Compartment Proteomics Analysis of White Perch (Morone americana) Ovary Using Support Vector Machines

Combinatorial metabolomic and transcriptomic analysis of muscle growth in hybrid striped bass (female white bass Morone chrysops x male striped bass M. saxatilis)

BACKGROUND

Understanding growth regulatory pathways is important in aquaculture, fisheries, and vertebrate physiology generally. Machine learning pattern recognition and sensitivity analysis were employed to examine metabolomic small molecule profiles and transcriptomic gene expression data generated from liver and white skeletal muscle of hybrid striped bass (white bass Morone chrysops x striped bass M. saxatilis) representative of the top and bottom 10 % by body size of a production cohort.

RESULTS

Larger fish (good-growth) had significantly greater weight, total length, hepatosomatic index, and specific growth rate compared to smaller fish (poor-growth) and also had significantly more muscle fibers of smaller diameter (≤ 20 µm diameter), indicating active hyperplasia. Differences in metabolomic pathways included enhanced energetics (glycolysis, citric acid cycle) and amino acid metabolism in good-growth fish, and enhanced stress, muscle inflammation (cortisol, eicosanoids) and dysfunctional liver cholesterol metabolism in poor-growth fish. The majority of gene transcripts identified as differentially expressed between groups were down-regulated in good-growth fish. Several molecules associated with important growth-regulatory pathways were up-regulated in muscle of fish that grew poorly: growth factors including agt and agtr2 (angiotensins), nicotinic acid (which stimulates growth hormone production), gadd45b, rgl1, zfp36, cebpb, and hmgb1; insulin-like growth factor signaling (igfbp1 and igf1); cytokine signaling (socs3, cxcr4); cell signaling (rgs13, rundc3a), and differentiation (rhou, mmp17, cd22, msi1); mitochondrial uncoupling proteins (ucp3, ucp2); and regulators of lipid metabolism (apoa1, ldlr). Growth factors pttg1, egfr, myc, notch1, and sirt1 were notably up-regulated in muscle of good-growing fish.

CONCLUSION

A combinatorial pathway analysis using metabolomic and transcriptomic data collectively suggested promotion of cell signaling, proliferation, and differentiation in muscle of good-growth fish, whereas muscle inflammation and apoptosis was observed in poor-growth fish, along with elevated cortisol (an anti-inflammatory hormone), perhaps related to muscle wasting, hypertrophy, and inferior growth. These findings provide important biomarkers and mechanisms by which growth is regulated in fishes and other vertebrates as well.

Combining supervised machine learning with statistics reveals differential gene expression patterns related to energy metabolism in the jejuna of chickens divergently selected for antibody response to sheep red blood cells

Since the 1970s, 2 lines of White Leghorn chickens, HAS and LAS, have been continuously divergently selected for 5-day postinjection antibody titer to injection with sheep red blood cells (SRBC). Antibody response is a complex genetic trait and characterizing differences in gene expression could facilitate better understanding of physiological changes due to selection and antigen exposure. At 41 d of age, randomly selected HAS and LAS chickens, which had been coraised from hatch, were either injected with SRBC (HASI and LASI) or kept as the noninjected cohort (HASN and LASN). Five days later, all were euthanized, and samples collected from the jejunum for RNA isolation and sequencing. Resulting gene expression data were analyzed combining traditional statistics with machine learning to obtain signature gene lists for functional analysis. Differences in ATP production and cellular processes were observed in the jejunum between lines and following SRBC injection. HASN vs. LASN exhibited upregulation of ATP production, immune cell motility, and inflammation. LASI exhibits upregulation of ATP production and protein synthesis vs. LASN, reflective of what was observed in HASN vs. LASN. In contrast, no corresponding upregulation of ATP production was observed in HASI vs. HASN, and most other cellular processes appear inhibited. Without exposure to SRBC, gene expression in the jejunum indicates HAS generates more ATP than LAS, suggesting HAS maintains a "primed" system; and gene expression of HASI vs. HASN further suggests this basal ATP production is sufficient for robust antibody responses. Conversely, LASI vs. LASN jejunal gene expression implies a physiological need for increased ATP production with only minimal correlating antibody production. The results of this experiment provide insight into energetic resource needs and allocations in the jejunum in response to genetic selection and antigen exposure in HAS and LAS which may help explain phenotypic differences observed in antibody response.

Discovery Proteomics and Absolute Protein Quantification Can Be Performed Simultaneously on an Orbitrap-Based Mass Spectrometer

Mass spectrometry (MS) has steadily moved into the forefront of quantification-centered protein research. Protein cleavage isotope dilution MS is a proven way for quantifying proteins by using an isotope-labeled analogue of a peptide fragment of the parent protein as an internal standard. Parallel reaction monitoring (PRM) has become the go-to approach for such quantification on an Orbitrap-based instrument as it is assumed that the instrument sensitivity is enhanced. We performed a comparative study on data-dependent acquisition (DDA) and PRM-based workflows to quantify egg yolk protein precursors or vitellogenins (VTGs) Aa, Ab, and C in striped bass (Morone saxatilis). VTG proportions serve as a developmental measure of egg quality, possibly changing with the environment, and have been studied as an indicator of the health of North Carolina stocks. Based on single-factor analysis of variance comparisons of mean VTG amounts across fish from the same sample groupings, our results indicate that there is no statistical difference between MS1-based and MS2-based VTG quantification. We further conclude that DDA is able to deliver both discovery data and absolute quantification data in the same experiment.

Differential bumble bee gene expression associated with pathogen infection and pollen diet

BACKGROUND

Diet and parasitism can have powerful effects on host gene expression. However, how specific dietary components affect host gene expression that could feed back to affect parasitism is relatively unexplored in many wild species. Recently, it was discovered that consumption of sunflower (Helianthus annuus) pollen reduced severity of gut protozoan pathogen Crithidia bombi infection in Bombus impatiens bumble bees. Despite the dramatic and consistent medicinal effect of sunflower pollen, very little is known about the mechanism(s) underlying this effect. However, sunflower pollen extract increases rather than suppresses C. bombi growth in vitro, suggesting that sunflower pollen reduces C. bombi infection indirectly via changes in the host. Here, we analyzed whole transcriptomes of B. impatiens workers to characterize the physiological response to sunflower pollen consumption and C. bombi infection to isolate the mechanisms underlying the medicinal effect. B. impatiens workers were inoculated with either C. bombi cells (infected) or a sham control (un-infected) and fed either sunflower or wildflower pollen ad libitum. Whole abdominal gene expression profiles were then sequenced with Illumina NextSeq 500 technology.

RESULTS

Among infected bees, sunflower pollen upregulated immune transcripts, including the anti-microbial peptide hymenoptaecin, Toll receptors and serine proteases. In both infected and un-infected bees, sunflower pollen upregulated putative detoxification transcripts and transcripts associated with the repair and maintenance of gut epithelial cells. Among wildflower-fed bees, infected bees downregulated immune transcripts associated with phagocytosis and the phenoloxidase cascade.

CONCLUSIONS

Taken together, these results indicate dissimilar immune responses between sunflower- and wildflower-fed bumble bees infected with C. bombi, a response to physical damage to gut epithelial cells caused by sunflower pollen, and a strong detoxification response to sunflower pollen consumption. Identifying host responses that drive the medicinal effect of sunflower pollen in infected bumble bees may broaden our understanding of plant-pollinator interactions and provide opportunities for effective management of bee pathogens.

Distinctive Cellular and Metabolic Reprogramming in Porcine Lung Mononuclear Phagocytes Infected With Type 1 PRRSV Strains

Porcine reproductive and respiratory syndrome (PRRS) has an extensive impact on pig production. The causative virus (PRRSV) is divided into two species, PRRSV-1 (European origin) and PRRSV-2 (North American origin). Within PRRSV-1, PRRSV-1.3 strains, such as Lena, are more pathogenic than PRRSV-1.1 strains, such as Flanders 13 (FL13). To date, the molecular interactions of PRRSV with primary lung mononuclear phagocyte (MNP) subtypes, including conventional dendritic cells types 1 (cDC1) and 2 (cDC2), monocyte-derived DCs (moDC), and pulmonary intravascular macrophages (PIM), have not been thoroughly investigated. Here, we analyze the transcriptome profiles of in vivo FL13-infected parenchymal MNP subpopulations and of in vitro FL13- and Lena-infected parenchymal MNP. The cell-specific expression profiles of in vivo sorted cells correlated with their murine counterparts (AM, cDC1, cDC2, moDC) with the exception of PIM. Both in vivo and in vitro, FL13 infection altered the expression of a low number of host genes, and in vitro infection with Lena confirmed the higher ability of this strain to modulate host response. Machine learning (ML) and gene set enrichment analysis (GSEA) unraveled additional relevant genes and pathways modulated by FL13 infection that were not identified by conventional analyses. GSEA increased the cellular pathways enriched in the FL13 data set, but ML allowed a more complete comprehension of functional profiles during FL13 in vitro infection. Data indicates that cellular reprogramming differs upon Lena and FL13 infection and that the latter might keep antiviral and inflammatory macrophage/DC functions silent. Although the slow replication kinetics of FL13 likely contribute to differences in cellular gene expression, the data suggest distinct mechanisms of interaction of the two viruses with the innate immune system during early infection.

Oogenesis and Egg Quality in Finfish: Yolk Formation and Other Factors Influencing Female Fertility

Egg quality in fishes has been a topic of research in aquaculture and fisheries for decades as it represents an important life history trait and is critical for captive propagation and successful recruitment. A major factor influencing egg quality is proper yolk formation, as most fishes are oviparous and the developing offspring are entirely dependent on stored egg yolk for nutritional sustenance. These maternally derived nutrients consist of proteins, carbohydrates, lipids, vitamins, minerals, and ions that are transported from the liver to the ovary by lipoprotein particles including vitellogenins. The yolk composition may be influenced by broodstock diet, husbandry, and other intrinsic and extrinsic conditions. In addition, a number of other maternal factors that may influence egg quality also are stored in eggs, such as gene transcripts, that direct early embryonic development. Dysfunctional regulation of gene or protein expression may lead to poor quality eggs and failure to thrive within hours of fertilization. These gene transcripts may provide important markers as their expression levels may be used to screen broodstock for potential spawning success. In addition to such intrinsic factors, stress may lead to ovarian atresia or reproductive failure and can impact fish behavior, fecundity, and ovulation rate. Finally, postovulatory aging may occur when eggs become overripe and the fish fails to spawn in a timely fashion, leading to low fertility, often encountered during manual strip spawning of fish.

Comparative Evaluation of MS-based Metabolomics Software and Its Application to Preclinical Alzheimer's Disease

Mass spectrometry-based metabolomics has undergone significant progresses in the past decade, with a variety of software packages being developed for data analysis. However, systematic comparison of different metabolomics software tools has rarely been conducted. In this study, several representative software packages were comparatively evaluated throughout the entire pipeline of metabolomics data analysis, including data processing, statistical analysis, feature selection, metabolite identification, pathway analysis, and classification model construction. LC-MS-based metabolomics was applied to preclinical Alzheimer's disease (AD) using a small cohort of human cerebrospinal fluid (CSF) samples (N = 30). All three software packages, XCMS Online, SIEVE, and Compound Discoverer, provided consistent and reproducible data processing results. A hybrid method combining statistical test and support vector machine feature selection was employed to screen key metabolites, achieving a complementary selection of candidate biomarkers from three software packages. Machine learning classification using candidate biomarkers generated highly accurate and predictive models to classify patients into preclinical AD or control category. Overall, our study demonstrated a systematic evaluation of different MS-based metabolomics software packages for the entire data analysis pipeline which was applied to the candidate biomarker discovery of preclinical AD.

DNA methylation profiles correlated to striped bass sperm fertility

Background

Striped bass (Morone saxatilis) spermatozoa are used to fertilize in vitro the eggs of white bass (M. chrysops) to produce the preferred hybrid for the striped bass aquaculture industry. Currently, only one source of domestic striped bass juveniles is available to growers that is not obtained from wild-caught parents and is thus devoid of any genetic improvement in phenotypic traits of importance to aquaculture. Sperm epigenetic modification has been predicted to be associated with fertility, which could switch genes on and off without changing the DNA sequence itself. DNA methylation is one of the most common epigenetic modification types and changes in sperm epigenetics can be correlated to sub-fertility or infertility in male striped bass. The objective of this study was to find the differentially methylated regions (DMRs) between high-fertility and sub-fertility male striped bass, which could potentially regulate the fertility performance.

Results

In our present study, we performed DNA methylation analysis of high-fertility and sub-fertility striped bass spermatozoa through MBD-Seq methods. A total of 171 DMRs were discovered in striped bass sperm correlated to fertility. Based on the annotation of these DMRs, we conducted a functional classification analysis and two important groups of genes including the WDR3/UTP12 and GPCR families, were discovered to be related to fertility performance of striped bass. Proteins from the WDR3/UTP12 family are involved in forming the sperm flagella apparatus in vertebrates and GPCRs are involved in hormonal signaling and regulation of tissue development, proliferation and differentiation.

Conclusions

Our results contribute insights into understanding the mechanism of fertility in striped bass, which will provide powerful tools to maximize reproductive efficiencies and to identify those males with superior gametes for this important aquaculture species.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4548-6) contains supplementary material, which is available to authorized users.

Aquaculture genomics, genetics and breeding in the United States: current status, challenges, and priorities for future research

Advancing the production efficiency and profitability of aquaculture is dependent upon the ability to utilize a diverse array of genetic resources. The ultimate goals of aquaculture genomics, genetics and breeding research are to enhance aquaculture production efficiency, sustainability, product quality, and profitability in support of the commercial sector and for the benefit of consumers. In order to achieve these goals, it is important to understand the genomic structure and organization of aquaculture species, and their genomic and phenomic variations, as well as the genetic basis of traits and their interrelationships. In addition, it is also important to understand the mechanisms of regulation and evolutionary conservation at the levels of genome, transcriptome, proteome, epigenome, and systems biology. With genomic information and information between the genomes and phenomes, technologies for marker/causal mutation-assisted selection, genome selection, and genome editing can be developed for applications in aquaculture. A set of genomic tools and resources must be made available including reference genome sequences and their annotations (including coding and non-coding regulatory elements), genome-wide polymorphic markers, efficient genotyping platforms, high-density and high-resolution linkage maps, and transcriptome resources including non-coding transcripts. Genomic and genetic control of important performance and production traits, such as disease resistance, feed conversion efficiency, growth rate, processing yield, behaviour, reproductive characteristics, and tolerance to environmental stressors like low dissolved oxygen, high or low water temperature and salinity, must be understood. QTL need to be identified, validated across strains, lines and populations, and their mechanisms of control understood. Causal gene(s) need to be identified. Genetic and epigenetic regulation of important aquaculture traits need to be determined, and technologies for marker-assisted selection, causal gene/mutation-assisted selection, genome selection, and genome editing using CRISPR and other technologies must be developed, demonstrated with applicability, and application to aquaculture industries.Major progress has been made in aquaculture genomics for dozens of fish and shellfish species including the development of genetic linkage maps, physical maps, microarrays, single nucleotide polymorphism (SNP) arrays, transcriptome databases and various stages of genome reference sequences. This paper provides a general review of the current status, challenges and future research needs of aquaculture genomics, genetics, and breeding, with a focus on major aquaculture species in the United States: catfish, rainbow trout, Atlantic salmon, tilapia, striped bass, oysters, and shrimp. While the overall research priorities and the practical goals are similar across various aquaculture species, the current status in each species should dictate the next priority areas within the species. This paper is an output of the USDA Workshop for Aquaculture Genomics, Genetics, and Breeding held in late March 2016 in Auburn, Alabama, with participants from all parts of the United States.

In-Depth Characterization and Validation of Human Urine Metabolomes Reveal Novel Metabolic Signatures of Lower Urinary Tract Symptoms

Lower urinary tract symptoms (LUTS) are a range of irritative or obstructive symptoms that commonly afflict aging population. The diagnosis is mostly based on patient-reported symptoms, and current medication often fails to completely eliminate these symptoms. There is a pressing need for objective non-invasive approaches to measure symptoms and understand disease mechanisms. We developed an in-depth workflow combining urine metabolomics analysis and machine learning bioinformatics to characterize metabolic alterations and support objective diagnosis of LUTS. Machine learning feature selection and statistical tests were combined to identify candidate biomarkers, which were statistically validated with leave-one-patient-out cross-validation and absolutely quantified by selected reaction monitoring assay. Receiver operating characteristic analysis showed highly-accurate prediction power of candidate biomarkers to stratify patients into disease or non-diseased categories. The key metabolites and pathways may be possibly correlated with smooth muscle tone changes, increased collagen content, and inflammation, which have been identified as potential contributors to urinary dysfunction in humans and rodents. Periurethral tissue staining revealed a significant increase in collagen content and tissue stiffness in men with LUTS. Together, our study provides the first characterization and validation of LUTS urinary metabolites and pathways to support the future development of a urine-based diagnostic test for LUTS.

Mechanisms of Egg Yolk Formation and Implications on Early Life History of White Perch (Morone americana)

The three white perch (Morone americana) vitellogenins (VtgAa, VtgAb, VtgC) were quantified accurately and precisely in the liver, plasma, and ovary during pre-, early-, mid-, and post-vitellogenic oocyte growth using protein cleavage-isotope dilution mass spectrometry (PC-IDMS). Western blotting generally mirrored the PC-IDMS results. By PC-IDMS, VtgC was quantifiable in pre-vitellogenic ovary tissues and VtgAb was quantifiable in pre-vitellogenic liver tissues however, neither protein was detected by western blotting in these respective tissues at this time point. Immunohistochemistry indicated that VtgC was present within pre-vitellogenic oocytes and localized to lipid droplets within vitellogenic oocytes. Affinity purification coupled to tandem mass spectrometry using highly purified VtgC as a bait protein revealed a single specific interacting protein (Y-box binding protein 2a-like [Ybx2a-like]) that eluted with suramin buffer and confirmed that VtgC does not bind the ovary vitellogenin receptors (LR8 and Lrp13). Western blotting for LR8 and Lrp13 showed that both receptors were expressed during vitellogenesis with LR8 and Lrp13 expression highest in early- and mid-vitellogenesis, respectively. The VtgAa within the ovary peaked during post-vitellogenesis, while VtgAb peaked during early-vitellogenesis in both white perch and the closely related striped bass (M. saxatilis). The VtgC was steadily accumulated by oocytes beginning during pre-vitellogenesis and continued until post-vitellogenesis and its composition varies widely between striped bass and white perch. In striped bass, the VtgC accounted for 26% of the vitellogenin-derived egg yolk, however in the white perch it comprised only 4%. Striped bass larvae have an extended developmental window and these larvae have yolk stores that may enable them to survive in the absence of food for twice as long as white perch after hatch. Thus, the VtgC may play an integral role in providing nutrients to late stage fish larvae prior to the onset of exogenous feeding and its composition in the egg yolk may relate to different early life histories among this diverse group of animals.

Ovarian yolk formation in fishes: Molecular mechanisms underlying formation of lipid droplets and vitellogenin-derived yolk proteins

Fish egg yolk is largely derived from vitellogenins, which are synthesized in the liver, taken up from the maternal circulation by growing oocytes via receptor-mediated endocytosis and enzymatically processed into yolk proteins that are stored in the ooplasm. Lipid droplets are another major component of fish egg yolk, and these are mainly composed of neutral lipids that may originate from maternal plasma lipoproteins. This review aims to briefly summarize our current understanding of the molecular mechanisms underlying yolk formation in fishes. A hypothetical model of oocyte growth is proposed based on recent advances in our knowledge of fish yolk formation.

Machine learning reveals sex-specific 17β-estradiol-responsive expression patterns in white perch (Morone americana) plasma proteins

With growing abundance and awareness of endocrine disrupting compounds (EDCs) in the environment, there is a need for accurate and reliable detection of EDC exposure. Our objective in the present study was to observe differences within and between the global plasma proteomes of sexually mature male and female white perch (Morone americana) before (Initial Control, IC) and after 17β-estradiol (E2 ) induction. Semiquantitative nanoLC-MS/MS data were analyzed by machine learning support vector machines (SVMs) and by two-way ANOVA. By ANOVA, the expression levels of 44, 77, and 57 proteins varied significantly by gender, treatment, and the interaction of gender and treatment, respectively. SVMs perfectly classified male and female perch IC and E2 -induced plasma samples using the protein expression data. E2 -induced male and female perch plasma proteomes contained significantly higher levels of the yolk precursors vitellogenin Aa and Ab (VtgAa, VtgAb), as well as latrophilin and seven transmembrane domain-containing protein 1 (Eltd1) and kininogen 1 (Kng1). This is the first report that Eltd1 and Kng1 may be E2 -responsive proteins in fishes and therefore may be useful indicators of estrogen induction.

One-dimensional proteomic profiling of Danio rerio embryo vitellogenin to estimate quantum dot toxicity

BACKGROUND

Vitellogenin (Vtg) is the major egg yolk protein (YP) in most oviparous species and may be useful as an indicator in ecotoxicological testing at the biochemical level. In this study, we obtained detailed information about the Vtgs of Danio rerio embryos by cutting SDS-PAGE gel lanes into thin slices, and analyzing them slice-by-slice with (MALDI-TOF) mass spectrometry.

RESULTS

We conducted three proteomic analyses, comparing embryonic Danio rerio Vtg cleavage products after exposure for 48 h to CdSecore/ZnSshell quantum dots (QDs), after exposure to a mixture of the components used for quantum dot synthesis (MCS-QDs), and in untreated embryos. The Vtg mass spectrometric profiles of the QDs-treated embryos differed from those of the unexposed or MCS-QDs-treated embryos.

CONCLUSION

This study demonstrates the possible utility of Vtg profiling in D. rerio embryos as a sensitive diagnostic tool to estimate nanoparticle toxicity.