Biology subjects

Smith, R. L.

Publications and source records attributed to Smith, R. L..

18 recordsLinked to original sources

bioRxiv2026

scRBP infers cell-specific RNA-binding protein regulons from single-cell transcriptomes at gene and isoform resolution

Single-cell regulatory network inference remains dominated by transcription factors, despite RNA-binding proteins (RBPs) orchestrating major aspects of transcriptional regulation. We present scRBP, a framework that infers motif-supported RBP regulons from short- and long-read single-cell transcriptomes at gene and isoform resolution, resolves targets by transcript region (5'UTR, CDS, intron, 3'UTR), scores regulon activity in individual cells, and tests common- and rare-variant association against matched empirical nulls. From 20,746 motifs for 616 RBPs, scRBP recovered experimentally defined targets across 223 ENCODE eCLIP datasets at gene and isoform level. Across 30 tissues, transcript-region preferences separated 3'UTR-associated stability factors from intron-dominant splicing regulators. In published genome-scale CRISPRi Perturb-seq data, scRBP-inferred targets were over-represented among genes responding to RBP knockdown (1.4-2.5-fold across 161 RBPs; FDR<2x10-4). Across 6.2 million cells and 50 traits, scRBP prioritized cell-specific post-transcriptional programs linking human genetic risk to development and disease.

genetics↗

bioRxiv2026

Autism genes converge on three functional programs organized by neuronal subclass, developmental timing, and cortical patterning

Our companion sequencing study uncovered 253 genes robustly associated with autism spectrum disorder (ASD), yet the biological programs they impact, and the cellular, developmental, and spatial contexts in which they converge, remain unresolved. Here we systematically contextualize genes associated with ASD across neurodevelopment and cortical areas, integrating developmental single-cell and spatial atlases with gene- and isoform co-expression, regulatory, proteomic, and synaptic networks. Genetic burden concentrates within temporally-resolved neuronal subclasses: newborn excitatory neurons, immature interneurons, and maturing intratelencephalic lineages. Genes associated with ASD converge on three functional programs--gene regulation, neuronal morphogenesis, and synaptic transmembrane signaling machinery--resolved from 28 ASD-associated networks, several of which are directly regulated by ASD genes including MEF2C, SOX11, and FOXP2. These programs are spatially patterned, with risk genes exhibiting an increasing anterior-to-posterior cortical expression gradient, anchored in the primary visual cortex and driven by excitatory neuron gene-regulatory programs. Finally, ASD risk genes associated with more severe developmental phenotypes show broader excitatory neuron enrichment and less interneuron involvement. Together, these findings anchor ASD genetic vulnerability to specific neurodevelopmental lineages, epochs, and molecular substrates, and delineate the features that distinguish ASD from comorbidities with broader developmental impacts.

genomics↗

bioRxiv2026

Bayesian spatial prediction of three medically important tick species in Illinois

Tick-borne diseases are now reported from nearly every county in Illinois, and three vector tick species (Amblyomma americanum, Dermacentor variabilis, and Ixodes scapularis) are of particular concern because these are responsible for most of the tick-borne disease transmission in the state. However, active surveillance is patchy, many counties have little or no sampling, and there is no statewide, quantitative map of relative abundance that can be used to anticipate risk in unsampled areas. To address these gaps, we developed Bayesian hierarchical spatial models to estimate the county-level abundance of these three vector tick species in Illinois. Using active surveillance data from 2019-2022, we modeled county-level abundance as a function of climate, land cover, forest fragmentation, and deer habitat suitability. Spatial dependence was captured using a Besag-York-Mollie 2 (BYM2) prior implemented in INLA, along with spatial 5-fold cross-validation to assess predictive performance. A. americanum showed the highest predicted abundance in southern and central Illinois, D. variabilis was widespread but diffuse, and I. scapularis was concentrated in northern and selected central counties. Together, these models provide the first spatial, statewide, uncertainty-aware assessment of tick abundance in Illinois, highlighting priority counties where surveillance lags disease risk.

ecology↗

bioRxiv2026

Filling surveillance gaps: Bayesian INLA models for predicting tick distributions in data-sparse regions

Fragmented and geographically uneven surveillance limits the ability to target tick monitoring and control in many livestock systems. We evaluated whether heterogeneous published surveillance could be converted into district-level, uncertainty-aware abundance predictions for Rhipicephalus microplus and Hyalomma anatolicum across Punjab and Khyber Pakhtunkhwa, Pakistan. Species-specific tick counts were standardized by the number of animals examined and sampling duration and expressed as ticks per 100,000 animal-months. Environmental covariates were summarized using principal component analysis, with livestock density included separately. Bayesian Gaussian models, with and without a district-level Besag-York-Mollie 2 spatial effect, were fitted in R using Integrated Nested Laplace Approximation (INLA) and compared. Leave-one-district-out validation was performed to assess out-of-sample predictive performance. Spatial models improved model fit for both species. For R. microplus, PC1 and PC4 showed credible negative associations with abundance, whereas no fixed-effect 95% credible interval excluded zero for H. anatolicum. Predicted R. microplus abundance was more spatially heterogeneous, with high but uncertain estimates in several northern districts, whereas H. anatolicum predictions were more homogeneous and relatively higher toward southern Punjab. Mapping posterior uncertainty identified districts where additional standardized surveillance would be most informative. This approach provides a transferable framework for extracting spatial surveillance information from heterogeneous veterinary data while explicitly representing uncertainty.

ecology↗

bioRxiv2025

Knowledge, attitudes, and practices of para-veterinary workers about ticks and tick-borne diseases in three provinces of Pakistan

There is a high prevalence of tick infestation in Pakistani livestock, affecting more than 45% of the population of more than 200 million small and large ruminants. Most livestock farmers seek assistance from para-veterinary workers, who fall under the definition of Veterinary Paraprofessionals (VPPs), according to the World Organization for Animal Health (WOAH). There is a shortage of information concerning the awareness of these para-veterinary workers regarding tick control and management. This study aims to bridge this critical knowledge gap by conducting a cross-sectional survey that evaluates the knowledge, attitudes, and practices of para-veterinary workers about tick-borne diseases (TBDs) in Pakistan. Between March and August 2023, we conducted a web-based survey among para-veterinary workers recruited via email, text message, and face-to-face conversations. Poisson regression was used to identify factors associated with knowledge, attitude, and practice (KAP) scores related to TBDs. We received 118 responses from three provinces; only 27.9% (n = 33) responded that they had attended workshops related to ticks and TBDs. Attending workshops was associated with higher KAP scores. All section scores were correlated, and higher knowledge scores were significantly associated with lower odds of tick exposure. Our findings suggest that workshop attendance is important in increasing overall awareness and promoting better practices regarding TBDs.

scientific communication and education↗

bioRxiv2025

A neuro-immune axis of transcriptomic dysregulation within the subgenual anterior cingulate cortex in schizophrenia

Many genes are linked to psychiatric disorders, but genome-wide association studies (GWAS) and differential gene expression (DGE) analyses in post-mortem brain tissue often implicate distinct gene sets. This disconnect impedes therapeutic development, which relies on integrating genetic and genomic insights. We address this issue using a novel multivariate technique that reduces DGE bias by leveraging gene co-expression networks and controlling for confounds such as drug exposure. Deep RNA sequencing was performed in bulk post-mortem sgACC from individuals with bipolar disorder (BD; N=35), major depression (MDD; N=51), schizophrenia (SCZ; N=44), and controls (N=55). Toxicology data dimensionality was reduced using multiple correspondence analysis; case-control gene expression was then analyzed using 1) traditional DGE and 2) group regularized canonical correlation analysis (GRCCA) - a multivariate regression method that accounts for feature interdependence. Gene set enrichment analyses compared results with established neuropsychiatric risk genes, gene ontology pathways, and cell type enrichments. GRCCA revealed a significant association with SCZ (Pperm=0.001; no significant BD or MDD association), and the resulting gene weight vector correlated with DGE SCZ-control t-statistics (R=0.53; P<0.05). Both methods indicated down-regulation of immune and microglial genes and upregulation of ion transport and excitatory neuron genes. However, GRCCA - at both the gene and transcript level - showed stronger enrichments (FDR<0.05). Notably, GRCCA results were enriched for SCZ GWAS-implicated genes (FDR<0.05), while DGE results were not. These findings identify a SCZ-specific sgACC gene expression pattern that highlights SCZ risk genes and implicates neuro-immune pathways, thus demonstrating the utility of multivariate approaches to integrate genetic and genomic signals.

neuroscience↗

bioRxiv2024

Development and early life stress sensitivity of the rat cortical microstructural similarity network

Understanding how early life experiences shape brain network development is a key challenge in the neuroscience of mental health disorders. To address this, we used magnetic resonance imaging (MRI) similarity network analysis to study the effects of stress in the rat, an important animal model in neuropsychiatry. We measured magnetization transfer ratio (MTR) at each of 53 distinct cortical areas and estimated a cortical similarity network for each individual scan, in two independent experimental datasets. We first characterized normative network development in rats scanned repeatedly between postnatal days 20 (weanling) and 290 (mid-adulthood) (N=47), and then contrasted these findings with a cohort exposed to early life stress in the form of repeated maternal separation (RMS, N=40). The normative rat cortical similarity network exhibited biologically meaningful organization, aligning with prior cytoarchitectonic and tract-tracing data, and displayed complex topological features, including rich club organization. During postnatal and adolescent development, brain regions became more similar, including an early phase of fronto-hippocampal convergence. Early increases in inter-areal similarity were reversed in a later phase of fronto-hippocampal divergence in mid-adulthood. RMS exposure altered inter-areal similarity, especially between frontal and parahippocampal regions, that were also most active developmentally and in aging. Our results reveal how normative cortical network changes in the developing brain are influenced by early life stress. These findings suggest a new translational framework for elucidating how environmental risk factors lead to atypical development of cortical networks.

neuroscience↗

bioRxiv2023

Microbiomes of blood feeding triatomines in the context of their predatory relatives and the environment

AbstractThe importance of gut microbiomes has become generally recognized in vector biology. This study addresses microbiome signatures in North American Triatoma species of public health significance (vectors of Trypanosoma cruzi) linked to their blood feeding strategy and the natural habitat. To place the Triatoma associated microbiomes within a complex evolutionary and ecological context, we sampled sympatric Triatoma populations, related predatory reduviids, unrelated ticks, and environmental material from vertebrate nests where these arthropods reside. Along with five Triatoma species, we have characterized microbiomes of five reduviids (Stenolemoides arizonensis, Ploiaria hirticornis, Zelus longipes, and two Reduvius species), a single soft tick species, Ornithodoros turicata, and environmental microbiomes from selected sites in Arizona, Texas, Florida and Georgia. The microbiomes of predatory reduviids lack a shared core microbiota. Like in triatomines, microbiome dissimilarities among species corelate with dominance of a single bacterial taxa. These include Rickettsia, Lactobacillus, Candidatus Midichloria, and Zymobacter, which are often accompanied by known symbiotic genera, i.e., Wolbachia, Candidatus Lariskella, Asaia, Gilliamella, and Burkholderia. We have further identified compositional convergence of analyzed microbiomes in respect to the host phylogenetic distance in both blood feeding and predatory reduviids. While microbiomes of two reduviid species from Emesinae family reflect their close relationship, the microbiomes of all Triatoma species repeatedly form a distinct monophyletic cluster highlighting their phylosymbiosis. Furthermore, based on environmental microbiome profiles and blood meal analysis, we propose three epidemiologically relevant and mutually interrelated bacterial sources for Triatoma microbiomes, i.e., host abiotic environment, host skin microbiome, and pathogens circulating in host blood. ImportanceThis study places microbiomes of blood feeding North American Triatoma vectors (Reduviidae) into a broader evolutionary and ecological context provided by related predatory assassin bugs (Reduviidae), another unrelated vector species (soft tick Ornithodor turicata), and the environment these arthropods cohabit. For both vectors, microbiome analyses suggest three interrelated sources of bacteria, i.e., microbiome of vertebrate nests as their natural habitat, vertebrate skin microbiome, and pathobiome circulating in vertebrate blood. Despite an apparent influx of environment-associated bacteria into the arthropod microbiomes, Triatoma microbiomes retain their specificity, forming a distinct cluster that significantly differ from both predatory relatives and ecologically comparable ticks. Similarly, within the related predatory Reduviidae, we found the host phylogenetic distance to underlie microbiome similarities.

ecology↗

bioRxiv2023

Transdermal Electrophysiological Recordings of Diabetic Peripheral Neuropathy Using a Needle Electrode Array in Mice and Men

Diabetic peripheral neuropathy (DPN) is a common complication of diabetes. Proactive treatment options remain limited, which is exacerbated by a lack of sensitive and convenient diagnostics, especially early in disease progression or specifically to assess small fiber neuropathy (SFN), the loss of distal small diameter axons that innervate tissues and organs. We designed, fabricated, tested, and validated a first-of-its-kind medical diagnostic device for the functional assessment of transdermal small fiber nerve activity. This device, the Detecting Early Neuropathy (DEN), is an electrically conductive needle array designed to record nerve electrical activity in the skin and subdermal tissues. DEN recordings were validated across a time course of diet-induced DPN in mice, using statistical and computational analyses compared to other SFN measures. Based on these preclinical mouse data, the device design was adapted to obtain recordings in human with a flexible printed circuit board to mold to the leg or other skin regions. The DEN successfully recorded various types of neural activity in mouse and human, with or without stimulation, including validated action potentials and electromyography signals. New functional diagnostic tools like DEN offer a promising outlook for patients needing an earlier or more sensitive diagnosis of SFN/DPN, to allow for earlier and more effective treatment options, especially as more become available in the clinic in future years.

bioengineering↗

bioRxiv2022

Annexin A2 modulates phospholipid membrane composition upstream of Arp2 to control angiogenic sprout initiation

The intersection of protein and lipid biology is of growing importance for understanding how cells address structural challenges during adhesion and migration. While protein complexes engaged with the cytoskeleton play a vital role, support from the phospholipid membrane is crucial for directing localization and assembly of key protein complexes. During angiogenesis, it is well observed that dramatic cellular remodeling is necessary for endothelial cells to shift from a stable monolayer to invasive structures. However, the molecular dynamics between lipids and proteins during endothelial invasion are not defined. Here, we utilized cell culture, immunofluorescence, and lipidomic analyses to identify a novel role for the membrane binding protein Annexin A2 (ANXA2) in modulating the composition of specific membrane lipids necessary for cortical F-actin organization and adherens junction stabilization. In the absence of ANXA2, there is disorganized cortical F-actin, reduced junctional Arp2, excess sprout initiation, and ultimately failed sprout maturation. Further, we observed reduced filipin III labeling of membrane cholesterol in cells with reduced ANXA2, suggesting there is an alteration in phospholipid membrane dynamics. Lipidomic analyses reveal that 42 lipid species are altered with loss of ANXA2, including an accumulation of phosphatidylcholine (16:0_16:0). We find that supplementation of phosphatidylcholine (16:0_16:0) in wild-type endothelial cells mimics the ANXA2 knock-down phenotype, indicating that ANXA2 regulates the phospholipid membrane upstream of Arp2 recruitment and organization of cortical F-actin. Altogether these data indicate a novel role for ANXA2, and show that proper lipid modulation is a critical component of endothelial sprouting. Summary StatementAnnexin A2 modulates composition of select phospholipid species in endothelial cells needed for F-actin organization and Arp2 recruitment to endothelial adherens junctions. These events simultaneously temper sprout initiation and support sprout maturation to maintain the integrity of sprouting structures during angiogenesis

cell biology↗

bioRxiv2022

Within-host evolutionary dynamics and tissue compartmentalization during acute SARS-CoV-2 infection

The global evolution of SARS-CoV-2 depends in part upon the evolutionary dynamics within individual hosts with varying immune histories. To characterize the within-host evolution of acute SARS-CoV-2 infection, we deep sequenced saliva and nasal samples collected daily from immune and unvaccinated individuals early during infection. We show that longitudinal sampling facilitates high-confidence genetic variant detection and reveals evolutionary dynamics missed by less-frequent sampling strategies. Within-host dynamics in both naive and immune individuals appeared largely stochastic; however, we identified clear mutational hotspots within the viral genome, consistent with selection and differing between naive and immune individuals. In rare cases, minor genetic variants emerged to frequencies sufficient for forward transmission. Finally, we detected significant genetic compartmentalization of virus between saliva and nasal swab sample sites in many individuals. Altogether, these data provide a high-resolution profile of within-host SARS-CoV-2 evolutionary dynamics.

microbiology↗

bioRxiv2021

Oral Lisinopril Raises Tissue Levels of ACE2, the SARS-CoV-2 Receptor, in Healthy Male and Female Mice

Angiotensin-converting enzyme 2 (ACE2) is the established cellular receptor for SARS-CoV-2. However, it is unclear whether ACE1 inhibitors (e.g., lisinopril) or angiotensin receptor blockers (e.g., losartan) alter tissue ACE2 expression. This study sought to determine whether lisinopril or losartan, as monotherapies or in combination, change tissue levels of ACE2 in healthy male and female mice. Mice received lisinopril (10 mg/kg/day), losartan (10 mg/kg/day), or both for 21 days via drinking water. A control group received water without drug. ACE2 protein index (ACE2 protein / total protein) was determined on small intestine, lung, kidney, and brain. Oral lisinopril increased ACE2 protein index across all tissues (p < 0.0001 vs control). In contrast, the combination of lisinopril plus losartan did not increase ACE2 levels in any tissue (p = 0.89 vs control) and even decreased tissue expression of the Ace2 gene (p < 0.001 vs control). Tissue ACE2 remained elevated in mice 21 days after cessation of lisinopril (p = 0.02). Across both cohorts, plasma ACE2 did not correlate with ACE2 protein index in any tissue. A sex difference was observed: kidney ACE2 levels were higher in males than females (p < 0.0001). Oral lisinopril increases ACE2, the cellular receptor for SARS-CoV-2, in tissues that are relevant to the transmission and pathogenesis of COVID-19. Remarkably, the addition of losartan prevented lisinopril-induced increases in ACE2 across tissues. These results suggest that ACE inhibitors and angiotensin receptor blockers interact to determine tissue levels of ACE2.

pharmacology and toxicology↗

bioRxiv2021

A LINCS microenvironment perturbation resource for integrative assessment of ligand-mediated molecular and phenotypic responses

The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods (synapse.org/LINCS_MCF10A). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes.

systems biology↗

bioRxiv2020

Reduced ech-6 Expression Attenuates Fat-induced Premature Aging in C. elegans

Deregulated energy homeostasis represents a hallmark of aging and results from complex gene-by-environment interactions. Here, we discovered that reducing the expression of the gene ech-6 encoding enoyl-CoA hydratase remitted fat diet-induced deleterious effects on lifespan in Caenorhabditis elegans, while a basal expression of ech-6 was important for survival under normal dietary conditions. Lipidomics revealed that supplementation of fat in ech-6-silenced worms had marginal effects on lipid profiles, suggesting an alternative fat utilization for energy production. Transcriptomics further suggest a causal relation between the lysosomal pathway, energy production, and the longevity effect conferred by the interaction between ech-6 and high-fat diets. Indeed, enhancing energy production from endogenous fat by overexpressing lysosomal lipase lipl-4 recapitulated the lifespan effects of high-fat diets on ech-6-silenced worms. Collectively, these results reveal that the gene ech-6 modulates metabolic flexibility and may be a target for promoting metabolic health and longevity.

cell biology↗

bioRxiv2020

Metabolomics and lipidomics in C. elegans using a single sample preparation

Comprehensive metabolomic and lipidomic mass spectrometry methods are in increasing demand, for instance in research related to nutrition and aging. The nematode C. elegans is a key model organism in these fields, due to the large repository of available C. elegans mutants and their convenient natural lifespan. Here, we describe a robust and sensitive analytical method for the semi-quantitative analysis of >100 polar (metabolomics) and >1000 apolar (lipidomics) metabolites in C. elegans, using a single sample preparation. Our method is capable of reliably detecting a wide variety of biologically relevant metabolic aberrations in, for instance, glycolysis and the TCA cycle, pyrimidine metabolism and complex lipid biosynthesis. In conclusion, we provide a powerful analytical tool that maximizes metabolic data yield from a single sample.Competing Interest StatementThe authors have declared no competing interest.View Full Text

biochemistry↗

bioRxiv2019

The drivers of West Nile virus human illness: fine scale dynamic effects of weather, mosquito infection, social, and biological conditions

West Nile virus (WNV) has consistently been reported to be associated with human cases of illness in the region near Chicago, Illinois. However, the number of reported cases of human illness varies across years, with intermittent outbreaks. Several dynamic factors, including temperature, rainfall, and infection status of vector mosquito populations, are responsible for much of these observed variations. However, local landscape structure and human demographic characteristics also play a key role. The geographic and temporal scales used to analyze such complex data affect the observed associations. Here, we used spatial and statistical modeling approaches to investigate the factors that drive the outcome of WNV human illness on fine temporal and spatial scales. Our approach included multi-level modeling of long-term weekly data from 2005 to 2016, with weekly measures of mosquito infection, human illness and weather combined with more stable landscape and demographic factors on the geographical scale of 1000m hexagons. We found that hot weather conditions, warm winters, and higher MIR in earlier weeks increased the probability of an area of having a WNV human case. Higher population and the proportion of urban light intensity in an area also increased the probability of observing a WNV human case. A higher proportion of open water sources, percentage of grass land, deciduous forests, and housing built post 1990 decreased the probability of having a WNV case. Additionally, we found that cumulative positive mosquito pools up to 31 weeks can strongly predict the total annual human WNV cases in the Chicago region. This study helped us to improve our understanding of the fine-scale drivers of spatiotemporal variability of human WNV cases.

bioinformatics↗

bioRxiv2019

Mastitis risk effect on the economic consequences of paratuberculosis control in dairy cattle: A stochastic modeling study

The benefits and efficacy of control programs for herds infected with Mycobacterium avium subsp. paratuberculosis (MAP) have been investigated under various contexts. However, most previous research investigated paratuberculosis control programs in isolation, without modeling the potential association with other dairy diseases. This paper evaluated the benefits of MAP control programs when the herd is also affected by mastitis, a common disease causing the largest losses in dairy production. The effect of typically suggested MAP controls were estimated under the assumption that MAP infection increased the rate of clinical mastitis. We evaluated one hundred twenty three control strategies comprising various combinations of testing, culling, and hygiene, and found that the association of paratuberculosis with mastitis alters the ranking of specific MAP control programs, but only slightly alters the cost-effectiveness of particular MAP control components, as measured by the distribution of net present value of a representative U.S. dairy operation. In particular, although testing and culling for MAP resulted in a reduction in MAP incidence, that control led to lower net present value (NPV) per cow. When testing was used, ELISA was more cost-effective than alternative testing regimes, especially if mastitis was explicitly modeled as more likely in MAP-infected animals, but ELISA testing was only significantly associated with higher NPV if mastitis was not included in the model at all. Additional hygiene was associated with a lower NPV per cow, although it lowered MAP prevalence. Overall, the addition of an increased risk of mastitis in MAP-infected animals did not change model recommendations as much as failing to consider mastitis at all.

epidemiology↗

bioRxiv2018

A Data-driven Individual-based Model of Infectious Disease in Livestock Operation: A Validation Study for Paratuberculosis

Chronic livestock diseases cause large financial loss and affect the animal health and welfare. Controlling these diseases mostly requires precise information on both individual animal and population dynamics to inform farmers decision. Mathematical models provide opportunities to test different control and elimination options rather implementing them in real herds, but these models require valid parameter estimation and validation. Fitting these models to data is a difficult task due to heterogeneities in livestock processes. In this paper, we develop an infectious disease modeling framework for a livestock disease (paratuberculosis) that is caused by Mycobacterium avium subsp. paratuberculosis (MAP). Infection with MAP leads to reduced milk production, pregnancy rates, and slaughter value and increased culling rates in cattle and causes significant economic losses to the dairy industry in the US. These economic effects are particularly important motivations in the control and elimination of MAP. In this framework, an individual-based model (IBM) of a dairy herd was built and a MAP infection was integrated on top of it. Once the model produced realistic dynamics of MAP infection, we implemented an evaluation method by fitting it to data from three dairy herds from the Northeast region of the US. The model fitting exercises used least-squares and parameter space searching methods to obtain the best-fitted values of selected parameters. The best set of parameters were used to model the effect of interventions. The results show that the presented model can complement real herd statistics where the intervention strategies suggested a reduction in MAP but no elimination was observed. Overall, this research not only provides a complete model for MAP infection dynamics in a cattle herd, but also offers a method for estimating parameter by fitting IBM models.

epidemiology↗