSMC5 variants altered human hippocampal neuron morphology, while PSMC5 knockdown led to impaired reversal learning in flies and loss of excitatory synapses in rat hippocampal neurons. PSMC5 loss-of-function resulted in abnormal protein aggregation, profoundly impacting innate immune signaling, mitophagy rates, and lipid metabolism in affected individuals. Importantly, targeting key components of the integrated stress response, such as PKR and GCN2 kinases, ameliorated immune dysregulations in cells from affected individuals. These findings significantly advance our understanding of the molecular mechanisms underlying neurodevelopmental proteasomopathies, provide links to research in neurodegenerative diseases, and open up potential therapeutic avenues.

Use of Elasticsearch-based business intelligence tools for integration and visualization of biological data.

The emergence of massive datasets exploring the multiple levels of molecular biology has made their analysis and knowledge transfer more complex. Flexible tools to manage big biological datasets could be of great help for standardizing the usage of developed data visualizations and integration methods. Business intelligence (BI) tools have been used in many fields as exploratory tools. They have numerous connectors to link numerous data repositories with a unified graphic interface, offering an overview of data and facilitating interpretation for decision makers. BI tools could be a flexible and user-friendly way of handling molecular biological data with interactive visualizations. However, it is rather uncommon to see such tools used for the exploration of massive and complex datasets in biological fields. We believe that two main obstacles could be the reason. Firstly, we posit that the way to import data into BI tools are not compatible with biological databases. Secondly, BI tools may not be adapted to certain particularities of complex biological data, namely, the size, the variability of datasets and the availability of specialized visualizations. This paper highlights the use of five BI tools (Elastic Kibana, Siren Investigate, Microsoft Power BI, Salesforce Tableau and Apache Superset) onto which the massive data management repository engine called Elasticsearch is compatible. Four case studies will be discussed in which these BI tools were applied on biological datasets with different characteristics. We conclude that the performance of the tools depends on the complexity of the biological questions and the size of the datasets.

The tip protein PAAR is required for the function of the type VI secretion system.

IMPORTANCE: The type VI secretion system (T6SS) is a bacterial contractile injection system involved in bacterial competition by the delivery of antibacterial toxins. The T6SS consists of an envelope-spanning complex that recruits the baseplate, allowing the polymerization of a contractile tail structure. The tail is a tube wrapped by a sheath and topped by the tip of the system, the VgrG spike/PAAR complex. Effectors loaded onto the puncturing tip or into the tube are propelled in the target cells upon sheath contraction. The PAAR protein tips and sharpens the VgrG spike. However, the importance and the function of this protein remain unclear. Here, we provide evidence for association of PAAR at the tip of the VgrG spike. We also found that the PAAR protein is a T6SS critical component required for baseplate and sheath assembly.

Higher risk of pre-eclampsia and other vascular disorders with artificial cycle for frozen-thawed embryo transfer compared to ovulatory cycle or to fresh embryo transfer following in vitro fertilization.

Background: Risks of maternal morbidity are known to be reduced in pregnancies resulting from frozen embryo transfer (FET) compared to fresh-embryo transfer (fresh-ET), except for the risk of pre-eclampsia, reported to be higher in FET pregnancies compared to fresh-ET or natural conception. Few studies have compared the risk of maternal vascular morbidities according to endometrial preparation for FET, either with ovulatory cycle (OC-FET) or artificial cycle (AC-FET). Furthermore, maternal pre-eclampsia could be associated with subsequent vascular disorders in the offspring. Methods: A 2013-2018 French nationwide cohort study comparing maternal vascular morbidities in 3 groups of single pregnancies was conducted: FET with either OC or AC preparation, and fresh-ET. Data were extracted from the French National Health System database. Results were adjusted for maternal characteristics and infertility (age, parity, smoking, obesity, history of diabetes or hypertension, endometriosis, polycystic ovary syndrome and premature ovarian insufficiency). Results: A total of 68025 single deliveries were included: fresh-ET (n=48152), OC-FET (n=9500), AC-FET (n=10373). The risk of pre-eclampsia was higher in AC-FET compared to OC-FET and fresh-ET groups in univariate analysis (5.3% vs. 2.3% and 2.4%, respectively, P<0.0001). In multivariate analysis the risk was significantly higher in AC-FET compared to fresh-ET: aOR=2.43 [2.18-2.70], P<0.0001). Similar results were observed for the risk of other vascular disorders in univariate analysis (4.7% vs. 3.4% and 3.3%, respectively, P=0.0002) and in multivariate analysis (AC-FET compared to fresh-ET: aOR=1.50 [1.36-1.67], P<0.0001). In multivariate analysis, the risk of pre-eclampsia and other vascular disorders were comparable in OC-FET and fresh-ET: aOR=1.01 [0.87-1.17, P= 0.91 and aOR=1.00 [0.89-1.13], P=0.97, respectively).Within the group of FET, the risks of pre-eclampsia and other vascular disorders in multivariate analysis were higher in AC-FET compared to OC-FET (aOR=2.43 [2.18-2.70], P<0.0001 and aOR=1.5 [1.36-1.67], P<0.0001, respectively). Conclusion: This nationwide register-based cohort study highlights the possibly deleterious role of prolonged doses of exogenous estrogen-progesterone supplementation on gestational vascular pathologies and the protective role of the corpus luteum present in OC-FET for their prevention. Since OC-FET has been demonstrated not to strain the chances of pregnancy, OC preparation should be advocated as first-line preparation in FET as often as possible in ovulatory women.

Determinants of rapid adaptation in species with large variance in offspring production.

The speed of population adaptation to changing biotic and abiotic environments is determined by the interaction between genetic drift, positive selection and linkage effects. Many marine species (fish, crustaceans), invertebrates and pathogens of humans and crops, exhibit sweepstakes reproduction characterized by the production of a very large amount of offspring (fecundity phase) from which only a small fraction may survive to the next generation (viability phase). Using stochastic simulations, we investigate whether the occurrence of sweepstakes reproduction affects the efficiency of a positively selected unlinked locus, and thus, the speed of adaptation since fecundity and/or viability have distinguishable consequences on mutation rate, probability and fixation time of advantageous alleles. We observe that the mean number of mutations at the next generation is always the function of the population size, but the variance increases with stronger sweepstakes reproduction when mutations occur in the parents. On the one hand, stronger sweepstakes reproduction magnifies the effect of genetic drift thus increasing the probability of fixation of neutral allele and decreasing that of selected alleles. On the other hand, the time to fixation of advantageous (as well as neutral) alleles is shortened by stronger sweepstakes reproduction. Importantly, fecundity and viability selection exhibit different probabilities and times to fixation of advantageous alleles under intermediate and weak sweepstakes reproduction. Finally, alleles under both strong fecundity and viability selection display a synergistic efficiency of selection. We conclude that measuring and modelling accurately fecundity and/or viability selection are crucial to predict the adaptive potential of species with sweepstakes reproduction.

PSMC3 proteasome subunit variants are associated with neurodevelopmental delay and type I interferon production.

A critical step in preserving protein homeostasis is the recognition, binding, unfolding, and translocation of protein substrates by six AAA-ATPase proteasome subunits (ATPase-associated with various cellular activities) termed PSMC1-6, which are required for degradation of proteins by 26S proteasomes. Here, we identified 15 de novo missense variants in the PSMC3 gene encoding the AAA-ATPase proteasome subunit PSMC3/Rpt5 in 23 unrelated heterozygous patients with an autosomal dominant form of neurodevelopmental delay and intellectual disability. Expression of PSMC3 variants in mouse neuronal cultures led to altered dendrite development, and deletion of the PSMC3 fly ortholog Rpt5 impaired reversal learning capabilities in fruit flies. Structural modeling as well as proteomic and transcriptomic analyses of T cells derived from patients with PSMC3 variants implicated the PSMC3 variants in proteasome dysfunction through disruption of substrate translocation, induction of proteotoxic stress, and alterations in proteins controlling developmental and innate immune programs. The proteostatic perturbations in T cells from patients with PSMC3 variants correlated with a dysregulation in type I interferon (IFN) signaling in these T cells, which could be blocked by inhibition of the intracellular stress sensor protein kinase R (PKR). These results suggest that proteotoxic stress activated PKR in patient-derived T cells, resulting in a type I IFN response. The potential relationship among proteosome dysfunction, type I IFN production, and neurodevelopment suggests new directions in our understanding of pathogenesis in some neurodevelopmental disorders.

Risk factors associated with preterm birth in singletons born after IVF: a national cohort study.

RESEARCH QUESTION: What are the risk factors for prematurity other than intrauterine growth restriction in singletons after IVF? DESIGN: Data were collected from a national registry, based on an observational prospective cohort of 30,737 live births after assisted reproductive technology (fresh embryo transfers: n = 20,932 and frozen embryo transfer [FET] n = 9805) between 2014 and 2015. A population of not-small for gestational age singletons conceived after fresh embryo transfers and FET, and their parents, was selected. Data on a number of variables were collected, including type of infertility, number of oocytes retrieved and vanishing twins. RESULTS: Preterm birth occurred in 7.7% (n = 1607) of fresh embryo transfers and 6.2% (n = 611) of frozen-thawed embryo transfers (P < 0.0001; adjusted odds ratio [aOR] = 1.34 [1.21-1.49]). Endometriosis and vanishing twin increased the risk of preterm birth after fresh embryo transfer (P < 0.001; aOR 1.32 and 1.78, respectively). Polycystic ovaries or more than 20 oocytes retrieved also increased preterm birth risk (aOR 1.31 and 1.30; P = 0.003 and P = 0.02, respectively); large oocyte cohort (>20) was no longer associated with the risk of prematurity in FET. CONCLUSION: Endometriosis remains a risk for prematurity even in the absence of intrauterine growth retardation, which suggests a dysimmune effect. Large oocyte cohorts obtained by stimulation, without clinical polycystic ovary syndrome diagnosed before attempts, do not affect FET outcomes, reinforcing the idea of a phenotypic difference in the clinical presentation of polycystic ovary syndrome.

Fetal growth disorders following medically assisted reproduction: due to maternal context or techniques? A national French cohort study.

RESEARCH QUESTION: What part do maternal context and medically assisted reproduction (MAR) techniques play in the risk of fetal growth disorders? DESIGN: This retrospective nationwide cohort study uses data available in the French National Health System database and focuses on the period from 2013 to 2017. Fetal growth disorders were divided into four groups according to the origin of pregnancy: fresh embryo transfer (n = 45,201), frozen embryo transfer (FET, n = 18,845), intrauterine insemination (IUI, n = 20,179) and natural conceptions (n = 3,412,868). Fetal growth disorders were defined from the percentiles of the weight distribution according to gestational age and sex: small and large for gestational age (SGA and LGA) if <10th and >90th percentiles, respectively. Analyses were performed using univariate and multivariate logistic models. RESULTS: Compared with births following natural conception, multivariate analysis showed that the risk of SGA was higher for births following fresh embryo transfer and IUI (adjusted odds ratio [aOR] 1.26 [1.22-1.29] and 1.08 [1.03-1.12], respectively) and significantly lower following FET (aOR 0.79 [0.75-0.83]). The risk of LGA was higher for births following FET (aOR 1.32 [1.27-1.38]), especially in artificial cycles when compared with ovulatory cycles (aOR 1.25 [1.15-1.36]). In the subgroup of births without any obstetrical or neonatal morbidity, the same increased risk of SGA and LGA were observed following fresh embryo transfer or IUI and FET (aOR 1.23 [1.19-1.27] or 1.06 [1.01-1.11] and aOR 1.36 [1.30-1.43], respectively). CONCLUSIONS: An effect of MAR techniques on the risks for SGA and LGA is suggested independently from maternal context and obstetrical or neonatal morbidities. Pathophysiological mechanisms remain poorly understood and should be further evaluated, as well as the influence of embryonic stage and freezing techniques.

Transgenerational impact of grand-paternal lifetime exposures to both folic acid deficiency and supplementation on genome-wide DNA methylation in male germ cells.

BACKGROUND: DNA methylation (DNAme) erasure and reacquisition occur during prenatal male germ cell development; some further remodeling takes place after birth during spermatogenesis. Environmental insults during germline epigenetic reprogramming may affect DNAme, presenting a potential mechanism for transmission of environmental exposures across multiple generations. OBJECTIVES: We investigated how germ cell DNAme is impacted by lifetime exposures to diets containing either low or high, clinically relevant, levels of the methyl donor folic acid and whether resulting DNAme alterations were inherited in germ cells of male offspring of subsequent generations. MATERIALS AND METHODS: Female mice were placed on a control (FCD), 7-fold folic acid deficient (7FD) or 10- to 20-fold supplemented (10FS and 20FS) diet before and during pregnancy. Resulting F1 litters were weaned on the respective diets. F2 and F3 males received control diets. Genome-wide DNAme at cytosines (within CpG sites) was assessed in F1 spermatogonia, and in F1, F2 and F3 sperm. RESULTS: In F1 germ cells, a greater number of differentially methylated cytosines (DMCs) were observed in spermatogonia as compared with F1 sperm for all folic acid diets. DMCs were lower in number in F2 versus F1 sperm, while an unexpected increase was found in F3 sperm. DMCs were predominantly hypomethylated, with genes in neurodevelopmental pathways commonly affected in F1, F2 and F3 male germ cells. While no DMCs were found to be significantly inherited inter- or transgenerationally, we observed over-representation of repetitive elements, particularly young long interspersed nuclear elements (LINEs). DISCUSSION AND CONCLUSION: These results suggest that the prenatal window is the time most susceptible to folate-induced alterations in sperm DNAme in male germ cells. Altered methylation of specific sites in F1 germ cells was not present in later generations. However, the presence of DNAme perturbations in the sperm of males of the F2 and F3 generations suggests that epigenetic inheritance mechanisms other than DNAme may have been impacted by the folate diet exposure of F1 germ cells.

Activity and Crystal Structure of the Adherent-Invasive Escherichia coli Tle3/Tli3 T6SS Effector/Immunity Complex Determined Using an AlphaFold2 Predicted Model.

The type VI secretion system (T6SS) delivers enzymatic effectors into target cells to destroy them. Cells of the same strain protect themselves against effectors with immunity proteins that specifically inhibit effectors. Here, we report the identification and characterization of a Tle3 phospholipase effector and its cognate immunity protein Tli3-an outer membrane lipoprotein from adherent-invasive Escherichia coli (AIEC). Enzymatic assays demonstrate that purified Tle3AIEC has a phospholipase A1, and not A2, activity and that its toxicity is neutralized by the cognate immunity protein Tli3AIEC. Tli3AIEC binds Tle3 in a 1:1 stoichiometric ratio. Tle3AIEC, Tli3AIEC and the Tle3AIEC-Tli3AIEC complex were purified and subjected to crystallization. The Tle3AIEC-Tli3AIEC complex structure could not be solved by SeMet phasing, but only by molecular replacement when using an AlphaFold2 prediction model. Tle3AIEC exhibits an α/ß-hydrolase fold decorated by two protruding segments, including a N-terminus loop. Tli3AIEC displays a new fold of three stacked ß-sheets and a protruding loop that inserts in Tle3AIECcatalytic crevice. We showed, experimentally, that Tle3AIEC interacts with the VgrG AIEC cargo protein and AlphaFold2 prediction of the VgrGAIEC-Tle3AIEC complex reveals a strong interaction between the VgrGAIEC C-terminus adaptor and Tle3AIEC N-terminal loop.

Overview of methods for characterization and visualization of a protein-protein interaction network in a multi-omics integration context.

At the heart of the cellular machinery through the regulation of cellular functions, protein-protein interactions (PPIs) have a significant role. PPIs can be analyzed with network approaches. Construction of a PPI network requires prediction of the interactions. All PPIs form a network. Different biases such as lack of data, recurrence of information, and false interactions make the network unstable. Integrated strategies allow solving these different challenges. These approaches have shown encouraging results for the understanding of molecular mechanisms, drug action mechanisms, and identification of target genes. In order to give more importance to an interaction, it is evaluated by different confidence scores. These scores allow the filtration of the network and thus facilitate the representation of the network, essential steps to the identification and understanding of molecular mechanisms. In this review, we will discuss the main computational methods for predicting PPI, including ones confirming an interaction as well as the integration of PPIs into a network, and we will discuss visualization of these complex data.

New Developments and Possibilities in Reanalysis and Reinterpretation of Whole Exome Sequencing Datasets for Unsolved Rare Diseases Using Machine Learning Approaches.

Rare diseases impact the lives of 300 million people in the world. Rapid advances in bioinformatics and genomic technologies have enabled the discovery of causes of 20-30% of rare diseases. However, most rare diseases have remained as unsolved enigmas to date. Newer tools and availability of high throughput sequencing data have enabled the reanalysis of previously undiagnosed patients. In this review, we have systematically compiled the latest developments in the discovery of the genetic causes of rare diseases using machine learning methods. Importantly, we have detailed methods available to reanalyze existing whole exome sequencing data of unsolved rare diseases. We have identified different reanalysis methodologies to solve problems associated with sequence alterations/mutations, variation re-annotation, protein stability, splice isoform malfunctions and oligogenic analysis. In addition, we give an overview of new developments in the field of rare disease research using whole genome sequencing data and other omics.

Sperm Heterogeneity Accounts for Sperm DNA Methylation Variations Observed in the Caput Epididymis, Independently From DNMT/TET Activities.

Following their production in the testis, spermatozoa enter the epididymis where they gain their motility and fertilizing abilities. This post-testicular maturation coincides with sperm epigenetic profile changes that influence progeny outcome. While recent studies highlighted the dynamics of small non-coding RNAs in maturing spermatozoa, little is known regarding sperm methylation changes and their impact at the post-fertilization level. Fluorescence-activated cell sorting (FACS) was used to purify spermatozoa from the testis and different epididymal segments (i.e., caput, corpus and cauda) of CAG/su9-DsRed2; Acr3-EGFP transgenic mice in order to map out sperm methylome dynamics. Reduced representation bisulfite sequencing (RRBS-Seq) performed on DNA from these respective sperm populations indicated that high methylation changes were observed between spermatozoa from the caput vs. testis with 5,546 entries meeting our threshold values (q value <0.01, methylation difference above 25%). Most of these changes were transitory during epididymal sperm maturation according to the low number of entries identified between spermatozoa from cauda vs. testis. According to enzymatic and sperm/epididymal fluid co-incubation assays, (de)methylases were not found responsible for these sperm methylation changes. Instead, we identified that a subpopulation of caput spermatozoa displayed distinct methylation marks that were susceptible to sperm DNAse treatment and accounted for the DNA methylation profile changes observed in the proximal epididymis. Our results support the paradigm that a fraction of caput spermatozoa has a higher propensity to bind extracellular DNA, a phenomenon responsible for the sperm methylome variations observed at the post-testicular level. Further investigating the degree of conservation of this sperm heterogeneity in human will eventually provide new considerations regarding sperm selection procedures used in fertility clinics.

Representations of personalised medicine in family medicine: a qualitative analysis.

BACKGROUND: The promise of personalised medicine (PM) to transform healthcare has sparked great enthusiasm in the last years. Yet, its lack of consensus around the nature and scope of the concept has ended in terminological confusion amongst the users in primary care. We aimed to investigate the perceptions of doctors and their patients in response to this evolving concept. This present article focuses on the general understanding of personalised medicine, underlining the confusion over the concept. METHODS: Semi-structured comprehensive interviews were conducted with 10 general practitioners (GPs) and 10 of their patients. The purposive sampling took into account the doctor's age, sex, and place of practice (rural/urban); each doctor recruited one patient of the same age and sex. Each interview began with the same open-ended question about the participant's knowledge of the topic, after which a working definition was provided to continue the discussion. Using the grounded theory method, the analysis consisted of open coding, axial coding and selective coding. RESULTS: From our present analysis focusing on the general understanding of PM, three main themes representing the concept emerged. The first two representations being "centred on the person as a whole" and "focused on alternative and complementary methods", in which the therapeutic relationship was stated as key. The third theme "medicine open to innovation" involved the few participants who had a good understanding of the concept and could associate personalised medicine with genomics. For those who value therapeutic relationship, the risks of accepting innovation could result in "fast-food" medicine and interpersonal barriers. DISCUSSION: PM is predominantly unfamiliar in family medicine. It is misinterpreted as a holistic or integrative type of medicine. This semantic confusion probably lies in the choice of the label "personalised" or from the lack of a uniform definition for the term.

timeOmics: an R package for longitudinal multi-omics data integration.

MOTIVATION: Multi-omics data integration enables the global analysis of biological systems and discovery of new biological insights. Multi-omics experimental designs have been further extended with a longitudinal dimension to study dynamic relationships between molecules. However, methods that integrate longitudinal multi-omics data are still in their infancy. RESULTS: We introduce the R package timeOmics, a generic analytical framework for the integration of longitudinal multi-omics data. The framework includes pre-processing, modeling and clustering to identify molecular features strongly associated with time. We illustrate this framework in a case study to detect seasonal patterns of mRNA, metabolites, gut taxa and clinical variables in patients with diabetes mellitus from the integrative Human Microbiome Project. AVAILABILITYAND IMPLEMENTATION: timeOmics is available on Bioconductor and github.com/abodein/timeOmics. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Interpretation of network-based integration from multi-omics longitudinal data.

Multi-omics integration is key to fully understand complex biological processes in an holistic manner. Furthermore, multi-omics combined with new longitudinal experimental design can unreveal dynamic relationships between omics layers and identify key players or interactions in system development or complex phenotypes. However, integration methods have to address various experimental designs and do not guarantee interpretable biological results. The new challenge of multi-omics integration is to solve interpretation and unlock the hidden knowledge within the multi-omics data. In this paper, we go beyond integration and propose a generic approach to face the interpretation problem. From multi-omics longitudinal data, this approach builds and explores hybrid multi-omics networks composed of both inferred and known relationships within and between omics layers. With smart node labelling and propagation analysis, this approach predicts regulation mechanisms and multi-omics functional modules. We applied the method on 3 case studies with various multi-omics designs and identified new multi-layer interactions involved in key biological functions that could not be revealed with single omics analysis. Moreover, we highlighted interplay in the kinetics that could help identify novel biological mechanisms. This method is available as an R package netOmics to readily suit any application.

Early-Life Exposure to Environmental Contaminants Perturbs the Sperm Epigenome and Induces Negative Pregnancy Outcomes for Three Generations via the Paternal Lineage.

Due to the grasshopper effect, the Arctic food chain in Canada is contaminated with persistent organic pollutants (POPs) of industrial origin, including polychlorinated biphenyls and organochlorine pesticides. Exposure to POPs may be a contributor to the greater incidence of poor fetal growth, placental abnormalities, stillbirths, congenital defects and shortened lifespan in the Inuit population compared to non-Aboriginal Canadians. Although maternal exposure to POPs is well established to harm pregnancy outcomes, paternal transmission of the effects of POPs is a possibility that has not been well investigated. We used a rat model to test the hypothesis that exposure to POPs during gestation and suckling leads to developmental defects that are transmitted to subsequent generations via the male lineage. Indeed, developmental exposure to an environmentally relevant Arctic POPs mixture impaired sperm quality and pregnancy outcomes across two subsequent, unexposed generations and altered sperm DNA methylation, some of which are also observed for two additional generations. Genes corresponding to the altered sperm methylome correspond to health problems encountered in the Inuit population. These findings demonstrate that the paternal methylome is sensitive to the environment and that some perturbations persist for at least two subsequent generations. In conclusion, although many factors influence health, paternal exposure to contaminants plays a heretofore-underappreciated role with sperm DNA methylation contributing to the molecular underpinnings involved.