Performing Department
(N/A)
Non Technical Summary
Bovine leukemia virus (BLV) presents a significant challenge for the U.S. dairy industry, infecting approximately 84% of dairy herds and causing economic losses estimated at up to$2.7 billion annuallydue to reduced milk production. Beyond the direct impact on agriculture, this issue resonates through the economy as it affects rural employment and dairy product prices, influencing community welfare and the environment. Most infected cattle do not exhibit symptoms but can spread the virus, complicating efforts to control the disease and posing a persistent threat to herd health. Moreover, about 5% of these infections lead to fatal diseases in cows, exacerbating the economic and emotional burden on farmers.Our research is not just another study on BLV. We are delving into how this infection affects cow immune systems by examining changes in the blood cells at a molecular level. To do this, we are employing cutting-edge techniques like single-cell RNA sequencing. This advanced method allows us to look at individual cells and understand the diverse impacts of the virus, providing a detailed picture that typical studies do not. By focusing on B-cells, which are crucial for a healthy immune response, we aim to uncover how the virus alters immune cell function. The insights gained from this innovative approach will pinpoint specific weaknesses in the immune system caused by BLV, guiding the development of targeted treatments and management strategies to mitigate these effects.The ultimate goal of this project is to enhance the health and productivity of dairy cows, thereby improving the economic stability of dairy farms and reducing the prices of dairy products. Based on our findings, successful management and potential reduction of BLV prevalence could lead to healthier herds, decreased use of antibiotics, and a lower environmental impact from farming operations. This research aims to bolster the agricultural economy and safeguard public health by controlling a virus that could impact other animals and ecosystems. The project promises substantial societal benefits by achieving these outcomes, including enhanced food security and economic resilience in rural communities.
Animal Health Component
100%
Research Effort Categories
Basic
70%
Applied
30%
Developmental
0%
Goals / Objectives
Our proposal goal is to define how BLV infection and its progression change PBMC transcriptional heterogeneity and define mechanisms of B-cell dysfunction in infected dairy cows.
Project Methods
Thisproject will employ a structured approach to study bovine leukemia virus (BLV) infection in dairy cows, specifically examining transcriptional differences in peripheral blood mononuclear cells (PBMCs) and B-cell dysfunction.Overall design:Animals and study design: First, clinically healthy, mid-lactation (~150 DIM) Holstein dairy cows in their 3rd or 4th lactations from a single dairy farm in West Texas will be screened for blood BLV antibodies, PVL, and lymphocyte count (LC). Control, non-infected cattle (BLV-) will have no BLV antibodies/PVL detected in blood. BLV-infected cows (BLV+) will have detectable BLV antibodies and PVL in blood. Second, BLV+ cows will be grouped based on PVL categories, as previously reported: Low PVL (<16,000 copies of provirus), moderate PVL (>16,000 to < 50,000 copies), and high PVL (>50,000 copies). The initial number of cows to be sampled for BLV screening will be based on these estimates.BLV, PVL, and LC screening: Whole blood (EDTA) and serum samples will be collected by coccygeal venipuncture using Vacutainer needles and tubes and will be tested for BLV antibodies by ELISA (Antel Biosystems). Lymphocytes will be quantified during a whole blood differential white blood cell count using Qscout (Advanced Animal Diagnostics). PVL quantification will be performed using blood DNA (DNeasy Blood/ Tissue Kit -Qiagen) through a SS1 qPCR assay in a QuantStudio 6 Pro Fast Real-Time PCR (Life Tech.).PBMC isolation: PBMCs will be isolated from 8mL of blood collected by coccygeal venipuncture in ACD-containing tubes (Becton Dickinson) using Ficoll-Paque Plus Density Gradient Media.Aim 1: Identify how BLV infection affects the transcriptional heterogeneity of PBMCs in dairy cows.Single-cell library preparation and RNA sequencing: PBMCs will be prepared and sequenced using 10X Genomics and Illumina NovaSeq 6000 technologies at Texas Tech University to target 10,000 cells per sample, aiming for a depth of 30,000 read pairs per cell. The resultant data will be processed using Bcl2fastq2 and CellRanger software to produce de-multiplexed Fastq files and aligned count matrices. Data analysis will be conducted in R Studio using Seurat, focusing on filtering, PCA, and UMAP clustering to explore gene expression variations and cellular differences between BLV- and BLV+ cows. These analyses will include pathway assessments via clusterProfiler to understand impacts on biological pathways using rigorous statistical corrections.Aim 2: Delineate mechanisms of B-cell dysfunction in BLV-infected dairy cows.Experiment #1: How does BLV infection affect B-cell-specific transcriptome?Sample size: Sample size calculation was performed using the PROC POWER procedure in SAS 9.4 based on a two-sample t-test for mean difference.We used B-cell frequency (means ± SD) obtained from PBMCs by flow cytometry from BLV-infected cows.Assuming a 2-sided confidence interval of 95%, 80% power, calculations resulted in a n of 10 cows per group (BLV+ vs. BLV-) for each experiment.Sorting strategy for B- and T-cells: Isolated PBMCs will be resuspended in FACS buffer (0.1% BSA PBS) and labeled with anti-bovine fluorescent antibodies. B-cells will be CD19+SIgM+MHCII+, and T-cells will be CD4+CD8-. Sorting gates will be set by FMO, and unstained controls will be installed in a BD FACS Aria II sorter equipped with five lasers for multicolor cell sorting.Isolation of BLV-infected B-cells for transcriptomics: We will use BLV gp51, a BLV surface glycoprotein, for isolating BLV-infected B-cells by FACS. Briefly, PBMCs at 5x106cells/ml will be fixed and permeabilized with 4% PFA and 0.1% saponin in molecular grade PBS supplemented with 1:100 RNase Inhibitor (Promega, N2615) for 30 min at 4C.Next, PBMCs will be stained with primary antibodies for BLV Anti-gp51 (VMRD), CD19, SIgM, and MHCII in PBS with 1% BSA, 0.1% saponin and 1:25 RNase inhibitor. The same procedure will be used for secondary antibodies. Sorted infected B-cells will be CD19+SIgM+MHCII+gp51+, and non-infected B-cells will be CD19+SIgM+MHCII+gp51-.B-cell RNA extraction and sequencing: B-cell RNA will be extracted (RNeasy Micro Kit-Qiagen) and integrity assessed in Bioanalyzer 2100 (Agilent Tech.) After cDNA synthesis, PCR products from BLV-infected and non-infected B-cell samples will be purified (AMPure XP system) and library quality assessed. Library preparations will be sequenced on an Illumina Novaseq 6000 S4 platform to generate 30 million paired-end reads (2 x 150 nt) per sample. Data analysis will be performed as described in preliminary data, with differentially expressed gene (DEG) identification and enrichment analysis (GO and KEGG) being the primary strategies.Experiment # 2 How does BLV infection affect B- and T-cell crosstalk?B- and T-cells Co-culture: We will conduct co-culture experiments using PBMC-isolated B-cells and CD4+ T-cells to study the impact of BLV infection on T-cell activation. CD4+ T-cells from BLV-negative cows will be co-cultured with B-cells from either BLV-negative or BLV-positive cows with high proviral load and persistent lymphocytosis. Controls will include T-cells activated with concanavalin A, inhibited with anti-CD3/CD28 antibodies, and B-cells cultured with or without immune stimulants IL-21 and CpG-ODN. After isolation via FACS and preparation in RPMI-1640 medium, the cells will be cultured in 24-well plates and incubated. Cell mixtures and supernatants will be collected at 0, 24, 48, and 72 hours for analysis.Data analysis: All in vitro conditions will be assessed in duplicates and standardized by cell number. Statistical analysis will be performed in SAS (v.9.4, SAS Institute Inc., Cary, NC). Data will be tested for normality and homoscedasticity and adjusted accordingly. Linear mixed models will determine the effect of BLV, time course (Exp.2), and their interaction on assay outcomes. Cow will be included as a random factor in the model. Correlation and regression analyses will assess associations between the frequency of BLV-infected B-cells and cytokine and antibody profiles, B-cell proliferation, and anergy markers. Post-hoc pairwise comparisons will be performed using Bonferroni's correction for multiple testing.Efforts:This project will create numerous educational opportunities for undergraduate and graduate students in animal and human health sciences fields by incorporating laboratory instruction and practical experiences. Specific classroom content willbe developedfor courses in internal medicine, molecular biology, and large animal clinics, all aimed at deepening understanding of bovine leukemia virus (BLV) infection mechanisms. Furthermore, a significant mid-term goal of this research is to identify BLV-specific cellular targets for potential therapeutic interventions, which could lead to innovative nutritional and medical strategies to manage this infection in dairy herds.Evaluation:The outcomes of this BLV-focused project willbe assessedthrough the following milestones:Successful identification of distinct transcriptional profiles within peripheral blood mononuclear cells (PBMCs) of BLV-infected dairy cows.Determination of how BLV infection influences specific cell subpopulations, evidenced by changes in their transcriptomes and functions.Compilation and publication of open-access datasets on the single-cell transcriptomes of PBMCs from BLV-infected cows.Novel isolation and detailed in vitro characterization ofkeyimmune cell subpopulations implicated in BLV pathology.Completingat least one master's thesis in Animal Science, focusing on BLV research.The findings will be disseminated through presentations at at least two scientific conferences and the publication of at least two peer-reviewed research articles.