Intact cell MALDI-TOF mass spectrometry, a promising proteomic profiling method in farm animal clinical and reproduction research

Unraveling the mysteries of chicken proteomics: Insights into follicle development and reproduction

Chicken proteomics is a valuable method for comprehending the many mechanisms involved in follicle growth and reproduction in birds. This study offers a thorough summary of the latest progress in chicken proteomics research, specifically highlighting the knowledge obtained regarding follicle development and reproductive physiology. Proteomic studies have revealed essential proteins and pathways that play a role in follicle development, including those that control oocyte size, maturation, and ovulation. Proteomic investigations have provided insight into the molecular pathways that govern reproductive processes. By utilizing advanced proteomic technologies, including mass spectrometry and protein microarray analysis, we have been able to identify and measure many proteins in chicken follicles at their different developmental stages. The utilization of proteomic methods has enabled the identification of previously unknown biomarkers for reproductive efficiency that expedited the creation of innovative diagnostic instruments for monitoring reproductive health in chicken. Chicken proteomics not only offers insights into follicle growth and reproduction but also uncovers the effects of environmental influences on reproductive function. This provides new opportunities for exploring the molecular pathways that cause these effects. The integration of current data with upcoming proteomic technologies offers the potential for innovative strategies to enhance chicken reproduction.

Taxonomic identification of Morocco scorpions using MALDI-MS fingerprints of venom proteomes and computational modeling

The venom of scorpions has been the subject of numerous studies. However, their taxonomic identification is not a simple task, leading to misidentifications. This study aims to provide a practical approach for identifying scorpions based on the venom molecular mass fingerprint (MFP). Specimens (251) belonging to fifteen species were collected from different regions in Morocco. Their MFPs were acquired using MALDI-MS. These were used as a training dataset to generate predictive models and a library of mean spectral profiles using software programs based on machine learning. The computational model achieved an overall recognition capability of 99 % comprising 32 molecular signatures. The models and the library were tested using a new dataset for external validation and to evaluate their capability of identification. We recorded an accuracy classification with an average of 97 % and 98 % for the computational models and the library, respectively. To our knowledge, this is the first attempt to demonstrate the potential of MALDI-MS and MFPs to generate predictive models capable of discriminating scorpions from family to species levels, and to build a library of species-specific spectra. These promising results may represent a proof of concept towards developing a reliable approach for rapid molecular identification of scorpions in Morocco. SIGNIFICANCE OF THE STUDY: With their clinical importance, scorpions may constitute a desirable study model for many researchers. The first step in studying scorpion is systematically identifying the species of interest. However, it can be a difficult task, especially for the non-experts. The taxonomy of scorpions is primarily based on morphometric characters. In Morocco, the high number of species and subspecies mainly endemic, and the morphological similarities between different species may result in false identifications. This was observed in many reports according to the scorpion experts. In this study, we describe a reliable practical approach for identifying scorpions based on the venom molecular mass fingerprints (MFPs). By using two software programs based on machine learning, we have demonstrated that these MFPs contains sufficient inter-specific variation to differentiate between the scorpion species mentioned in this study with a good accuracy. Using a drop of venom, this new approach could be a rapid, accurate and cost saving method for taxonomic identification of scorpions in Morocco.

Alternative protocol leading to rapid identification of Actinomycetes isolated from Algerian desertic soil by MALDI-TOF mass spectrometry

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is the first-line method for the rapid identification of most cultured microorganisms. As for Streptomyces strains, MALDI-TOF MS identification is complicated by the characteristic incrustation of colonies in agar and the strong cell wall of Actinomycetes cells requiring the use of alternative protein extraction protocols. In this study, we developed a specific protocol to overcome these difficulties for the MALDI-TOF MS identification of Actinomycetes made on solid medium. This protocol includes incubation of colony removed from agar plate with the beta-agarase enzyme, followed by a mechanical lysis and two washes by phosphate buffer and ethanol. Twenty-four Streptomyces and two Lentzea strains isolated from Algerian desertic soils were first identified by 16S rRNA sequencing as gold standard method, rpoB gene was used as a secondary gene target when 16S rRNA did not allow species identification. In parallel the isolates were identified by using the MALDI-TOF MS protocol as reported. After the expansion of the database with the inclusion of this MSPS, the strains were analyzed again in MALDI Biotyper, and all were identified. This work demonstrates that the rapid identification of Actinomycetes can be obtained without protein extraction step frequently used in MALDI-TOF mass spectrometry with this type of microorganisms.

Intact cell mass spectrometry coupled with machine learning reveals minute changes induced by single gene silencing

Intact (whole) cell MALDI TOF mass spectrometry is a commonly used tool in clinical microbiology for several decades. Recently it was introduced to analysis of eukaryotic cells, including cancer and stem cells. Besides targeted metabolomic and proteomic applications, the intact cell MALDI TOF mass spectrometry provides a sufficient sensitivity and specificity to discriminate cell types, isogenous cell lines or even the metabolic states. This makes the intact cell MALDI TOF mass spectrometry a promising tool for quality control in advanced cell cultures with a potential to reveal batch-to-batch variation, aberrant clones, or unwanted shifts in cell phenotype. However, cellular alterations induced by change in expression of a single gene has not been addressed by intact cell mass spectrometry yet. In this work we used a well-characterized human ovarian cancer cell line SKOV3 with silenced expression of a tumor suppressor candidate 3 gene (TUSC3). TUSC3 is involved in co-translational N-glycosylation of proteins with well-known global impact on cell phenotype. Altogether, this experimental design represents a highly suitable model for optimization of intact cell mass spectrometry and analysis of spectral data. Here we investigated five machine learning algorithms (k-nearest neighbors, decision tree, random forest, partial least squares discrimination, and artificial neural network) and optimized their performance either in pure populations or in two-component mixtures composed of cells with normal or silenced expression of TUSC3. All five algorithms reached accuracy over 90 % and were able to reveal even subtle changes in mass spectra corresponding to alterations of TUSC3 expression. In summary, we demonstrate that spectral fingerprints generated by intact cell MALDI-TOF mass spectrometry coupled to a machine learning classifier can reveal minute changes induced by alteration of a single gene, and therefore contribute to the portfolio of quality control applications in routine cell and tissue cultures.

Factors affecting the success of laparoscopic artificial insemination in sheep

Successful artificial breeding underpins rapid genetic and production gains in animal agriculture. In sheep, artificial insemination with frozen semen is performed via intrauterine laparoscopy as frozen-thawed spermatozoa do not traverse the cervix in sufficient numbers for high fertility and transcervical insemination is anatomically impossible in most ewes. Historically, laparoscopic artificial insemination has always been considered reasonably successful, but recent anecdotal reports of poor fertility place it at risk of warning adoption. Understanding the male, female and environmental factors that influence the fertility of sheep is warranted if the success of artificial insemination is to be improved and genetic progress maximised for the sheep industry. This review details the current practice of laparoscopic AI in sheep. It explores the effects of semen quantity and quality, the ewe, her preparation, and environmental conditions, on the fertility obtained following laparoscopic artificial insemination.

Extracellular Vesicles Contribute to the Difference in Lipid Composition between Ovarian Follicles of Different Size Revealed by Mass Spectrometry Imaging

Follicular fluid (FF) ensures a safe environment for oocyte growth and maturation inside the ovarian follicle in mammals. In each cycle, the large dominant follicle (LF) contains the oocyte designated to be ovulated, whereas the small subordinate follicles (SFs) of the same wave will die through atresia. In cows, the oocytes from the SF, being 2 mm in size, are suitable for in vitro reproduction biotechnologies, and their competence in developing an embryo depends on the size of the follicles. FF contains proteins, metabolites, fatty acids, and a multitude of extracellular vesicles (ffEVs) of different origins, which may influence oocyte competence through bidirectional exchanges of specific molecular cargo between follicular cells and enclosed oocytes. FF composition evolves along with follicle growth, and the abundance of different lipids varies between the LF and SF. Here, significant differences in FF lipid content between the LFs and SFs within the same ovary were demonstrated by MALD-TOF mass spectrometry imaging on bovine ovarian sections. We then aimed to enlighten the lipid composition of FF, and MALDI-TOF lipid profiling was performed on cellular, vesicular, and liquid fractions of FF. Differential analyses on the abundance of detected lipid features revealed specific enrichment of phospholipids in different ffEV types, such as microvesicles (MVs) and exosomes (Exo), compared to depleted FF. MALDI-TOF lipid profiling on MVs and Exo from the LF and SF samples (n = 24) revealed that more than 40% of detected features were differentially abundant between the groups of MVs and Exo from the different follicles (p < 0.01, fold change > 2). Glycerophospholipid and sphingolipid features were more abundant in ffEVs from the SFs, whereas different lysophospholipids, including phosphatidylinositols, were more abundant in the LFs. As determined by functional analysis, the specific lipid composition of ffEVs suggested the involvement of vesicular lipids in cell signaling pathways and largely contributed to the differentiation of the dominant and subordinate follicles.

Use of MALDI-TOF mass spectrometry to explore the peptidome and proteome of in-vitro produced bovine embryos pre-exposed to oviduct fluid

In order to identify oviduct fluid (OF) peptides and proteins possibly uptaken by developing embryos, in-vitro produced bovine embryos exposed or not to OF were individually analyzed by MALDI-TOF mass spectrometry. Overall, 11 masses were overabundant in OF-treated embryos compared to controls, among which one at 8.9 kDa annotated as immediate early response 3-interacting protein 1 or a peptide of transitional endoplasmic reticulum ATPase met the criteria of an OF embryo-interacting protein or peptide.

Proteomic Changes Associated With Sperm Fertilizing Ability in Meat-Type Roosters

The molecular basis of male fertility remains unclear, especially in chickens, where decades of genetic selection increased male fertility variability as a side effect. As transcription and translation are highly limited in sperm, proteins are key molecules defining their functionality, making proteomic approaches one of the most adequate methods to investigate sperm capacity. In this context, it is interesting to combine complementary proteomic approaches to maximize the identification of proteins related to sperm-fertilizing ability. In the present study, we aimed at identifying proteins related to fertility in meat-type roosters, showing fertility variability. Fertile roosters (fertility rates higher than 70% after artificial insemination) differed from subfertile roosters (fertility rates lower than 40%) in their sperm mass motility. Fertile and subfertile sperm protein contents were compared using two complementary label-free quantitative proteomic methods: Intact Cell MALDI-TOF-Mass Spectrometry and GeLC-MS/MS. Combining the two strategies, 57 proteins were identified as differentially abundant. Most of them were described for the first time as differentially abundant according to fertility in this species. These proteins were involved in various molecular pathways including flagellum integrity and movement, mitochondrial functions, sperm maturation, and storage in female tract as well as oocyte-sperm interaction. Collectively, our data improved our understanding of chicken sperm biology by revealing new actors involved in the complexity of male fertility that depends on multiple cell functions to reach optimal rates. This explains the inability of reductionist in vitro fertility testing in predicting male fertility and suggests that the use of a combination of markers is a promising approach.