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Additional file 2 : Supplementary Methods.

Additional file 6 : Figure S3. Selection, design and quality criteria for the locus-specific qPCR systems, illustrated with the 060400302-HERV0489uL locus.

Additional file 3 : Figure S1. Description of HERV/MaLR transcriptome in whole blood of septic shock patients from the MIP-Rea cohort subset (descriptive phase).

Additional file 4 : Figure S2. Genomic, transcriptomic and functional projections of the “HERV_prototype” repertoire in the IMMUNOSEPSIS cohort subset (descriptive phase).

Additional file 7 : Figure S4. RT-qPCR validation of 29 HERV/MaLR loci that were identified by microarray and were differentially expressed, according to themHLA-DR expression (discovery phase).

Following inflammatory injury, like a septic shock, severe burn or important trauma, the immune system responds by a massive modulation of its transcriptome in the blood. We propose to explore another repertoire than gene expression and to focus on repeated elements, especially on HERVs. They represent more than 8% of the human genome. HERVs are expressed in similar settings (cancer or auto-immune diseases) and impact immune response. In this project, we describe and aim to better understand the HERV contribution in host immune response, following inflammatory aggression. To bring elements of response, we developed specifically dedicated tools to describe the HERVome, either at genomic or transcriptomic level. We show HERVs are expressed in blood in these settings, modulated in patients and could play a role on nearby gene expression. We also evaluate the polymorphism of presence of HERV loci on more than two thousands individuals, grouped into human populations. We show an important HERV polymorphism, that it is population-specific, and that some loci are absent in the majority of the analyzed genomes.Finally, with different approaches, we identify associations between immune-response genes and HERVs, suggesting these elements can play a role in host immune response following inflammatory aggressions, Suite à une agression inflammatoire, telle que le choc septique, des brulures graves ou un traumatisme sévère, le système immunitaire répond par une modulation massive du transcriptome dans le sang. On propose d’explorer un autre répertoire que l’expression des gènes et de s’intéresser aux éléments répétés du génome, peu étudiés dans ces contextes, et plus particulièrement aux rétrovirus endogènes humains (HERV). Ils représentent plus de 8% du génome chez l’Homme. Certains sont exprimés dans des situations similaires à l’agression inflammatoire (cancer, maladies auto-immunes) et ont un impact sur la réponse immunitaire.Dans ce travail, nous cherchons à décrire et comprendre la contribution des HERV, au sein de la réponse immunitaire de l’hôte à l’agression inflammatoire. Pour cela, nous avons développé des méthodes et outils spécifiquement dédiés à la description du HERVome, au niveau génomique et transcriptomique. Nous montrons que les HERV sont exprimés dans le sang, modulés chez les patients, et que certains pourraient jouer un rôle sur l’expression de gènes de la réponse immunitaire situés à proximité. Nous évaluons également le polymorphisme de présence des HERV dans le génome de plus de deux mille individus répartis dans les populations humaines. On met en évidence que le polymorphisme HERV est globalement important, qu’il est lié à la population d’appartenance et que certains loci sont absents dans la majorité des génomes étudiés. Finalement, par différentes approches, nous identifions des associations entre gènes de la réponse immunitaire et HERV, suggérant que ces éléments peuvent jouer un rôle important dans la réponse de l’hôte à l’agression inflammatoire

Table S1. (A) Virus strain-reference panel and (B) viral PCR-reference panel used for determination of the LOD in the automated process. Figure S1. Selection of the so-called “viral cohort”, a subset of the MIP REA cohort. Figure S2. (A) Semi-automated procedure applied to detect DNA viremia in plasma. Internal controls are used all along the process to qualify each single step, namely extraction, amplification, detection. Figure S3. (A) Procedure applied to determine the LOD (B) Last performed dilution giving a positive count and selection (red) of the LOD (left), and amplification on blood extracts from healthy volunteers; a TTV LOD in plasma was derived from Kulifaj D. et al., 2018 ( https://doi.org/10.1016/j.jcv.2018.06.010 ). Table S2. Association between binary endpoints or markers and viremia presence. Clinical outcomes are mortality at D28 following ICU admission and HAI occurrence occurring during the hospitalization. Biomarkers, quantified by RT-PCR, consisted of CD74 ratio of D3/D1 (> 1.238 = increased incidence of HAI), CX3CR1 measured at D3 (> 0.253 = increased incidence of mortality at D28), IL10 measured at D3 (> 0.039 = increased incidence of HAI), and IL1b measured at D3 (increase at D2–D4 = increase incidence of HAI in pediatric patients). Thresholds were determined using the total MIPREA cohort, for CD74 and IL10 [16] and CX3CR1 as well [17, 19]. As no threshold was proposed for IL1β [19], it was used as a continuous variable. aIL1β not a binary endpoint. (PPT 1049 kb)

Figure S2. Specialisation of LTR features on the whole dataset. (PPT 212 kb)

Figure S5. Selection, design and quality criteria for the design of locus specific qPCR systems, illustrated with the 121601901-HERV0116uL locus, and PCR systems obtained. (PPT 766 kb)

Supplementary Methods. (DOC 55 kb)

Figure S6. RT-qPCR validation of 23 microarray-based identified HERV/MaLR elements differentially expressed following LPS stimulations. (PPT 1309 kb)

Figure S4. TNF-Îą and IL-10 protein assay and mRNA quantitation in PBMCs following LPS stimulations. (PPT 172 kb)

Figure S3. Genomic environment of functional and silent LTRs. (DOC 507 kb)

Figure S7. Strategy used to integrate 62 HERVs/MaLRs and 26 genes in 11 canonical immune pathways, global landscape resulting from this analysis, and identification of PTGS2 and FLT1 associated HERVs/MaLRs at the crossroads of “LXR/RXR activation” and “NF-kB signalling” pathways. (PPT 1323 kb)

Models performance illustrated on gene CD59. (PDF 223 kb)

Correlation between gU133 probesets on HG-U133 Plus 2.0 and HERV-V3 microarrays. (PDF 281 kb)

RT-PCR validation on loci specific of placenta, colon and prostate tumor tissues, and, embryonic stem cells. (PDF 357 kb)

HERV-V3 specificity evaluation. (PDF 315 kb)

Supplementary notes. (DOCX 22 kb)