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Recent advances in sequencing, mass spectrometry, and cytometry technologies have enabled researchers to collect multiple 'omics data types from a single sample. These large datasets have led to a growing consensus that a holistic approach is needed to identify new candidate biomarkers and unveil mechanisms underlying disease etiology, a key to precision medicine. While many reviews and benchmarks have been conducted on unsupervised approaches, their supervised counterparts have received less attention in the literature and no gold standard has emerged yet. In this work, we present a thorough comparison of a selection of six methods, representative of the main families of intermediate integrative approaches (matrix factorization, multiple kernel methods, ensemble learning, and graph-based methods). As non-integrative control, random forest was performed on concatenated and separated data types. Methods were evaluated for classification performance on both simulated and real-world datasets, the latter being carefully selected to cover different medical applications (infectious diseases, oncology, and vaccines) and data modalities. A total of 15 simulation scenarios were designed from the real-world datasets to explore a large and realistic parameter space (e.g. sample size, dimensionality, class imbalance, effect size). On real data, the method comparison showed that integrative approaches performed better or equally well than their non-integrative counterpart. By contrast, DIABLO and the four random forest alternatives outperform the others across the majority of simulation scenarios. The strengths and limitations of these methods are discussed in detail as well as guidelines for future applications.
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Biologia Computacional , Humanos , Biologia Computacional/métodos , Algoritmos , Genômica/métodos , Genômica/estatística & dados numéricos , MultiômicaRESUMO
Background and aims: Hepatitis B virus (HBV) infection affects 300 million individuals worldwide, representing a major factor for the development of hepatic complications. Although existing antivirals are effective in suppressing replication, eradication of HBV is not achieved. Therefore, a multi-faceted approach involving antivirals and immunomodulatory agents is required. Non-human primates are widely used in pre-clinical studies due to their close evolutionary relationship to humans. Nonetheless, it is fundamental to identify the differences in immune response between humans and these models. Thus, we performed a transcriptomic characterization and interspecies comparison of the early immune responses to HBV in human and cynomolgus macaques. Methods: We characterized early transcriptomic changes in human and cynomolgus B cells, T cells, myeloid and plasmacytoid dendritic cells (pDC) exposed to HBV ex vivo for 2 hours. Differentially-expressed genes were further compared to the profiles of HBV-infected patients using publicly-available single-cell data. Results: HBV induced a wide variety of transcriptional changes in all cell types, with common genes between species representing only a small proportion. In particular, interferon gamma signaling was repressed in human pDCs. At the gene level, interferon gamma inducible protein 16 (IFI16) was upregulated in macaque pDCs, while downregulated in humans. Moreover, IFI16 expression in pDCs from chronic HBV-infected patients anti-paralleled serum HBsAg levels. Conclusion: Our characterization of early transcriptomic changes induced by HBV in humans and cynomolgus macaques represents a useful resource for the identification of shared and divergent host responses, as well as potential immune targets against HBV.
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Hepatite B , Transcriptoma , Animais , Humanos , Vírus da Hepatite B/genética , Interferon gama , Antivirais , Macaca fascicularis , Hepatite B/genéticaRESUMO
Bordetella pertussis is the bacterial causative agent of whooping cough, a serious respiratory illness. An extensive knowledge on its virulence regulation and metabolism is a key factor to ensure pertussis vaccine manufacturing process robustness. The aim of this study was to refine our comprehension of B. pertussis physiology during in vitro cultures in bioreactors. A longitudinal multi-omics analysis was carried out over 26 h small-scale cultures of B. pertussis. Cultures were performed in batch mode and under culture conditions intending to mimic industrial processes. Putative cysteine and proline starvations were, respectively, observed at the beginning of the exponential phase (from 4 to 8 h) and during the exponential phase (18 h 45 min). As revealed by multi-omics analyses, the proline starvation induced major molecular changes, including a transient metabolism with internal stock consumption. In the meantime, growth and specific total PT, PRN, and Fim2 antigen productions were negatively affected. Interestingly, the master virulence-regulating two-component system of B. pertussis (BvgASR) was not evidenced as the sole virulence regulator in this in vitro growth condition. Indeed, novel intermediate regulators were identified as putatively involved in the expression of some virulence-activated genes (vags). Such longitudinal multi-omics analysis applied to B. pertussis culture process emerges as a powerful tool for characterization and incremental optimization of vaccine antigen production.
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The immunological immaturity of the innate immune system during the first-week post-hatch enables pathogens to infect chickens, leading to the death of the animals. Current preventive solutions to improve the resistance of chicks to infections include vaccination, breeding, and sanitation. Other prophylactic solutions have been investigated, such as the stimulation of animal health with immunostimulants. Recent studies showed that administration of immune-modulators to one-day-old chicks, or in ovo, significantly reduces mortality in experimental bacterial or viral infection challenge models. Owing to a lack of molecular biomarkers required to evaluate chicken immune responses and assess the efficacy of vaccines or immune-modulators, challenge models are still used. One way to reduce challenge experiments is to define molecular signatures through omics approaches, resulting in new methodologies to rapidly screen candidate molecules or vaccines. This study aims at identifying a dual transcriptomics and metabolomics blood signature after administration of CpG-ODN (cytosine-phosphate-guanine oligodeoxynucleotides), a reference immune-stimulatory molecule. A clinical study was conducted with chicks and transcriptomics and metabolomics analyses were performed on whole-blood and plasma samples, respectively. Differentially expressed genes and metabolites with different abundance were identified in chicks treated with CpG-ODN. The results showed that CpG-ODN activated the innate immune system, within hours after administration, and its effect lasted over time, as metabolomics and transcriptomics profiles still varied 6 D after administration. In conclusion, through an integrated clinical omics approach, we deciphered in part the mode of action of CpG-ODN in post-hatch chicks.
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Galinhas , Metaboloma , Oligodesoxirribonucleotídeos , Transcriptoma , Adjuvantes Imunológicos/farmacologia , Animais , Animais Recém-Nascidos/imunologia , Oligodesoxirribonucleotídeos/imunologia , Oligodesoxirribonucleotídeos/farmacologia , Oligonucleotídeos/imunologia , Oligonucleotídeos/farmacologiaRESUMO
Recent advances in sequencing, mass spectrometry and cytometry technologies have enabled researchers to collect large-scale omics data from the same set of biological samples. The joint analysis of multiple omics offers the opportunity to uncover coordinated cellular processes acting across different omic layers. In this work, we present a thorough comparison of a selection of recent integrative clustering approaches, including Bayesian (BCC and MDI) and matrix factorization approaches (iCluster, moCluster, JIVE and iNMF). Based on simulations, the methods were evaluated on their sensitivity and their ability to recover both the correct number of clusters and the simulated clustering at the common and data-specific levels. Standard non-integrative approaches were also included to quantify the added value of integrative methods. For most matrix factorization methods and one Bayesian approach (BCC), the shared and specific structures were successfully recovered with high and moderate accuracy, respectively. An opposite behavior was observed on non-integrative approaches, i.e. high performances on specific structures only. Finally, we applied the methods on the Cancer Genome Atlas breast cancer data set to check whether results based on experimental data were consistent with those obtained in the simulations.
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Genômica/métodos , Proteômica/métodos , Teorema de Bayes , Neoplasias da Mama/genética , Neoplasias da Mama/metabolismo , Análise por Conglomerados , Humanos , Aprendizado de Máquina não SupervisionadoRESUMO
A new member of Anelloviridae, named torque teno mini virus (TTMV)-SH, was recently identified in the serum of three Hodgkin's lymphoma patients suggesting that TTMV-SH may be associated with this type of hematological malignancy. We investigated by metagenomic analysis the presence of TTMV-SH-related viruses in plasma samples (n = 323) collected from patients with various hematological malignancies (multiple myeloma (MM, n = 256), non-Hodgkin's lymphoma (NHL, n = 20), acute myeloid leukemia (n = 10)) and from healthy donors (n = 37). TTMV-SH-related strains were identified in 24 samples corresponding to four MM and one NHL patients. Phylogenic analysis revealed that the 24 isolates were close to the TTMV-SH strains previously identified, sharing 79.6-86.7% ORF1 nucleotide sequence identity. These results suggest that TTMV-SH-related viruses might be found in hematological diseases other than Hodgkin's lymphoma. Due to the high genetic variability within Anelloviridae species, the association between a particular medical condition and a new genotype should be interpreted with caution.
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Over recent years, there has been increasing interest in the use of the anelloviruses, the major component of the human virome, for the prediction of post-transplant complications such as severe infections. Due to an important diversity, the comprehensive characterization of this viral family over time has been poorly studied. To overcome this challenge, we used a metagenomic next-generation sequencing (mNGS) approach with the aim of determining the individual anellovirus profile of autologous stem cell transplant (ASCT) patients. We conducted a prospective pilot study on a homogeneous patient cohort regarding the chemotherapy regimens that included 10 ASCT recipients. A validated viral mNGS workflow was used on 108 plasma samples collected at 11 time points from diagnosis to 90 days post-transplantation. A complex interindividual variability in terms of abundance and composition was noticed. In particular, a strong sex effect was found and confirmed using quantitative PCR targeting torque teno virus, the most abundant anellovirus. Interestingly, an important turnover in the anellovirus composition was observed during the course of the disease revealing a strong intra-individual variability. Although more studies are needed to better understand anellovirus dynamics, these findings are of prime importance for their future use as biomarkers of immune competence.
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Anelloviridae/isolamento & purificação , Sangue/virologia , Infecções por Vírus de DNA/virologia , Variação Genética , Transplante de Células-Tronco , Transplantados , Transplante Autólogo , Anelloviridae/classificação , Anelloviridae/genética , Antineoplásicos/uso terapêutico , DNA Viral/química , DNA Viral/genética , Tratamento Farmacológico/métodos , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Mieloma Múltiplo/tratamento farmacológico , Projetos Piloto , Estudos Prospectivos , Análise de Sequência de DNARESUMO
BACKGROUND: Human endogenous retroviruses (HERVs) have received much attention for their implications in the etiology of many human diseases and their profound effect on evolution. Notably, recent studies have highlighted associations between HERVs expression and cancers (Yu et al., Int J Mol Med 32, 2013), autoimmunity (Balada et al., Int Rev Immunol 29:351-370, 2010) and neurological (Christensen, J Neuroimmune Pharmacol 5:326-335, 2010) conditions. Their repetitive nature makes their study particularly challenging, where expression studies have largely focused on individual loci (De Parseval et al., J Virol 77:10414-10422, 2003) or general trends within families (Forsman et al., J Virol Methods 129:16-30, 2005; Seifarth et al., J Virol 79:341-352, 2005; Pichon et al., Nucleic Acids Res 34:e46, 2006). METHODS: To refine our understanding of HERVs activity, we introduce here a new microarray, HERV-V3. This work was made possible by the careful detection and annotation of genomic HERV/MaLR sequences as well as the development of a new hybridization model, allowing the optimization of probe performances and the control of cross-reactions. RESULTS: HERV-V3 offers an almost complete coverage of HERVs and their ancestors (mammalian apparent LTR-retrotransposons, MaLRs) at the locus level along with four other repertoires (active LINE-1 elements, lncRNA, a selection of 1559 human genes and common infectious viruses). We demonstrate that HERV-V3 analytical performances are comparable with commercial Affymetrix arrays, and that for a selection of tissue/pathological specific loci, the patterns of expression measured on HERV-V3 is consistent with those reported in the literature. CONCLUSIONS: Given its large HERVs/MaLRs coverage and additional repertoires, HERV-V3 opens the door to multiple applications such as enhancers and alternative promoters identification, biomarkers identification as well as the characterization of genes and HERVs/MaLRs modulation caused by viral infection.
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Retrovirus Endógenos/genética , Perfilação da Expressão Gênica , Hibridização Genética , Modelos Genéticos , Transcriptoma , Algoritmos , Análise por Conglomerados , Biologia Computacional/métodos , Bases de Dados de Ácidos Nucleicos , Perfilação da Expressão Gênica/métodos , Loci Gênicos , Humanos , Hibridização de Ácido Nucleico , Reprodutibilidade dos Testes , Fluxo de TrabalhoRESUMO
MOTIVATION: The identification of nucleosomes along the chromatin is key to understanding their role in the regulation of gene expression and other DNA-related processes. However, current experimental methods (MNase-ChIP, MNase-Seq) sample nucleosome positions from a cell population and contain biases, making thus the precise identification of individual nucleosomes not straightforward. Recent works have only focused on the first point, where noise reduction approaches have been developed to identify nucleosome positions. RESULTS: In this article, we propose a new approach, termed NucleoFinder, that addresses both the positional heterogeneity across cells and experimental biases by seeking nucleosomes consistently positioned in a cell population and showing a significant enrichment relative to a control sample. Despite the absence of validated dataset, we show that our approach (i) detects fewer false positives than two other nucleosome calling methods and (ii) identifies two important features of the nucleosome organization (the nucleosome spacing downstream of active promoters and the enrichment/depletion of GC/AT dinucleotides at the centre of in vitro nucleosomes) with equal or greater ability than the other two methods.