Dataset Information

Pseudolycoriella hygida saliva proteome

ABSTRACT: This experiment aimed at indentifying secreted proteins/enzymes from saliva of the fly Pseudolycoriella hygida. To do this, twelve-day-old Psl. hygida larvae were selected and the last segment of the larvae was tied with elastane fishing line with the help of a stereomicroscope. This was performed to avoid contamination of saliva samples with feaces. Groups of 20 tied larvae were transferred to 1.5-mL microtubes and a few holes were made in the microtube cap. Then, the microtubes were incubated at 22 °C for 3 h. After removing the larvae, the microtubes were briefly centrifuged at 15,000 g for 30 s, and the secreted saliva, usually 2-3 ul per tube, was stored at -20 °C until gel electrophoresis.

INSTRUMENT(S):

ORGANISM(S): Bradysia Hygida

TISSUE(S): Saliva

SUBMITTER: Richard Ward

LAB HEAD: Richard John Ward

PROVIDER: PXD033046 | Pride | 2023-04-07

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	PCF_Gel_Bradysia.tif	Other
	SEARCH_Bradysia_hygida.zip	Other
	Zelda_210507_P1651_PH_RJW_sampleR2_10prc_T_R1.raw	Raw
	Zelda_210507_P1651_PH_RJW_sampleR2_10prc_T_R2.raw	Raw
	checksum.txt	Txt

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Publications

Biocatalytic potential of Pseudolycoriella CAZymes (Sciaroidea, Diptera) in degrading plant and fungal cell wall polysaccharides.

Trinca Vitor V Carli Sibeli S Uliana João Vitor Cardoso JVC Garbelotti Carolina Victal CV Mendes da Silva Mariana M Kunes Vitor V Meleiro Luana Parras LP Brancini Guilherme Thomaz Pereira GTP Menzel Frank F Andrioli Luiz Paulo Moura LPM Torres Tatiana Teixeira TT Ward Richard John RJ Monesi Nadia N

iScience 20230320 4

Soil biota has a crucial impact on soil ecology, global climate changes, and effective crop management and studying the diverse ecological roles of dipteran larvae deepens the understanding of soil food webs. A multi-omics study of Pseudolycoriella hygida comb. nov. (Diptera: Sciaroidea: Sciaridae) aimed to characterize carbohydrate-active enzymes (CAZymes) for litter degradation in this species. Manual curation of 17,881 predicted proteins in the Psl. hygida genome identifi ...[more]

PMID: 37020966

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Project description:Expression profiling of distinct central nervous system (CNS) cell populations has been employed to facilitate disease classification and to provide insights into the molecular basis of brain pathology. One important cell type implicated in a wide variety of CNS disease states is the resident brain macrophage (microglia). In these studies, microglia are often isolated from dissociated brain tissue by flow sorting procedures [fluorescence-activated cell sorting (FACS)] or from postnatal glial cultures by mechanic isolation. Given the highly dynamic and state-dependent functions of these cells, the use of FACS or short-term culture methods may not accurately capture the biology of brain microglia. In the current study, we performed RNA-sequencing using Cx3cr1+/GFP labeled microglia isolated from the brainstem of 6-week-old mice to compare the transcriptomes of FACS-sorted versus laser capture microdissection (LCM). While both isolation techniques resulted in a large number of shared (common) transcripts, we identified transcripts unique to FACS-isolated and LCM-captured microglia. In particular, M-bM-^HM-<50% of these LCM-isolated microglial transcripts represented genes typically associated with neurons and glia. While these transcripts clearly localized to microglia using complementary methods, they were not translated into protein. Following the induction of murine experimental autoimmune encephalomyelitis, increased oligodendrocyte and neuronal transcripts were detected in microglia, while only the myelin basic protein oligodendrocyte transcript was increased in microglia after traumatic brain injury. Collectively, these findings have implications for the design and interpretation of microglia transcriptome-based investigations. Wildtype and GFP expressing microglia from mouse brainstems were flow sorted or captured by laser microdissection. Differences between the two isolation methods were verified and further examined in neurodegenerative disease models.

Project description:The dataset in this Proteome Exchange entry are specific to the WTC11 benchmarking samples described in the "IsoBayes" publication (Bollon et al.) Motivation: Studying protein isoforms is an essential step in biomedical research; at present, the main approach for analyzing proteins is via bottom-up mass spectrometry proteomics, which return peptide identifications, that are indirectly used to infer the presence of protein isoforms. However, the detection and quantification processes are noisy; in particular, peptides may be erroneously detected, and most peptides, known as shared peptides, are associated to multiple protein isoforms. As a consequence, studying individual protein isoforms is challenging, and inferred protein results are often abstracted to the gene-level or to groups of protein isoforms. Results: Here, we introduce IsoBayes, a novel statistical method to perform inference at the isoform level. Our method enhances the information available, by integrating mass spectrometry proteomics and transcriptomics data in a Bayesian probabilistic framework. To account for the uncertainty in the measurement process, we propose a two-layer latent variable approach: first, we sample if a peptide has been correctly detected (or, alternatively filter peptides); second, we allocate the abundance of such selected peptides across the protein(s) they are compatible with. This enables us, starting from peptide-level data, to recover protein-level data; in particular, we: i) infer the presence/absence of each protein isoform (via a posterior probability), ii) estimate its abundance (and credible interval), and iii) target isoforms where transcript and protein relative abundances significantly differ. We benchmarked our approach in simulations, and in two multi-protease real datasets: our method displays good sensitivity and specificity when detecting protein isoforms, its estimated abundances highly correlate with the ground truth, and can detect changes between protein and transcript relative abundances. Availability and implementation: IsoBayes is freely distributed as a Bioconductor R package, and is accompanied by an example usage vignette.

Dataset Information

Pseudolycoriella hygida saliva proteome

Dataset's files

Publications

Biocatalytic potential of <i>Pseudolycoriella</i> CAZymes (Sciaroidea, Diptera) in degrading plant and fungal cell wall polysaccharides.

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