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. 2026 Feb 6;21(2):e0328428. doi: 10.1371/journal.pone.0328428

Transport stress induces paradoxical increases in airway inflammatory responses in beef stocker cattle

Grace M Jakes 1,#, Dylan T Ammons 1,#, Randy Hunter 2,#, Steven Dow 1,3,*, Sarah M Raabis 3,*
Editor: Angel Abuelo4
PMCID: PMC12880702  PMID: 41650133

Abstract

The development of Bovine Respiratory Disease (BRD) in beef cattle is associated with stressful events, including auction and transport. In addition to the effects of commingling on pathogen exposure, stress also impacts immune function and has classically been associated with an immunosuppressed state. Much of the research on cattle immunity in stress has focused on peripheral blood immune functionality rather than mucosal immune responses. To characterize immunity at the primary site of pathogen colonization in BRD, we evaluated stress responses in lung cells from beef stocker cattle to understand mucosal immune changes. Stocker calves were sampled via bronchoalveolar lavage fluid (BALF) collection within 24 hours of auction and transport to a new facility (Stressed, n = 12), or allowed to acclimate for 2 months at the new facility before sampling (Acclimated, n = 7). Lavage cellular RNA was extracted and sequenced for bulk RNA-seq gene expression. Differential gene expression analysis of RNA sequencing data demonstrated a profound upregulation of inflammatory genes in Stressed calves compared to Acclimated calves, including expression of CXCL8, CSF3R, IL1B, and CCL22. Top pathway upregulation in Stressed calves involved neutrophil migration and chemotaxis, and cytokine signaling. To predict cellular population proportions from the data, CIBERSORTx was used to deconvolute bulk RNA-seq gene counts. This analysis showed that Stressed calves had significantly increased BALF neutrophils compared to Acclimated calves (p = 0.003). Neutrophilic infiltration occurred in the absence of pathogen colonization of the lungs in most calves, as demonstrated by a multi-pathogen respiratory qPCR screen. As such, the stress induced an inflammatory response in lungs not explained by pathogen exposure. This study provides strong evidence that shipping stress in beef stocker calves can trigger increased inflammatory pulmonary mucosal immune responses, which has important implications for the pathogenesis of BRD.

Introduction

Bovine respiratory disease (BRD) is the leading cause of morbidity and mortality in beef cattle raised in the United States [1,2]. One of the major risk factors for BRD is the stress of transport and commingling at a new facility, where cases typically peak in the first weeks following arrival [35]. Given the fact that transport and commingling are experienced by the vast majority of U.S. beef cattle [1,6], understanding the mechanisms of immune regulation following these stressors is imperative to mitigate disease. Stress has classically been considered immunosuppressive due to the down-modulatory effects of stress-induced glucocorticoids on inflammatory and lymphocyte responses [7]. Glucocorticoids regulate inflammatory responses principally through the downregulation of NFκB-mediated signaling [7], which in turn mitigates the production of proinflammatory cytokines including TNF-α [8], IL-1β [9], IL-6 [10], and IL-8 [11] across species and cell classes. Additionally, glucocorticoids attenuate lymphocyte responses and serve as pro-apoptotic factors to reduce lymphocytes in circulation [12]. In the peripheral blood, stress in cattle has been demonstrated to delay humoral responses to vaccination [13].

However, the effects of shipping stress on mucosal immune responses in the lungs have not been thoroughly evaluated, and it remains possible that pulmonary immune responses may differ from peripheral immune responses in stressed cattle. While stress is thought to decrease lymphocyte functionality [5], immune responses are not always attenuated in cattle following stress. For example, transit stress is known to increase cellular recruitment to the lung following LPS challenge in cattle [14], and additive stressors such as weaning and transport can result in greater systemic inflammatory responses and increased mortality in experimental infection [15]. Cattle in the first weeks following arrival at a new facility can express higher levels of inflammatory cytokines in the peripheral blood [16], and in response to stimulation [17]. However, it is unclear if this is in response to immunosuppression and greater pathogen colonization in the lower airway, or if there are other mechanisms where stress can upregulate inflammatory and cellular recruitment responses. Increasingly, studies in humans and mice have demonstrated that acute and chronic stressors can upregulate systemic inflammatory responses in the absence of overt pathogen challenge [1821], and that this may in turn affect mucosal tissues such as the gastrointestinal tract and lung.

New insights into immune regulation in stressed cattle can be limited by a number of factors, one of the greatest of which is the lack of reagents for cell analysis by flow cytometry or for cytokine analysis by ELISA. Recently, with the advent of bulk transcriptomic mRNA sequencing (RNA-seq) technologies, global immune regulation can be evaluated to determine host responses to physiologic stressors. In cattle, RNA-seq has been used to predict gene expression patterns in the peripheral blood which are associated with increased risk of BRD development [22]. Other studies have demonstrated that modulation of lung immune responses in experimental infection can result in improved calf morbidity and mortality outcomes [23]. These studies have highlighted that an excess of inflammatory immune responses is often linked with more severe morbidity.

In the current study, we sought to increase our understanding of mucosal immune responses in the lungs following shipping stress by leveraging RNA-seq to determine pathways of immune regulation. Our hypothesis was that transported calves would experience an increase in systemic stress markers including cortisol, haptoglobin, and serum amyloid A, and that adaptive immune responses would be attenuated at the mucosal surface in the lungs following shipping stress, resulting in an increase in pathogen recovery in the lower airway. The findings reported here provide unexpected results regarding the nature of mucosal immune regulation in cattle following auction and transport stress and demonstrate that inflammation rather than immunosuppression predominates in calves after stress, even in the absence of detectable pathogen colonization of the lower airway. These findings provide important context for the understanding of immune responses leading to BRD risk in cattle.

Materials and methods

Study population

Beef calves (5–6 months of age) were comingled and purchased at auction and transported 228 miles to a commercial backgrounding operation (Wheatland, WY). The first group of calves was sampled within 24 hours of arrival at the backgrounding facility before vaccination and branding (Stressed), and the second group of calves was sampled after 2 months at the facility (Acclimated, Fig 1). Calves arrived at the backgrounder in separate shipments, allowing for random sampling throughout the backgrounding period. A power analysis was conducted based on expected differences in systemic acute phase protein levels, as they are validated markers associated with immune activation and the stress response. The power analysis was conducted in R using the pwr package [24] for a two-sample t-test with a Cohen’s d of 1.4, expected 5-fold difference in mean levels of acute phase proteins (including lipopolysaccharide binding protein (LBP), serum amyloid A (SAA), and haptoglobin), and significance set to 0.05 [25]. This yielded a desired sample size of 9 per group. To account for expected proportions of calves that would go on to develop BRD from the Stressed group, additional Stressed calves were sampled for a total of 12 Stressed calves. Calves were not administered metaphylactic antibiotics at any time during the study. All calves were administered the following vaccinations according to label instructions: Pyramid 3 + Presponse SQ® (Bovine Viral Diarrhea Virus types 1 and 2, Bovine Herpes Virus 1 and Mannheimia Haemolytica toxoid, BI Animal Health), as well as Vision 7® (7-way Clostridium spp.vaccine, Merck Animal Health) at receiving. Calves were managed on pasture for the duration of the backgrounding period (approximately 7 months), and health evaluation was conducted by pen riders. All procedures in the study were approved by the Colorado State University Institutional Animal Care and Use Committee (IACUC protocol # 5749), with all BALF collected using veterinarian-administered xylazine (as described in the Sample Acquisition and Health Screening section), and every effort made to reduce animal suffering.

Fig 1. Study design.

Fig 1

Healthy stressed calves (n = 12) were sampled within 24 hours of arrival at the backgrounding facility. Healthy acclimated calves (n = 7) were likewise sampled after 2 months at the backgrounding facility and BALF was processed for sequencing analysis. Stressed calves who experienced BRD signs in the first 14 days at the facility were sampled a second time just prior to first BRD treatment to determine the etiology of infection. Figure created using Biorender.

Sample acquisition and health screening

Calves were handled according to humane best handling practices, and all sampling and health screening was performed using a Silencer® chute. Bronchoalveolar lavage fluid was collected from healthy calves. Exclusion criteria included an elevated rectal temperature (>39.7 °C), at least 1 cm2 of lung consolidation on ultrasound, or clinical signs consistent with BRD, including spontaneous cough, and moderate to severe nasal or ocular discharge [26]. Lung ultrasound was performed with an Ibex Pro® 5–9 MHz rectal linear probe (E.I. Medical Imaging®, Loveland, CO) by author SR, as previously described [27], with the exception that the right cranial lung lobe could not be consistently evaluated due to limitations of the chute design. Due to logistical reasons, only 7 calves were sampled from the Acclimated group. BALF sampling was conducted in standing animals sedated with xylazine (20 mg/ml Ana-Sed®) at 0.01 mg/kg IV. A 5 Fr red rubber catheter (JorVetTM) was inserted into both nares to apply 100–160 mg lidocaine (20 mg/ml VetOne®) to the arytenoids. A sterile cuffed bronchoalveolar lavage catheter (MILA® BAL 240 cm) was passed through the ventral meatus, arytenoids and into the trachea with visualization using a modified video endoscope (S.E.C Repro®). When the catheter reached a terminal bronchus, a 30 cc balloon was inflated and 120 ml of sterile saline was instilled prior to removing the BALF sample. BALF samples were immediately placed on ice until processing at the laboratory (approx. 4 hours). Following BALF collection, peripheral blood was collected for serum analysis (haptoglobin, SAA, LBP, cortisol) via jugular venipuncture and placed on ice until processing at the laboratory.

Acclimated calves were evaluated for BRD signs including reduced rumen fill, nasal discharge, and depressed attitude before sampling and after sampling by trained pen riders. Acclimated calves were excluded from the study if they were ever pulled for BRD treatment prior to the 2-month sampling timepoint. Calves in the acclimated group were never pulled by pen riders for clinical signs consistent with BRD. Stressed calves were likewise evaluated for BRD by trained pen riders after sample collection for the remainder of the backgrounding period. During the study, several Stressed calves developed BRD signs in the first two weeks after arrival. Any previously sampled calf displaying BRD signs was pulled and screened for elevated rectal temperature >39.7 °C and lung consolidation on ultrasound. Calves meeting either of these criteria were then sampled for BALF and treated with tulathromycin and ketoprofen intramuscular injection (Draxxin® KP, Zoetis, Parsippany-Troy Hills, NJ). Two stressed calves experienced BRD signs more than 6 weeks after arrival to the facility and could not be sampled for BALF due to technical reasons. BALF samples were handled as above and screened for major BRD pathogens by qPCR (as below). Stressed calves who remained healthy after arrival were not pulled for sampling again subsequent to the initial sampling timepoint. For the purpose of downstream RNA-seq analysis, calves were classified as having developed BRD if signs were noted within the first two weeks at the facility.

Sample processing

Prior to filtering and centrifugation, a ~ 2 ml aliquot of BALF was saved for qPCR analysis for major BRD pathogens. BALF samples were filtered through a sterile 70 μm filter and immune cells were pelleted by centrifugation at 500 x g for 10 minutes. BALF supernatant was removed, and RNA was extracted from cells using the RNeasy Mini Kit (Qiagen, Hilden Germany). Blood was allowed to clot and then centrifuged at 3000 x g for 5 minutes. Serum was separated and stored at −80 °C until further analysis.

qPCR analysis of BALF

BALF samples were analyzed at the Iowa State University Veterinary Diagnostic Laboratory via qPCR for BRD pathogens, including Mannheimia haemolytica, Pasteurella multocida, Histophilus somni, Mycoplasma bovis, Bovine Herpes Virus 1, Bovine Viral Diarrhea Virus, Bovine Respiratory Syncytial Virus, and Bovine Coronavirus. Threshold cycle (Ct) values were collected for each pathogen, with the positivity threshold set to <35. For animals who later went on to develop BRD, a second BALF sample was collected at the time of diagnosis and screened for pathogens using the same qPCR panel.

Serum cortisol and acute phase protein assessment

Serum haptoglobin, serum LBP, SAA, and serum cortisol levels were assessed using commercially available kits (haptoglobin: Immunology Consultants Laboratory, Inc. E-10HPT; LBP: Hycult Biotech; SAA: Tridelta Development Ltd.; cortisol: Seimens Diagnostics) according to manufacturer’s instructions. All samples and standards were plated in duplicate.

Sequencing

RNA libraries were sequenced by Novogene Corp. using an Illumina Novaseq 6000 platform (Novogene Co., Sacramento, CA). RNA quality was evaluated using an Agilent 2100 Bioanalyzer system to verify minimum RNA integrity levels.

Libraries were sequenced on an Illumina PE150 (Novaseq) platform for 40M raw reads per sample. Raw data were filtered using Fastp (version 0.23.2) by removing reads containing adapters and for Phred scores >30. The filtered reads were then aligned with STAR (version 2.7.10b), ARS-UCD1.3 genome assembly. Aligned reads were annotated and counted using FeatureCounts (version 2.0.1), and differentially expressed genes were identified using DEseq2. Further biological interpretations including gene ontology enrichment and gene set enrichment analysis were then performed using clusterProfiler [28].

CIBERSORTx analysis: cell identity and proportion prediction

To predict BALF cell population proportions, the CIBERSORTx software was used to deconvolute bulk RNA-seq gene counts. Briefly, a prior bovine BALF single-cell dataset was annotated and used as the “ground-truth” reference for the bulk gene counts expressed in the present study. Five of the Acclimated cattle had paired single-cell and bulk RNA-seq data, which were used as a reference for deconvolution, and to evaluate the accuracy of deconvolution. To predict cellular proportions, a gene count matrix including identity assignment of major immune cell subsets was imported into the CIBERSORTx software. Raw gene counts were imported into the software from Stressed and Acclimated calves, and ν-support vector regression with constraints was performed to find the best set of cell fractions whose weighted combination of gene expression best explained the bulk data. Single-cell reference uniform manifold approximation and projection (UMAP), as well as visual representation of cell population marker expression can be found in S1 Fig. Cell identity assignment for the single-cell reference was performed using classical surface marker and transcription factors for each major cell population. Table 1 contains a select representation of key markers used to define each cellular population. A complete list of up and down regulated markers (genes) defining each major cell cluster included in the CIBERSORTx matrix can be found in S1 Table.

Table 1. Key cellular markers defining major immune cell populations.

Major Cell Cluster Up-Regulated Markers Down-Regulated/Negative Markers
Macrophage CD163, SIRPA, MERTK CD3E, PAX5, CSF3R, TOP2A
Cycling Macrophage CD163, SIRPA, TOP2A, MKI67 CD3E, PAX5, CSF3R,
CD4 Tcell CD3E, LCK, CD4 CD163, PAX5, CSF3R, CD8
CD8 Tcell CD3E, GZMA, CD8 CD163, PAX5, CSF3R, CD4
NK Cell NCR1, KLRB1, KLRF1 CD163, PAX5, CSF3R, CD3E
NK Tcell CD3E, CD8, KLRK1, NKG2A CD163, PAX5, CSF3R, NCR1
γδ Tcell (gd Tcell) CD3E, WC1, RORA CD163, PAX5, CSF3R, CD4
Neutrophil CSF3R, IFIT3, SELL, SIRPA CD163, PAX5, CD3E, TOP2A
B Cell PAX5, MS4A1, HLA-DRA, CD19 CD163, CD3E, CSF3R, TOP2A

Two batch correction methods (noBatch, bBatch), which account for the bias of cell population prediction based on the single-cell assay type used, were evaluated. Percent similarity matrices for each batch correction method were used to determine the best batch correction method for this dataset, and to evaluate the accuracy of the cellular proportion prediction (S2 Fig). Correlation R2 values were calculated between the “ground truth” single-cell references and the bulk sequencing data and can be found in S3 Fig. Based on these two analyses, we elected to use the bBatch correction method to account for assay-induced single-cell population proportion prediction bias.

Statistical analysis

Statistical analyses for serum cortisol, acute phase proteins, clinical data, and an odds ratio were completed with Prism8 software (GraphPad) using the Mann-Whitney U test or a Student's t-test and the Fisher's exact test, respectively. The results are shown as the mean + /- SD (unless otherwise stated), with the significance set at p < 0.05. The normality of the data was examined using the Shapiro-Wilk normality test, and Welch’s correction was used for all t-tests where the standard deviation between groups significantly differed. Differentially expressed gene (DEG) calculations for RNA-seq were computed with DEseq2 using the Wald test, with significance denoted as a fold change > 2 and p-value with false discovery rate (FDR) < 0.05.

Results

Serum stress responses

To characterize stress responses between calves immediately following auction and transport (Stressed) and calves that had been allowed to acclimate for two months to the facility (Acclimated), we evaluated serum acute phase protein and cortisol levels. This demonstrated a >4-fold mean increase in serum haptoglobin in Stressed calves (4.44 ± 1.72 μg/ml difference, p = 0.02, Fig 2a), and a 9-fold mean increase in SAA (87.43 ± 17.59 μg/ml difference, p < 0.001, Fig 2b). LBP and cortisol levels did not differ between the two groups (p = 0.42, p = 0.92, S1 Fig).

Fig 2. Acute phase protein responses a) Serum haptoglobin levels between Stressed and Acclimated calves.

Fig 2

b) SAA levels between Stressed and Acclimated calves.

Health and Assessment of BRD pathogen burden by qPCR

At the time of sampling, calf mean rectal temperatures did not differ between groups (p = 0.27, S5 Fig). Levels of respiratory pathogens in BALF from calves were assessed by qPCR and are presented in Table 2. A full list of treatments and sampling relative to arrival are presented in S2 Table. One Stressed calf and one Acclimated calf were positive for at least one respiratory pathogen at sampling, although they did not exhibit signs of respiratory infection. Three Stressed calves later went on to develop BRD signs in the first two weeks at the facility and were sampled again for pathogen screening. Interestingly, two of the three calves were negative for all respiratory pathogens by qPCR, and the other calf was positive for BRSV (S2 Table). Stressed calves were not more likely to be positive for respiratory pathogens in BALF than Acclimated calves at first sampling (odds ratio = 0.55 [95% CI: 0.03–11.96], p = 1).

Table 2. qPCR results from BALF of Stressed and Acclimated calves.

Calf # Group Bacterial Results Viral Results Cycle Threshold Develop BRD in 1st 14 Days
BovLav12132 Stressed Neg Neg >35.0 No
BovLav12745 Stressed Neg Neg >35.0 No
BovLav105226 Stressed Neg Neg >35.0 No
BovLav106915 Stressed Neg Neg >35.0 No
BovLav107720 Stressed P. Multocida Neg 34.1 Yes
BovLav442765 Stressed Neg Neg >35.0 Yes
BovLav13014 Stressed Neg Neg >35.0 No
BovLav101614 Stressed Neg Neg >35.0 No
BovLav255204 Stressed Neg Neg >35.0 No
BovLav253180 Stressed Neg Neg >35.0 No
BovLav58778 Stressed Neg Neg >35.0 No
BovLav587932 Stressed Neg Neg >35.0 Yes
BovLav461618 Acclimated Neg Neg >35.0 No
BovLav429617 Acclimated M. Bovis, H. Somni Neg 30.6,34.5 No
BovLav420826 Acclimated Neg Neg >35.0 No
BovLav463021 Acclimated Neg Neg >35.0 No
BovLav465113 Acclimated Neg Neg >35.0 No
BovLav742132 Acclimated Neg Neg >35.0 No
BovLav466718 Acclimated Neg Neg >35.0 No

Stressed calves demonstrated increased inflammatory gene expression

Differential expression analysis identified 387 differentially expressed genes between Stressed and Acclimated calves (320 upregulated in Stressed calves, 67 downregulated, Fig 3, complete list in S3 Table).

Fig 3. Volcano plot of differentially expressed genes between Stressed and Acclimated calves (red, upregulated in Stressed calves; blue, downregulated, gray, n.s.).

Fig 3

Top differentially expressed genes included inflammatory genes such as CXCL8, CCL22, CSF1, CXCL2, and inflammatory receptors CSF3R and CXCR1 (Fig 4). Inflammatory cytokine signaling appeared to be a hallmark of Stressed calves relative to Acclimated, with >4-fold increases in these genes.

Fig 4. Normalized counts of key upregulated genes in Stressed calves (red) vs Acclimated calves (blue).

Fig 4

Hierarchical clustering was completed to assess relationships between gene expression profiles (Fig 5). This demonstrated that Acclimated calves had relatively uniform gene expression profiles, highlighting the relative homogeneity of the group. On the other hand, Stressed calves demonstrated a spectrum of gene regulation, where calves displayed varying levels of inflammatory gene expression. To better understand this variation, calves were further classified by whether they developed BRD in the first 14 days after arrival at the facility. Interestingly, while two of the calves which displayed the greatest inflammatory signatures later developed clinical BRD as identified by trained facility pen riders, differential gene expression analysis between Stressed calves who later went on to develop BRD and those who remained healthy did not demonstrate appreciable differences in inflammatory signaling (S6 Fig). Therefore, inflammatory signaling appeared to predominate in Stressed calves whether they later developed BRD or not.

Fig 5. Heat map of differential gene expression between Stressed and Acclimated calves, highlighting how Stress calves differentiate into groups based upon levels of inflammatory gene expression.

Fig 5

As one Stressed calf in this representation displayed profound inflammatory signaling, Supplemental Figure 7 is included to display distribution of DEGs in calves that had similar upregulation of inflammatory genes, but not to the extent of that calf. * Denotes a calf who later went on to develop BRD.

Gene ontology and cell abundance analysis

To better understand this inflammatory gene expression, we conducted gene ontology analysis using GO:BP gene sets from msigdb. This demonstrated 69 upregulated pathways in Stressed calves, some of the most prominent being granulocyte migration, IL-1β and IL6 mediated signaling, and antiviral signaling. (Fig 6a, full list in S4 Table). Interestingly, this signaling was occurring even as the calves were negative for viral pathogens common to BRD pathogenesis (Table 2). Leukocyte, and more specifically, granulocyte migration was prominent in Stressed calves, so we sought to predict cell abundance proportions using CIBERSORTx [29]. A deconvolution reference was generated from annotated single-cell RNA-seq data (described in S1S4 Figs). Using this dataset, we were able to predict cellular abundance levels. From this analysis, Stressed calves were predicted to have a four-fold increase in the level of neutrophils in their BALF (p = 0.003). Interestingly, lymphocyte populations were predicted to remain relatively constant. As macrophages were the most abundant cell type, the increase in neutrophil relative abundances resulted in a reciprocal 13% decrease in macrophage percentages (p = 0.04, Fig 6b).

Fig 6. Gene Ontology Analysis and Predicted BALF Immune Cell Proportions in Stressed and Acclimated calves.

Fig 6

a) GO:BP terms upregulated in Stressed calves as compared to acclimated calves, b) CIBERSORTx predicted cell proportions in Stressed (red) and Acclimated (blue) calves.

Discussion

In this study, healthy Stressed beef steers had increased inflammatory transcriptomic signatures relative to healthy Acclimated steers. In contrast to our hypothesis, differential gene expression did not demonstrate downregulation of lymphocyte signaling at the mucosal surface. Genes associated with cytotoxic lymphocyte activity and natural killer (NK) cell immunity were not differentially expressed, which is surprising given the understanding that these responses are sensitive to stress mediators such as glucocorticoids and catecholamines [30]. In contrast, neutrophilic signaling pathways were profoundly upregulated in stressed calves. Predicted neutrophil proportion increases appeared to be associated with upregulation of both interferon signaling and IL-1β signaling and were associated with mononuclear migration pathway upregulation as well. Surprisingly, this inflammatory signaling appeared to occur in the absence of appreciable pathogen colonization of the lower respiratory tract, as indicated by qPCR. It is important to note that Bibersteinia trehalosi was not included in the BRD qPCR panel used here, so screening for that pathogen was not conducted.

Neutrophils are recruited to BALF more strongly in stressed cattle as compared to unstressed after stimulation with LPS [14], and our data further demonstrates that even in calves that have similar pathogen burden, transit and auction stress may potentiate neutrophil recruitment to the lung. In mice, chronic stress can increase neutrophil infiltration in the lung in a glucocorticoid receptor-dependent manner [19]. Acute stress has also been associated with increased immune cell recruitment to sites of inflammatory stimuli in mice [21]. This study demonstrated that acute stress results in increased recruitment of many major immune cell populations, including neutrophils, T cells, and NK cells, and that the inclusion of cytokines like TNF-α in a site of inflammation shifts recruited cellular proportions to favor profound neutrophilic recruitment over lymphocytes. In cattle, this phenomenon has not been experimentally evaluated, though it could explain the neutrophilic infiltration seen here. In rats, resident immune cells like alveolar macrophages can have a more inflammatory phenotype following stress, and produce significantly more IL-1β and TNF-α upon stimulation with lipopolysaccharide (LPS) [31]. In the present study, while qPCR demonstrated that most calves were negative for BRD pathogens in the lower respiratory tract, commensal bacteria exist in the lower airway and may stimulate neutrophilic recruitment in animals that are sensitized due to the stress of transport and commingling through an upregulation in TNF-α from alveolar macrophages. Although this has not been replicated in cattle, it is plausible that signaling in the early stages of stress from mediators such as epinephrine [32] activated macrophages to recruit innate immune cells from circulation.

It is important to note that more work is needed to characterize neutrophilic recruitment to the lung in stress. The data presented here demonstrating elevated neutrophils in BALF are predictive based upon gene expression data. Gene signatures and pathway analysis likewise provide support for cellular recruitment in stress, but future work in this area will require inclusion of functional immune characterization including flow cytometry, cytology, and cell culture.

Stressed calves in this study did not have appreciably elevated levels of serum cortisol at the time of sampling, but it is possible that peak cortisol levels had already been reached and had fallen back to baseline levels at the time of sampling, which averaged 16–18 hours after arrival at the backgrounding facility. The distance calves traveled in this study was comparable to average distances traveled by feedlot and stocker calves across the U.S [1]. Additionally, auction marketing likely contributed to stress levels, as the calves were held overnight and comingled prior to transport to the new facility. The acute phase response, as demonstrated by serum haptoglobin and SAA, appeared to be elevated in steers immediately following auction and transport. Serum haptoglobin and SAA are typically elevated in animals following stressful activities [3335], and may be better indicators of extended stress as compared to glucocorticoids. Sympathetic mediators upregulated in stress stimulate the acute phase response and result in extended production of these proteins by the liver, which remain elevated significantly longer than cortisol following acute stress. Additionally, acute phase responses are upregulated in inflammation, specifically in response to molecules of bacterial and viral origin, including LPS. As a more sensitive indicator of potential infection [36], LBP was included in acute phase protein assessment to better ascertain if calves were experiencing low levels of LPS challenge, either from the upper respiratory tract or gastrointestinal tract. While SAA and haptoglobin levels were significantly elevated in Stressed calves, LBP levels were not significantly different between the Stressed and Acclimated calves, further supporting that these calves did not have significantly different levels of gram-negative bacteria impacting systemic immune responses.

Compared to previous research, Stressed calves appeared to have similar neutrophil proportions to calves with significant (≥1 cm) lung consolidation [37], although mean neutrophil proportions were predicted to be lower than animals with clinical BRD [38]. As even healthy calves can have significant levels of pathogen burden in the lung [39], qPCR was chosen as a means to sensitively compare pathogen burden in the lower airway. In this study, a lower percentage of healthy animals were positive for respiratory pathogens than has been reported by other studies [39,40], although one animal from each experimental group was positive for various respiratory pathogens. It is possible that greater differences could have been appreciated by evaluating upper airway levels of BRD pathogens in these calves, but importantly many of the bacterial organisms on BRD qPCR panels are considered commensals of the upper airway [5]. Aside from the one BRSV positive calf, calves who were diagnosed with BRD were not positive for respiratory pathogens by the time of second sampling, indicating that pathogen levels were either too low at that point to appreciate, or pathogens were localized to a different lung lobe than what was sampled. BALF collections were performed without visualization of the bronchus, so the lung lobe sampled could not be determined. It is notable that Stressed calves who went on to develop BRD signs in the two weeks at the facility did not have significantly greater inflammatory signaling than Stressed calves who stayed healthy. Due to the auction and commingling experienced by all calves, it would be theoretically possible for calves to arrive at the backgrounding facility already infected with a respiratory pathogen. However, qPCR and hierarchical clustering of gene expression appear to indicate that even calves who went on to develop BRD were free from excess pathogen levels in the lower respiratory tract at arrival and did not significantly differ from cattle who stayed healthy in their immune responses.

In the current study, we found inflammatory signaling to be increased in Stressed calves in the absence of elevated pathogen burden, with significant implications for further pathology. While heightened immune responses can be protective in the immediate period following weaning and transport [16,41,42], there appears to be a tipping point at which immune stimulation in the respiratory tract leads to further pathology [42]. The principle immune cell involved in further pathology is the neutrophil, due to its capacity to effect significant tissue damage through the production of excess reactive oxygen species, proteases, and inflammatory chemokines [43]. Neutrophils provide an essential role in protection from bacterial and viral infections, and considerable research in cattle has explored maximization of neutrophil functionality in the effort to mitigate disease [5,4345]. However, increasing evidence indicates that in cattle, pathology in stressed states is due to an excess of inflammation, which is characteristically mediated by neutrophils. Here, we propose that the recruitment of neutrophils is enhanced in Stressed cattle, even in the absence of overt pathogen challenge.

Supporting information

S1 Fig. Single-cell dataset (A) annotated Uniform Manifold Approximation and Projection (UMAP) of all cells included in the reference dataset, (B) characteristic markers showing distribution of feature expression on the UMAP, (C) relative expression of select marker genes across UMAP cell clusters.

(TIF)

pone.0328428.s001.tif (702.4KB, tif)
S2 Fig. Heatmap displaying percent difference values between CIBERSORTx predicted cellular proportions and single-cell “ground truth” cellular proportions.

(TIF)

pone.0328428.s002.tif (762.4KB, tif)
S3 Fig. Plots displaying correlation and R2 values between CIBERSORTx predicted cell proportions and single-cell “ground truth” cellular proportions.

(TIF)

pone.0328428.s003.tif (834.8KB, tif)
S4 Fig. Serum LBP and cortisol levels between Stressed and Acclimated calves.

(TIF)

pone.0328428.s004.tif (575.7KB, tif)
S5 Fig. Rectal temperature between Stressed and Acclimated calves.

(TIF)

pone.0328428.s005.tif (135KB, tif)
S6 Fig. Differences in transcriptomic sequencing between Stressed calves who developed BRD and those who remained healthy, including (A) volcano plot of DEGs, and (B) heatmap showing clustering of animals.

(TIF)

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S7 Fig. Heat map between Stressed and Acclimated calves with all calves included.

(TIF)

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S1 Table. Cluster markers (genes) for each major cell population included in the CIBERSORTx matrix.

(CSV)

pone.0328428.s008.csv (7.2MB, csv)
S2 Table. Calf treatment and metadata values demonstrating time relative to arrival of sampling and treatment, as well as BRD calf sampling qPCR positives.

Ultrasound score (0–5); 0 = no lobular or lobar consolidation; 1 = diffuse comet tails; 2 = at least 1 cm2 of lobular consolidation; 3 = lobar consolidation (1 lung lobe); 4 = lobar consolidation (2 lung lobes); 5 = lobar consolidation (3 or more lung lobes).

(XLSX)

pone.0328428.s009.xlsx (18.8KB, xlsx)
S3 Table. Complete list of differentially expressed genes (DEGs) between Stressed and Acclimated calves.

(CSV)

pone.0328428.s010.csv (33.5KB, csv)
S4 Table. GO: BP terms upregulated in Stressed calves.

(CSV)

pone.0328428.s011.csv (17.2KB, csv)

Acknowledgments

We would like to thank Jade Kurihara for sample processing support and laboratory training of author GJ. Additionally, Jenaye De Seve provided indispensable field support during sample collection on-farm.

Data Availability

The data presented in this paper are available through the Dryad open data publishing platform at https://doi.org/10.5061/dryad.02v6wwqh6. The data discussed in this publication have also been deposited in NCBI’s Gene Expression Omnibus and are accessible through GEO Series accession number GSE299548 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE299548). An associated GitHub page containing all the analysis code and software versions used to analyze the data presented in this article is available at (https://github.com/gmjakes/Bovine_bulkseq_stress_study). Any additional data requests can be made by contacting the corresponding authors.

Funding Statement

Authors SD and SR were granted a Cooperative Agreement with the USDA Agricultural Research Service (https://www.ars.usda.gov/). FAIN: 58-3022-3-023. The sponsor had no role in the study design, data collection and analysis, decision to publish, or in the preparation of the manuscript.

References

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Decision Letter 0

Angel Abuelo

19 Aug 2025

Dear Dr. Raabis,

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Partly

Reviewer #2: Partly

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2. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: Yes

Reviewer #2: No

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3. Have the authors made all data underlying the findings in their manuscript fully available??>

The PLOS Data policy

Reviewer #1: Yes

Reviewer #2: No

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4. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: This manuscript by Jakes et al. addresses an important question in bovine respiratory disease pathogenesis, how stress impacts mucosal immune responses in the absence of overt infection. The authors use a combination of BALF RNA-seq, pathogen qPCR, and serum biomarkers to interrogate this question. The study is well-designed, and the focus on lower airway responses is a strength that adds to prior work centered on systemic or peripheral responses.

Major comments:

1) The core finding that stress induces, rather than suppresses, inflammation differs somewhat from the understanding of BRD, but I think that idea is not totally novel and is consistent with prior studies in calves (e.g., Hodgson et al., Griebel’s work), many of which the authors identified. This manuscript extends that work by focusing specifically on the lower airway and linking inflammation to pathogen-independent mechanisms, demonstrated by the absence of detectable pathogens in BALF at the time of sampling. The authors should consider softening the novelty claims around increased vs. suppressed inflammation, and instead emphasize the value of this study in refining prior observations through a mucosal, pathogen-exclusion lens.

2) The authors heavily emphasize the CIBERSort cell deconvolution data in the discussion. However, this data and analysis is not clearly described and lacks validation. More detail is needed on the reference dataset used, and the markers used to differentiate these populations. Without supporting cytology, flow cytometry, or BALF cell counts, the inferred shift in neutrophils should be interpreted cautiously and some discussion should be added regarding the limitations of relying solely on computational predictions should be acknowledged. Along these lines, Figure 7 doesn't seem to add much to the discussion section.

Reviewer #2: This manuscript describes research supporting the concept that newly received cattle have increased activation of gene expression pathways related to inflammation in airways cells, in the absence of evidence of infection, and as compared to acclimated cattle. The study does provide some support for the concept that excessive inflammation, rather than immunosuppression per se, is the state that underlies BRD in newly received stocker cattle. The results merit reporting. However, the experimental design is not clear, and some needed information is missing, as described below.

Introduction

Line 83-91: There is no mention of the fact that haptoglobin, cortisol, LBP, and SAA would be measured in the blood of study cattle. What objective was being addressed by these measurements? That should be added to this section.

Materials and Methods

Where are the methods for the CIBERSORT? They need to be included.

Were the calves in the Stressed group and the calves in the Acclimated group all from the same group of cattle purchased at the same time? Or were they purchased at different times?

Did the cattle receive antimicrobial metaphylaxis (i.e. long acting antimicrobial at arrival for BRD control)? This should be explicitly stated.

The study design is not very clear. Is it true that some Stressed calves were never diagnosed with BRD after they were sampled until the end of the backgrounding period, while others were diagnosed with BRD (and sampled when they were)?

And is it true that the Acclimated calves were never diagnosed with BRD between arrival and the day they were sampled? If so, it would help improve reader understanding of the design if this was stated explicitly. Also, how long was the total backgrounding period?

Reader understanding of the experimental design could be improved by adding more detail about the experimental design to Figure 1. For example, did all Stressed steers subsequently develop BRD, and have BAL collected when they developed BRD, or only some of them? For each Stressed animal sampled that developed BRD, how many days after arrival did BRD occur?

Line 98-100: power analysis described, but what outcome was the focus of the power calculation, and how much difference between the 2 groups in this outcome would the sample size of 9 detect?

Line 123: "foley" should be capitalized, and it seems that the term "Foley catheter" is limited to the type of cuffed catheters used for urinary catheterization. It may be more correct to simply to say "A sterile cuffed bronchoalveolar lavage catheter..." instead of "..Foley cather..."

Lines 182-186: what statistical test was used to compare cortisol and acute phase proteins between groups?

Results

Given the small number of cattle included in this study, the authors should provide metadata for each animal in both the Stressed and Acclimated groups in a spreadsheet provided as supplementary data. The metadata should information such as the weight of each animal, the day relative to arrival when the BAL and blood were collected, and all times the animal was treated for BRD or any other disease, and what treatment they received (i.e. which antimicrobial)

Where is the list of all DEG? They should be provided in a spreadsheet as supplementary data.

Line 227: "...whether they developed BRD in the first week after arrival..." Do the authors mean "first 2 weeks", as indicated in Supplementary Figure 4?

Line 255: "Clade" refers to a group of organisms that appear to have evolved from the same ancestor; it does not appear to be an appropriate term as used here. The word "clade" should be replaced with a different word in the manuscript and figures; "group" is probably adequate.

Figures

Figure 1: As mentioned above, Figure 1 could be made more informative by inclusion of more information, e.g., how many cattle in each group was treated for BRD and when. It is not clear that as currently presented Figure 1 provides enough information to warrant inclusion.

Figure 5: Some of the text of the legend of Figure 5 is unclear, what does this sentence mean: "One Stressed calf displaying the most profound inflammatory signaling was removed for this representation to demonstrate the clades of inflammatory signaling"? Please revise this legend to make it more clear.

It is not very clear why the heatmap in Figure 5 is presented in the body of manuscript and the heatmap in Figure 4 was presented as supplementary data. Why not just present the heatmap in Figure 4 in the body of the manuscript?

The asterisks in Supplementary Fig 4 indicates cattle treated for BRD within 14 days of arrival; were any treated after 14 days but before the end of the backgrounding period?

Figure 7: In the image of the alveolus of the stressed animal, what do the small green dots represent?

Because the mechanism depicted in Figure 7 is entirely hypothetical, it is not clear that this figure is truly warranted.

Supplemental Figures:

Supplemental Figure 3 has two components, A and B, but these are not both described in the legend for this figure.

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2026 Feb 6;21(2):e0328428. doi: 10.1371/journal.pone.0328428.r002

Author response to Decision Letter 1


3 Oct 2025

Response to Editorial Comments:

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

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Thank you for the clarification and direction on the PLOS ONE style requirements. On further review of the provided title page template, we have removed the “Full Title” and “Short Title” sections on lines 1-6 (1-2). We have also added clarification on equal contributions for each author on line 9 (5,16-17).

We have changed our figure and supplemental figure file names to better comply with the desired file naming conventions as outlined in the PLOS ONE guidelines. Each figure we have changed from “Figure 1” to “Fig1”, and the supplemental figures and tables have been changed to include the S numbering system (e.g. S1, S2, etc.).

We have changed the main sections to a 14pt bolded font, and each subsection to a 11pt bolded font instead of using the numbering convention. If this is not the desired alteration, we can also change it back based upon your feedback.

2. To comply with PLOS ONE submissions requirements, in your Methods section, please provide additional information regarding the experiments involving animals and ensure you have included details on methods of anesthesia and/or analgesia.

We appreciate the feedback on this aspect of our methods section. To address this concern, we have included our handling practices, and chute brand/design for animal restraint on lines 129-130 (123-124). Additionally, we have added verbiage in the Study Population section about our use of xylazine and efforts to reduce animal suffering on lines 119-121 (113-115). Specific doses and brands used can be found on lines 137-140 (131-134). Based on our interpretation of PLOS ONE ‘s Animal Research guidelines, we have made every effort to include desired information regarding sedation and analgesia, but if there is additional information that is desired, we can supply it as needed.

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Thank you for this clarification on acceptable repositories. We have elected to upload our dataset to the Dryad repository and still include the GEO accession number so that readers can access both at their discretion. The Dryad repository reviewer link has been shared elsewhere in the submission, and can also be found here: http://datadryad.org/share/LINK_NOT_FOR_PUBLICATION/tFIZElhw0_WoF02Q1mmUKXPf3N9FbTHBVUYc6RGNbNw.

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https://doi.org/10.5061/dryad.02v6wwqh6.

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We apologize for this oversite and appreciate you bringing this to our attention. We have uploaded this table, now as Supporting Information/Table 4, as we have added more supporting information earlier in the document.

5. If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

We did not see any reviewer comments pertaining to citing other published work, but if further in the review process there is a request for other citations, we would be more than happy to address these as they arise.

Response to Reviewer 1:

Thank you for the time and effort it took to review our manuscript. Your thoughts and comments were extremely helpful in the revision of our manuscript, and we have made every effort to address each point raised in the review process. In our response to your comments, we have included your prior comment in italics, and our response in normal font immediately following that paragraph. We have sought to thoughtfully address every point raised and can provide more support or clarification to our data and revisions as needed.

1) The core finding that stress induces, rather than suppresses, inflammation differs somewhat from the understanding of BRD, but I think that idea is not totally novel and is consistent with prior studies in calves (e.g., Hodgson et al., Griebel’s work), many of which the authors identified. This manuscript extends that work by focusing specifically on the lower airway and linking inflammation to pathogen-independent mechanisms, demonstrated by the absence of detectable pathogens in BALF at the time of sampling. The authors should consider softening the novelty claims around increased vs. suppressed inflammation, and instead emphasize the value of this study in refining prior observations through a mucosal, pathogen-exclusion lens.

We appreciate the perspective in this comment and agree that our initial language may have over accentuated the novelty of our data, specifically in the context of stress. In response to this comment, we have altered our language in the abstract, introduction, and discussion sections of the manuscript to soften and redirect our commentary to focus on the mucosal host-pathogen aspect of our findings. Please see our changes at lines 43-44 (38-40), 94 (88-89), 399-409 (382-392).

2) The authors heavily emphasize the CIBERSort cell deconvolution data in the discussion. However, this data and analysis is not clearly described and lacks validation. More detail is needed on the reference dataset used, and the markers used to differentiate these populations. Without supporting cytology, flow cytometry, or BALF cell counts, the inferred shift in neutrophils should be interpreted cautiously and some discussion should be added regarding the limitations of relying solely on computational predictions should be acknowledged. Along these lines, Figure 7 doesn't seem to add much to the discussion section.

Thank you for this comment. We have added documentation detailing our methods and markers used in this CIBERSORTx analysis. Specifically, Table 1 in the body of the document has been added to detail select markers used to classify cellular populations. This does not provide an exhaustive list of the classifications, rather is intended to be similar to a flow cytometry-style panel, demonstrating upregulated and “negative” or downregulated markers. We have used both cell surface markers and transcription factors to classify the cellular populations and have included a minimum of 3 upregulated markers per cell type. A full list of the defining upregulated and downregulated markers for each cell type can be found in Supplemental Table 1. We have also visually represented the dataset using a uniform manifold approximation and projection (UMAP) image so that the readers can see the distribution and make-up of the single-cell dataset (Supplemental Figure 1a and 1b). A dot plot heat map has been included as a visual representation of the markers used for each cell type (Supplemental Figure 1c). The numbers/columns on the dot plot represent the individual cell clusters on the UMAP, so that readers may cross-reference the distribution of cell populations in relation to one another and their major markers.

Several of the calves included in the study had paired single-cell and bulk sequencing samples, so we completed a difference from single-cell “ground truth” analysis on our CIBERSORTx predicted values for each cell type. We completed this analysis for both of the different batch correction methods evaluated and have included that data in Supplemental Figure 2. We also conducted a correlation analysis and have included the visual representation of this analysis as well as the R2 values in Supplemental Figure 3.

A detailed discussion of our CIBERSORTx methodology can be found in the Methods section, lines 197-222 (189-214). Please let us know if additional support or clarification of the data is needed.

We have added a paragraph discussing the limitations of in silico predictions of cell population proportions on lines 347-351 (336-340) in the Discussion section, and upon further reflection, have elected to remove primary Figure 7 from the manuscript.

Response to Reviewer 2:

Thank you for the time and effort it took to review our manuscript. Your thoughts and comments were extremely helpful in the revision of our manuscript, and we have made every effort to address each point raised in the review process. In our response to your comments, we have included your prior comment in italics, and our response in normal font immediately following that paragraph. We have sought to thoughtfully address every point raised and can provide more support or clarification to our data and revisions as needed.

Introduction Line 83-91: There is no mention of the fact that haptoglobin, cortisol, LBP, and SAA would be measured in the blood of study cattle. What objective was being addressed by these measurements? That should be added to this section.

We appreciate this feedback. We sought to use these markers to demonstrate that calves in this study were truly stressed, or at least responding systemically to the transit and auction stressors that they had experienced. As we were not in control of exactly when the calves would arrive and be sampled (beyond within the first 18-24 hours after arrival), we chose multiple stress markers that covered early and later stress responses. We have updated the manuscript to reflect this in lines 87-88 (82-83).

Materials and Methods Where are the methods for the CIBERSORT? They need to be included.

Thank you for this clarifying request. We have included detailed methodology on lines 197-222 (189-214). We also wanted to respond with some explanation for each supplemental figure and table added for the CIBERSORTx methods:

Table 1 in the body of the document has been added to detail select markers used to classify cellular populations. This does not provide an exhaustive list of the classifications, rather is intended to be similar to a flow cytometry-style panel, demonstrating upregulated and “negative” or downregulated markers. We have used both cell surface markers and transcription factors to classify the cellular populations and have included a minimum of 3 upregulated markers per cell type. A full list of the defining upregulated and downregulated markers for each cell type can be found in Supplemental Table 1. We have also visually represented the dataset using a uniform manifold approximation and projection (UMAP) image so that the readers can see the distribution and make-up of the single-cell dataset (Supplemental Figure 1a and 1b). A dot plot heat map has been included as a visual representation of the markers used for each cell type (Supplemental Figure 1c). The numbers/columns on the dot plot represent the individual cell clusters on the UMAP, so that readers may cross-reference the distribution of cell populations in relation to one another and their major markers.

Several of the calves included in the study had paired single-cell and bulk sequencing samples, so we completed a difference from single-cell “ground truth” analysis on our CIBERSORTx predicted values for each cell type. We completed this analysis for both of the different batch correction methods evaluated and have included that data in Supplemental Figure 2. We also conducted a correlation analysis and have included the visual representation of this analysis as well as the R2 values in Supplemental Figure 3.

Were the calves in the Stressed group and the calves in the Acclimated group all from the same group of cattle purchased at the same time? Or were they purchased at different times?

Thank you for this question. We randomly sampled cattle in batches of 3-4 from different shipments throughout the purchasing season. This was done to ideally get the most randomized and representative sample from the backgrounding period, not biased by calf source. We have updated the manuscript to reflect this on line 103-104 (97-98).

Did the cattle receive antimicrobial metaphylaxis (i.e. long acting antimicrobial at arrival for BRD control)? This should be explicitly stated.

Thank you for this question. The calves did not receive any metaphylaxis, nor did any calf that arrived or was put out to pasture at the same time as the enrolled calves. We have added this information on line 112 (106).

The study design is not very clear. Is it true that some Stressed calves were never diagnosed with BRD after they were sampled until the end of the backgrounding period, while others were diagnosed with BRD (and sampled when they were)?And is it true that the Acclimated calves were never diagnosed with BRD between arrival and the day they were sampled? If so, it would help improve reader understanding of the design if this was stated explicitly. Also, how long was the total backgrounding period?

We appreciate this feedback and apologize for the lack of clarity. Yes, 7 of the Stressed calves were never diagnosed with BRD throughout the backgrounding period. Calves that developed BRD within 14 days of arrival were sampled at the time they were pulled (before antibiotic administration). Two calves developed BRD ~6 weeks after arrival and were not sampled because the backgrounder could not coordinate with our sampling over the Thanksgiving holiday. We have updated the manuscript to address this briefly on lines 158-160 (151-152).

Acclimated calves were never diagnosed with BRD between arrival and when they were sampled (and through the entire backgrounding period). We have updated the manuscript to reflect this on line 149-152 (142-145).

Reader understanding of the experimental design could be improved by adding more detail about the experimental design to Figure 1. For example, did all Stressed steers subsequently develop BRD, and have BAL collected when they developed BRD, or only some of them? For each Stressed animal sampled that developed BRD, how many days after arrival did BRD occur?

Thank you for this suggestion. We have substantially changed Figure 1 to include the timeline of sampling/the backgrounding period, and to include the number of Stressed calves who developed BRD and were sampled again. We included the date range for when we sampled calves who had developed BRD, and the specific number of days can be found in Supplemental Table 2.

Line 98-100: power analysis described, but what outcome was the focus of the power calculation, and how much difference between the 2 groups in this outcome would the sample size of 9 detect?

We appreciate this clarifying question. We based our power analysis on expected differences in acute-phase proteins and cortisol, as these were our validation markers for stress. We derived our expected difference between the two groups from recently published literature (Beenken et al., 2021 in our references, among others) and anticipated that each of the stress mediators would be elevated in the study animals. We were incorrect about cortisol and LBP, but we addressed theories on why this could be (time of sampling, possible lack of LPS stimulation) in the Discussion. The details regarding specific values for the difference we were expecting to see can be found on lines 103-109 (98-104).

Line 123: "foley" should be capitalized, and it seems that the term "Foley catheter" is limited to the type of cuffed catheters used for urinary catheterization. It may be more correct to simply to say "A sterile cuffed bronchoalveolar lavage catheter..." instead of "..Foley cather..."

Thank

Attachment

Submitted filename: Response to Reviewers.docx

pone.0328428.s012.docx (34.3KB, docx)

Decision Letter 1

Angel Abuelo

26 Nov 2025

Dear Dr. Raabis,

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Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

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Reviewer #1: Yes

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Reviewer #1: (No Response)

Reviewer #2: The authors have done a very good job addressing the previous review. Two small recommendations:

Line 225: Supplemental Figure 2 should be changed to Supplemental Figure 5

Supplemental Table 2: readers may be interested to know which calves had a fever and which calves had consolidated lung found on ultrasound; that information could be added to Supplemental Table 2.

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PLoS One. 2026 Feb 6;21(2):e0328428. doi: 10.1371/journal.pone.0328428.r004

Author response to Decision Letter 2


30 Dec 2025

Dear Dr. Abuelo,

Thank you for your continued consideration of our manuscript entitled, “Transport stress induced paradoxical increases in airway inflammatory responses in beef stocker cattle.” We sincerely appreciate the feedback included in this request for edits. We have sought to address these points individually and to the best of our ability and will appreciate any additional feedback should it arise.

Similar to our first round of edits, any in-text changes will be cited by line number in the “Revised Manuscript with Track Changes” document, and then in parenthesis for the Manuscript document (e.g. lines 115-117 [105-107]). We are only aware of one request for an in-text edit, as requested by Reviewer 2. We have made a few minor edits to our reference list based upon closer review of the style guidelines and have included specifics on those edits in the Response to Editorial comments section. Included in the editorial comments was a request to ensure that no retracted articles were included in our list of references. We are unaware of any retracted articles included in our list of references but would make every effort to remove and replace such a reference should they exist.

Please see our specific responses to editorial and reviewer comments in the following sections. Should any response not satisfactorily address a point raised by the editors or reviewers, we would be more than happy to revisit any point more thoroughly if indicated.

Response to Editorial Comments:

1. If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Thank you for this opportunity to review our submitted references. Upon further review, we have edited the journal names to include the NLM title abbreviation rather than the full journal name for each entry. We apologize for our incorrect interpretation of the style guidelines in our initial submission. We have also slightly edited the USDA report entries to better meet the citation guidelines. Finally, the pwr package citation has been edited to link to the CRAN repository rather than the author’s GitHub page, as based upon further review we believe that this may align more correctly with Vancouver citation guidelines. There was one citation (Nyhlén et al., 2000) where the citation was inadvertently included in caps rather than sentence case, and that has been corrected. We regret this oversite.

We have made every effort to review our list of references to make sure that no retracted articles are included in our reference list. We are unaware of any article(s) that have been retracted and would be more than willing to remove any reference that is retracted should that be the case.

We have not received any requests from reviewers to cite additional work, but if there are gaps in our discussion or introduction that should be filled, we would be more than happy to review any relevant literature not already included if indicated.

Response to Reviewer 1:

Thank you for your careful review of our revised manuscript. We appreciate your effort in the review process and would welcome any further comments should they arise.

Response to Reviewer 2:

Thank you for your careful consideration of this revised manuscript draft. We appreciate your comments and have done our best to address each one.

Thank you for catching the mislabeling/reference to Supplemental Figure 5. We have corrected this in line 245 (245) of the Manuscript.

We also appreciate your suggestion of including the ultrasound score and rectal temperature at the second BAL sampling, when calves were diagnosed with BRD by pen-riders, in our supplemental data. This has been included in Supplemental Table 2 (S2 Table) under columns “Rectal Temperature at Second BAL (degrees C)” and “Lung Ultrasound Score at Second BAL.” It is important to note that the ultrasound score was 0 on two of the three calves, but based upon rectal temperature, behavior, upper respiratory signs, and caretaker best-judgement, these calves were diagnosed with BRD and were treated. The identification and treatment of these calves prior to the development of severe lung lesions is likely a testament to their acute development of signs and timely identification by pen riders before severe pulmonary disease could develop. Additionally, ultrasound examination was limited in this study, as we were unable to visualize the right cranial lung lobe consistently due to the logistics of the chute design (see lines 129-130). Therefore, lesions may have been present and not detected by ultrasound exam.

We want to reiterate our appreciation of your time and effort in reviewing our manuscript. Should you identify any further changes in the review process, we would be more than happy to address them as they arise.

Concluding Remarks

We want to conclude by reiterating our appreciation for the editorial and reviewer comments. They have substantially advanced the quality of our submission.

Thank you again for your consideration,

Grace Jakes (1st author)

Sarah Raabis (co-corresponding author)

Attachment

Submitted filename: Response_to_Reviewers_auresp_2.docx

pone.0328428.s013.docx (27.6KB, docx)

Decision Letter 2

Angel Abuelo

4 Jan 2026

Transport stress induces paradoxical increases in airway inflammatory responses in beef stocker cattle

PONE-D-25-35522R2

Dear Dr. Raabis,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Angel Abuelo, DVM, MRes, MSc, PhD, DABVP (Dairy), DECBHM

Academic Editor

PLOS One

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Angel Abuelo

PONE-D-25-35522R2

PLOS One

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig. Single-cell dataset (A) annotated Uniform Manifold Approximation and Projection (UMAP) of all cells included in the reference dataset, (B) characteristic markers showing distribution of feature expression on the UMAP, (C) relative expression of select marker genes across UMAP cell clusters.

    (TIF)

    pone.0328428.s001.tif (702.4KB, tif)
    S2 Fig. Heatmap displaying percent difference values between CIBERSORTx predicted cellular proportions and single-cell “ground truth” cellular proportions.

    (TIF)

    pone.0328428.s002.tif (762.4KB, tif)
    S3 Fig. Plots displaying correlation and R2 values between CIBERSORTx predicted cell proportions and single-cell “ground truth” cellular proportions.

    (TIF)

    pone.0328428.s003.tif (834.8KB, tif)
    S4 Fig. Serum LBP and cortisol levels between Stressed and Acclimated calves.

    (TIF)

    pone.0328428.s004.tif (575.7KB, tif)
    S5 Fig. Rectal temperature between Stressed and Acclimated calves.

    (TIF)

    pone.0328428.s005.tif (135KB, tif)
    S6 Fig. Differences in transcriptomic sequencing between Stressed calves who developed BRD and those who remained healthy, including (A) volcano plot of DEGs, and (B) heatmap showing clustering of animals.

    (TIF)

    pone.0328428.s006.tif (767.1KB, tif)
    S7 Fig. Heat map between Stressed and Acclimated calves with all calves included.

    (TIF)

    pone.0328428.s007.tif (1.1MB, tif)
    S1 Table. Cluster markers (genes) for each major cell population included in the CIBERSORTx matrix.

    (CSV)

    pone.0328428.s008.csv (7.2MB, csv)
    S2 Table. Calf treatment and metadata values demonstrating time relative to arrival of sampling and treatment, as well as BRD calf sampling qPCR positives.

    Ultrasound score (0–5); 0 = no lobular or lobar consolidation; 1 = diffuse comet tails; 2 = at least 1 cm2 of lobular consolidation; 3 = lobar consolidation (1 lung lobe); 4 = lobar consolidation (2 lung lobes); 5 = lobar consolidation (3 or more lung lobes).

    (XLSX)

    pone.0328428.s009.xlsx (18.8KB, xlsx)
    S3 Table. Complete list of differentially expressed genes (DEGs) between Stressed and Acclimated calves.

    (CSV)

    pone.0328428.s010.csv (33.5KB, csv)
    S4 Table. GO: BP terms upregulated in Stressed calves.

    (CSV)

    pone.0328428.s011.csv (17.2KB, csv)
    Attachment

    Submitted filename: Response to Reviewers.docx

    pone.0328428.s012.docx (34.3KB, docx)
    Attachment

    Submitted filename: Response_to_Reviewers_auresp_2.docx

    pone.0328428.s013.docx (27.6KB, docx)

    Data Availability Statement

    The data presented in this paper are available through the Dryad open data publishing platform at https://doi.org/10.5061/dryad.02v6wwqh6. The data discussed in this publication have also been deposited in NCBI’s Gene Expression Omnibus and are accessible through GEO Series accession number GSE299548 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE299548). An associated GitHub page containing all the analysis code and software versions used to analyze the data presented in this article is available at (https://github.com/gmjakes/Bovine_bulkseq_stress_study). Any additional data requests can be made by contacting the corresponding authors.


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