Rodrigues, A. C. S. | bioRxiv Science

bioRxiv2026

Sample Preparation and Homology-Driven Search Shape the First Holobiont Proteome of the Marine Sponge Viles ophiraphidites (formerly Topsentia ophiraphidites)

Marine sponges are holobionts of host cells, extracellular matrix and dense microbial communities, and most lack reference proteomes. Viles ophiraphidites (formerly Topsentia ophiraphidites), a Brazilian demosponge, is represented in UniProtKB by a single protein. The study had two phases. In phase 1, four sample preparation workflows were compared on two specimens in 42 nLC-MS/MS runs: urea/thiourea in-solution digestion, acetone precipitation, S-Trap and GeLC-MS/MS. Every run was analysed with FragPipe and with a homology-driven pipeline that adds three layers to a rescored Sage search: the proteome of the closest sequenced relative (Halichondria panicea), MS-BLAST style alignment of de novo sequence tags, and error-tolerant interpretation of tag flanks. In phase 2, the selected workflow, S-Trap, was applied to four specimens in 12 runs. Both strategies ranked the workflows identically ({rho} = 0.98). S-Trap gave the deepest and most specimen independent proteome, with about 2,100 protein groups per specimen and an 8% difference between specimens, against 21-39% for the other workflows. The homology-driven layers raised assigned non-contaminant spectra by 21.3% in phase 1 and 26.8% in phase 2. They contributed 1,969 protein groups found only by homology and agreed with the database search on 99.5-99.9% of shared spectra. The proteome comprises 4,294 protein groups: 42% sponge and 58% bacterial or archaeal, the latter dominated by Poribacteria. It includes Nitrospira nitrite oxidoreductase detected in every run. The four phase-2 specimens had a similar composition (Bacteria 51-64% and Porifera 35-48% of peptides, Poribacteria alone 27-33%), whereas the two specimens stored long-term in ethanol at 4{degrees}C, which also differed in collection site and storage history, yielded four to five times less evidence than the frozen ones, even though reduction and alkylation had not been effective in the two frozen specimens. S-Trap combined with homology-driven search is a robust strategy for proteomics of non-model holobionts.

biochemistry↗

bioRxiv2017

Whole genome linkage analysis in a large Brazilian multigenerational family reveals distinct linkage signals for Bipolar Disorder and Depression.

Both common and rare genetic variation play a role in the causes for mood disorders. Very large families pose unique opportunities and analytical challenges but may provide a way to identify regions and mutations associated with mood disorders. We identified a family with a high prevalence (~30%) of mood disorders in a rural village in Brazil, featuring decreasing age of onset over generations. The pattern of inheritance was complex with 32 Bipolar type I cases, 11 Bipolar type II and 59 recurrent and/or severe Depression cases in addition to other phenotypes. We enrolled 333 participants with DNA samples from a broader pedigree of 960 subjects for genotyping using the Affymetrix 10K array. Non-parametric linkage was carried out via MERLIN and parametric with both MERLIN and MCLINKAGE. We exome sequenced a subset of the family (n=27) in order to identify rare variation within the linkage regions shared by affected family members. We identified four genome wide significant and four suggestive linkage regions on chromosomes 1, 2, 3, 11 and 12 for different phenotype definitions. However, no region received strong joint support in both the parametric and non-parametric analyses. Exome sequencing revealed potential deleterious variants in 11p15.4 for MDD and 1q21.1-1q21.3 and 12p23.1-p22.3, implicated in cell signaling, adhesion, translation and neurogenesis processes. Overall, our results suggest promising, but not definitive or confirmed evidence, that rare genetic variation contributes to the high prevalence of mood disorders in this multi-generational family. We note that a substantial role for common genetic variation is likely given the strength of the linkage signals observed.\n\nThe World Health Organisation reports depression and bipolar disorder as the second and seventh most important causes of years lost due to disability worldwide[1]. The heritability of bipolar disorder is between 60-90% with a lower but still substantial heritability for major depression (40-45%) [2]; [3]. First-degree relatives of bipolar disorder probands have a 5-10 fold increase in risk of developing the illness compared to relatives of controls but also show a three fold increase in unipolar depression, indicating that bipolar disorder does not \"breed true\" [4]. Large collaborative genome-wide association studies (GWAS) have uncovered several common genetic variants of small effect [5]. Genomewide estimates of heritability suggest that up to 60% of the genetic risk is contributed by common variants [6]. Overall, the current picture for bipolar disorder (and almost all complex traits) is a genetic architecture formed of both common and rare variants.\n\nLinkage studies have been pursued on the basis that there may be variants of greater effect shared between and within affected families. However these studies have usually focused on collections of comparatively small families or sib pairs and few consistent findings have emerged [7]. Large multigenerational families (e. g. of >30 affected individuals) theoretically offer a powerful means for mapping complex disease loci that are individually rare but common in a single family. These loci may be more highly penetrant and of larger effect than loci found with GWAS [8]. Here we report the results of the Brazilian Bipolar Family (BBF) study on a five-generation family of 639 members of which 333 were enrolled in the current analyses. Our objectives were to perform a linkage analysis with genome coverage and try to identify new genes/mutations related to bipolar and other mood disorders in the family. Here we report our findings and preliminary results of sequencing of linkage regions.

genetics↗