Avian influenza (AI), particularly highly pathogenic avian influenza (HPAI), represents a serious and growing threat to global poultry production, international trade, and human health security. Control of AI is complicated by the high evolutionary rate of influenza A viruses, which drives antigenic diversity and ongoing emergence of novel strains. Effective surveillance and disease management therefore depend on timely and accurate diagnostics. While conventional methods—including virus isolation, reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and enzyme-linked immunosorbent assays (ELISAs)—remain effective and widely used, they are limited by long turnaround times, the need for specialized equipment, and reliance on highly trained personnel. In addition, strict state and federal regulatory requirements restrict testing to a limited number of authorized laboratories. Although these regulations are essential for maintaining diagnostic accuracy and quality assurance, they place substantial strain on laboratory capacity during outbreaks and delay actionable results. The need for rapid, on-site decision making has driven interest in alternative diagnostic approaches, including biosensor technologies. A major limitation of current diagnostic strategies is the lack of robust DIVA (Differentiating Infected from Vaccinated Animals) capability. In countries such as the United States, where poultry vaccination against AI is not routinely practiced, the absence of DIVA-compatible diagnostics has hindered adoption of vaccination as a disease management tool, as seropositive birds and products face significant trade restrictions. Biosensor platforms capable of enabling DIVA strategies offer a potential pathway to support vaccination while preserving surveillance integrity. This review examines the current landscape of AI and HPAI diagnostics, emphasizing the limitations of traditional approaches and the opportunities presented by biosensor platforms. We evaluate electrochemical, optical, piezoelectric, and nucleic-acid-based biosensors, with particular attention to biorecognition strategies, performance metrics, field deployability, and applications supporting subtype discrimination, DIVA implementation, and One Health surveillance.

Rapid antimicrobial susceptibility testing (AST) is crucial for combating antimicrobial resistance and guiding effective therapy. Conventional phenotypic AST methods are often time-consuming, requiring 18-72 h for results, while genotypic approaches often depend on pre-existing knowledge of resistance markers. Although nucleic acid-based phenotypic AST methods have reduced turnaround time, attempts to shorten antibiotic exposure often produce only small differences between susceptible and resistant bacteria. Consequently, most loop-mediated isothermal amplification (LAMP)-based phenotypic AST assays still require prolonged antibiotic exposure (up to 4 h) or rely on sophisticated high-resolution nucleic acid detection, such as digital LAMP, to accurately detect these subtle changes, limiting their simplicity. Therefore, there is a critical need to develop a rapid assay with both short antibiotic exposure times and a simple readout. To address this unmet need, we developed PMAxx dye-assisted colorimetric Dual DNAzyme-LAMP (PD-cDDLAMP), a rapid nucleic acid-based phenotypic AST method that enhances suppression of nucleic acid amplification from antibiotic-susceptible bacteria through the selective binding of photoreactive DNA-crosslinker dye (PMAxx) to the DNA of membrane-compromised cells. This strategy enables reliable discrimination between antibiotic-resistant bacteria ("signal-on") and antibiotic-susceptible bacteria ("signal-off") after only 30 min of antibiotic exposure using a user-friendly colorimetric DNAzyme-LAMP readout system. PD-cDDLAMP achieved 91.7% sensitivity, 83.3% specificity, and 87.5% accuracy in detecting Escherichia coli exposed to ampicillin and tetracycline, outperforming current methods by reducing antibiotic exposure time to just 30 min. The method was further validated in spiked milk samples, demonstrating its potential for on-site AST in dairy farming. PD-cDDLAMP's simplicity, speed, and reduced workflow complexity make it a promising tool for rapid AST. IMPORTANCE:Rapid, reliable antimicrobial susceptibility testing (AST) is essential for guiding targeted therapy and combating the escalating threat of antimicrobial resistance (AMR). However, current phenotypic ASTs are too slow for urgent decision-making, and genotypic assays cannot fully capture emerging or unknown resistance mechanisms. The PMAxx dye-assisted colorimetric dual DNAzyme-loop-mediated isothermal amplification (PD-cDDLAMP) assay introduced in this work provides a rapid nucleic acid-based phenotypic AST capable of distinguishing antibiotic-resistant from susceptible bacteria within 30 min of antibiotic exposure. By combining PMAxx-mediated suppression of nucleic acid amplification in susceptible cells with equipment-free colorimetric DNAzyme-LAMP readout, PD-cDDLAMP bridges the gap between speed and phenotypic accuracy. Its high diagnostic performance, compatibility with complex matrices such as milk, and minimal instrumentation requirements position this method as a promising point-of-care tool for clinical microbiology laboratories and on-site testing environments. PD-cDDLAMP has the potential to significantly shorten time-to-result while maintaining reliability, thereby supporting antimicrobial stewardship.

MicroRNAs (miRNAs) are promising biomarkers for early cancer detection, but their low abundance and matrix interference continue to limit rapid, point-of-care (POC) assays. Here, we report a rapid, sensitive, and label-free biosensing platform for the detection of miRNA-133a-3p, a tumor-suppressive biomarker implicated in various cancers. The sensor operates on a non-faradaic capacitive principle, utilizing gold-plated printed-circuit-board interdigitated electrodes functionalized with thiolated single-stranded DNA capture probes. Alternating current electrokinetic (ACEK) effects are integrated with capacitive readout to achieve a single-step operation that enhances target transport to the interface, accelerates hybridization, and amplifies the capacitance transient. Assay conditions were optimized to achieve a linear dynamic range from 1 fM to 1 pM with a high sensitivity of 2.44%/min per decade and a limit of detection (LOD) as low as 0.56 fM in a standard buffer. High specificity was confirmed through selectivity tests against non-complementary miRNAs. For serum analysis, only a simple 1:100 dilution is required prior to measurement, yielding a LOD of 0.74 fM in diluted serum (equivalent to 74 fM in neat serum). This portable and cost-effective ACEK-capacitive platform enables fast and selective miRNA detection in complex matrices with minimal sample preparation.

Shiga toxin-producing Escherichia coli (STEC) is causing outbreaks worldwide and a rapid detection method is urgently needed. Loop-mediated isothermal amplification (LAMP) has attracted attention in the development of pathogen detection methods; however, current methods for the detection of LAMP amplicon suffer some drawbacks. In this study, we designed a new LAMP method by incorporating peroxidase-mimicking G-quadruplex DNAzyme for a simple colorimetric detection of the LAMP amplicon. As the new method produces LAMP amplicon containing two DNAzyme molecules per amplification unit, the method was termed colorimetric Dual DNAzyme LAMP (cDDLAMP). cDDLAMP was developed targeting 3 common STEC's virulence genes (stx1, stx2, and eae) that are associated with serious human illnesses such hemorrhagic colitis and hemolytic-uremic syndrome. Immunomagnetic enrichment was used for specific, ultrasensitive, and fast detection of STEC in food samples (leafy vegetables and milk). The sensitivity of cDDLAMP ranged from 1-100 CFU/mL in pure culture to 100-103 CFU/mL in spiked milk, and 104-109 CFU/25g of lettuce. No cross-reaction with other generic E. coli strains and non-E. coli bacteria was observed. The color signal could be observed by the naked eye or analyzed by either UV-Vis spectra or smartphone platforms. Therefore, the cDDLAMP assay is a cost-effective method for detecting STEC strains without expensive machines or extraction methods.

Escherichia coli (E. coli) remains a major concern in poultry production due to its ability to incite foodborne illness and public health crisis, zoonotic potential, and the increasing prevalence of antibiotic-resistant strains. The contamination of poultry products with pathogenic E. coli, including avian pathogenic E. coli (APEC) and Shiga toxin-producing E. coli (STEC), presents risks at multiple stages of the poultry production cycle. The stages affected by E. coli range from, but are not limited to, the hatcheries to grow-out operations, slaughterhouses, and retail markets. While traditional detection methods such as culture-based assays and polymerase chain reaction (PCR) are well-established for E. coli detection in the food supply chain, their time, cost, and high infrastructure demands limit their suitability for rapid and field-based surveillance—hindering the ability for effective cessation and handling of outbreaks. Biosensors have emerged as powerful diagnostic tools that offer rapid, sensitive, and cost-effective alternatives for E. coli detection across various stages of poultry development and processing where detection is needed. This review examines current biosensor technologies designed to detect bacterial biomarkers, toxins, antibiotic resistance genes, and host immune response indicators for E. coli. Emphasis is placed on field-deployable and point-of-care (POC) platforms capable of integrating into poultry production environments. In addition to enhancing early pathogen detection, biosensors support antimicrobial resistance monitoring, facilitate integration into Hazard Analysis Critical Control Points (HACCP) systems, and align with the One Health framework by improving both animal and public health outcomes. Their strategic implementation in slaughterhouse quality control and marketplace testing can significantly reduce contamination risk and strengthen traceability in the poultry value chain. As biosensor technology continues to evolve, its application in E. coli surveillance is poised to play a transformative role in sustainable poultry production and global food safety.

Transmissible spongiform encephalopathies (TSEs), also known as prion diseases, are fatal neurodegenerative disorders found across various host species. Chronic wasting disease (CWD) of cervids is among the TSEs afflicting wildlife populations. Widely distributed in North America, CWD has a devastating impact on cervid populations, and is an economic burden to government agencies and the cervid industry. Because prion diseases have no treatment, surveillance is critical to managing CWD. Current diagnostic approaches infer TSE disease status via measurement of pathogenic prion (PrPSc) protein, but lack the sensitivity for detection of CWD prion in antemortem and environmental samples. Next generation prion amplification assays such as Protein Misfolding Cyclic Amplification (PMCA) and Real-Time Quaking-induced Conversion (RT-QuIC) offer sufficient sensitivity for this purpose but suffer from long turnaround times and are resource intensive. As an alternative method, we present a proof-of-concept test that uses Nanoparticle-Enhanced, Aptamer Template Loop-mediated Isothermal Amplification (NEAT-LAMP) using cellular prion (PrPC) as a model protein. We demonstrate that this fast, sensitive method outperforms current immunoassays with a sensitivity of 10 pM. NEAT-LAMP leverages existing capabilities of diagnostic laboratories and has the potential to improve CWD management efforts.

Pituitary pars intermedia dysfunction (PPID) is a neurodegenerative disease of senior horses. Loss of dopaminergic inhibition of the melanotropes of the pars intermedia leads to increased concentrations of pro-opiomelanocortin (POMC)-derived peptides. Diagnosis is challenging due to pre-analytical variables, such as sample storage, handling, and time to analysis. Our objective was to develop an ELISA for ACTH measurement, which could ultimately form the basis for a stall-side equine ACTH test. We selected 2 ACTH-specific monoclonal antibodies, CBL57 and EPR20361-248, based on the recognition of separate epitopes, strong and rapid color change, and minimal background interference, including no cross-reactivity with themselves, each other, and the test reagents. CBL57 was chosen as the detection antibody (or secondary antibody). EPR20361-248, functionalized on superparamagnetic iron oxide beads, was chosen as the capture antibody (or primary antibody) to bind ACTH in plasma. The incorporation of magnetic beads marks the initial stage in establishing a platform that could potentially be utilized in the field, similar to other stall-side tests. The concentrations of antibodies, magnetic beads, and incubation durations were optimized. Our immunoassay detected unglycosylated rat recombinant ACTH. Further studies are ongoing to optimize and validate our assay using equine plasma and serum samples.

Foodborne bacteria like Escherichia coli threaten global food security, necessitating affordable, on-site detection methods, especially in resource-limited settings. This study optimized loop-mediated isothermal amplification (LAMP) integrated with peroxidase-mimicking G-quadruplex DNA structures (DNAzyme), termed DNAzyme-LAMP which was designed to incorporate two different catalytic DNAzymes per amplification unit, enabling colorimetric detection of E. coli in leafy vegetables and milk samples. Additionally, we introduce a novel electrochemical method that enhances analytical sensitivity. The optimized DNAzyme-LAMP achieved a detection limit below 6.3 CFU per reaction or 0.1 aM gene copies. This system lays the groundwork for the development of on-site biosensors and can be adapted for detecting other foodborne pathogens.

With the ever-increasing proliferation of edge devices for applications, such as home automation and vehicle systems, their security vulnerabilities have received additional attention. A recent type of attack, physical fault injections, are particularly powerful as they can compromise these devices by skipping necessary instructions through physical methods, such as induced voltage glitches. Hence, they can trigger a wide range of software behavior anomalies and vulnerabilities not caused by the programs themselves. These attacks allow adversaries to carry out severe security breaches such as control flow hijacking and information leakage, even if the original device firmware has been well tested. To defend against physical fault injections, this paper develops an innovative approach based on a runtime attestation of code execution, i.e., given a sequence of instructions, they should be executed thoroughly and correctly in a verified manner. Hence, instruction anomalies can be detected and reported if faults are injected. This protection mechanism does not require additional hardware or specialized instructions. Instead, it leverages a lightweight virtual machine to protect critical code segments such as password-related operations. It integrates two techniques: blockchain-based instruction integrity assurance and memory randomization-based data protection. We fully implemented this framework on an AVR-based microcontroller, and our evaluation results demonstrate that our methodology is practical enough to effectively prevent a wide range of hardware-based fault injection attacks, paving the way for more secure edge applications.

The evolution of cooperation in microbes is a challenge to explain because microbes producing costly goods for the benefit of any strain types (cooperators) often withstand the threat of elimination by interacting with individuals that exploit these benefits without contributing (defectors). Here we developed an individual-based model to investigate whether partial privatization via the partial secretion of goods can favor cooperation in structured, surface-attaching microbial populations, biofilms. Whether partial secretion can favor cooperation in biofilms is unclear for two reasons. First, while partial privatization has been shown to foster cooperation in unstructured populations, little is known about the role of partial privatization in biofilms. Second, while limited diffusion of goods favors cooperation in biofilms because molecules are more likely to be shared with genetically-related individuals, partial secretion reduces goods that could have been directed towards genetically related individuals. Our results show that although partial secretion weakens the role that limited diffusion has on fostering cooperation, partial secretion favors cooperation in biofilms. Overall, our results provide predictions that future experiments could test to reveal contributions of relatedness and partial secretion to the social evolution of biofilms.

Comprehensive disease surveillance has not been conducted in elk (Cervus canadensis) in Tennessee, US, since their reintroduction to the state 20 yr ago. We identified causes of death, estimated annual survival, and identified pathogens of concern in elk at the North Cumberland Wildlife Management Area (NCWMA), Tennessee, US. In 2019 and 2020, we captured 29 elk (21 females, eight males) using chemical immobilization and fitted individuals with GPS collars with mortality sensors. Elk that died between February 2019 and February 2022 were necropsied to identify causes of death; these included disease associated with meningeal worm (Parelaphostrongylus tenuis; n=3), poaching (n=1), vehicular collision (n=1), legal hunter harvest (n=1), and unknown due to carcass degradation (n=3). Using data from GPS collars and known-fate survival models, we estimated an average yearly survival rate of 80.2%, indicating that survival had not significantly increased from soon after elk reintroduction (79.9%). We collected blood, tissue, feces, and ectoparasites opportunistically from anesthetized elk for health surveillance. We identified lone star ticks (Amblyomma americanum; n=53, 85.5%; 95% confidence interval [CI], 73.72-92.75), American dog ticks (Dermacentor variabilis; n=8, 12.9%; 95% CI, 6.13-24.40), and black-legged ticks (Ixodes scapularis; n=1, 1.6%; 95% CI, 0.08-9.83). We detected evidence of exposure to Anaplasma marginale (100%; 95% CI, 84.50-100.00), Leptospira interrogans (70.4%; 95% CI, 49.66-85.50), Toxoplasma gondii (55.6%; 95% CI, 35.64-73.96), epizootic hemorrhagic disease virus (51.9%; 95% CI, 32.35-70.84), and Theileria cervi (25.9%; 95% CI, 11.78-46.59). Johne's disease (Mycobacterium avium subsp. paratuberculosis) is potentially established within the population, but has not been previously documented in eastern elk populations. Disease associated with P. tenuis was a primary cause of death, and more research is needed to understand its ecology and epidemiology. Research to determine population implications of other detected pathogens at the NCWMA is warranted.

The amino-terminal domain of influenza A virus matrix protein (residues 1-164) was crystallized at pH 7 into a new crystal form in space group P1. This packing of the protein implies that M1(1-164) was monomeric in solution when it crystallized. Otherwise, the structure of the M1 fragment in the pH 7 crystals was the same as the monomers in crystals formed at pH 4 where crystal packing resulted in dimer formation [B. Sha and M. Luo, 1997, Nature Struct. Biol. 4, 239-244]. Analysis of intact M1 protein, the N-terminal domain, and the remaining C-terminal fragment (residues 165-252) in solution also showed that the N-terminal domain was monomeric with the same dimensions as determined from the crystal structure. Intact M1 protein was also monomeric but with an elongated shape due to the presence of the C-terminal part. Circular dichroism showed that the C-terminal part of M1 contained helical structure. A model for soluble M1 is presented, based on the assumption that the C-terminal domain is spherical, in which the N- and C-terminal domains are connected by a linker sequence which is available for proteolytic attack.

Sensitive and specific detection of pathogenic bacteria was important for early and appropriate antibiotic treatment of infected humans and animals. Also, the detection of Gram-negative bacteria, such as Escherichia, had a significant implication in food safety as the organisms were a major cause of food-borne illnesses. Our previous studies demonstrated that dielectrophoretic (DEP) capacitive sensing could be used to accelerate the detection by simultaneous DEP attraction of target bioparticles to the sensor surface and direct monitoring of interfacial capacitance. In this report, we implemented stepwise voltages for the detection of Gram-negative bacteria with high sensitivity and selectivity. The sensor achieved a detection limit of 282.1 cells/mL and a dynamic range of 282.1~2.82×10 4 cells/mL. The tunable dielectrophoresis approach is applicable for improved detection of other bioparticles.

Microorganisms produce costly cooperative goods whose benefit is partially shared with nonproducers, called 'mixed' goods. The Black Queen Hypothesis predicts that partial privatization has two major evolutionary implications. First, to favor strains producing several types of mixed goods over nonproducing strains. Second, to favor the maintenance of cooperative traits through different strains instead of having all cooperative traits present in a single strain (metabolic specialization). Despite the importance of quorum sensing regulation of mixed goods, it is unclear how partial privatization affects quorum sensing evolution. Here, we studied the influence of partial privatization on the evolution of quorum sensing. We developed a mathematical population genetics model of an unstructured microbial population considering four strains that differ in their ability to produce an autoinducer (quorum sensing signaling molecule) and a mixed good. Our model assumes that the production of the autoinducers and the mixed goods is constitutive and/or depends on quorum sensing. Our results suggest that, unless autoinducers are costless, partial privatization cannot favor quorum sensing. This result occurs because with costly autoinducers: (1) a strain that produces both autoinducer and goods (fully producing strain) cannot persist in the population; (2) the strain only producing the autoinducer and the strain producing mixed goods in response to the autoinducers cannot coexist, i.e., metabolic specialization cannot be favored. Together, partial privatization might have been crucial to favor a primordial form of quorum sensing-where autoinducers were thought to be a metabolic byproduct (costless)-but not the transition to nowadays costly autoinducers.

On-site detection of microRNAs in blood-borne extracellular vesicles is important for the timely diagnosis of various diseases and physiologic conditions, including pregnancy status. This work developed a rapid, highly -sensitive capacitive biosensor to detect bovine embryonic mortality-related microRNA, miRNA-16b, in serum extracellular vesicles. The sensor was developed to achieve rapid, highly sensitive and specific detection of miRNA-16b, based on AC electrokinetically accelerated capacitive detection of DNA probe-microRNA hybridi-zation. Using interdigitated electrodes functionalized with complementary DNA probes, this sensing method integrated capacitive measurement with simultaneous AC electrokinetic convection of analytes. Consequently, trace level microRNAs can be quantitatively detected in 30 s, with a detection limit of 22 aM from analytical buffer and 323 aM from neat serum over a linear dynamic range from 0.1 fM to 1 pM. The work also developed a simple and rapid pretreatment protocol to release miRNAs from extracellular vesicles in serum. As a result, the sensor can yield results from serum samples in minutes and diagnose embryonic mortality at day 17 of gestation with a sensitivity of 90.00% and specificity of 88.89% for clinical bovine serum samples. The sensor is fabricated from low-cost printed circuit board electrodes and is mass-production friendly. This rapid and sensitive sensor provides a foundation technology for the development of on-site diagnosis in various human and animal health applications.

Effective and efficient animal disease detection and control have drawn increasing attention in smart farming in recent years. It is crucial to explore how to harvest data and enable data-driven decision making for rapid diagnosis and early treatment of infectious diseases among herds. This article proposes an IoT-based animal social behavior sensing framework to model mastitis propagation and infer mastitis infection risks among dairy cows. To monitor cow social behaviors, we deploy portable GPS devices on cows to track their movement trajectories and contacts with each other. Based on those collected location data, we build directed and weighted cattle social behavior graphs by treating cows as vertices and their contacts as edges, assigning contact frequencies between cows as edge weights, and determining edge directions according to contact spatial-temporal information. Then, we propose a flexible probabilistic disease transmission model, which considers both direct contacts with infected cows and indirect contacts via environmental contamination, to estimate and forecast mastitis infection probabilities. Our model can answer two common questions in animal disease detection and control: 1) which cows should be given the highest priorities for an investigation to determine whether there are already infected cows on the farm and 2) how to rank cows for further screening when only a tiny number of sick cows have been identified. Both theoretical and simulation-based analytics of in-the-field experiments (17 cows and more than 70-h data) demonstrate the proposed framework's effectiveness. In addition, somatic cell count (SCC) mastitis tests validate our predictions as correct in real-world scenarios.

A sensitive and efficient method for microRNAs (miRNAs) detection is strongly desired by clinicians and, in recent years, the search for such a method has drawn much attention. There has been significant interest in using miRNA as biomarkers for multiple diseases and conditions in clinical diagnostics. Presently, most miRNA detection methods suffer from drawbacks, e.g., low sensitivity, long assay time, expensive equipment, trained personnel, or unsuitability for point-of-care. New methodologies are needed to overcome these limitations to allow rapid, sensitive, low-cost, easy-to-use, and portable methods for miRNA detection at the point of care. In this work, to overcome these shortcomings, we integrated capacitive sensing and alternating current electrokinetic effects to detect specific miRNA-16b molecules, as a model, with the limit of detection reaching 1.0 femto molar (fM) levels. The specificity of the sensor was verified by testing miRNA-25, which has the same length as miRNA-16b. The sensor we developed demonstrated significant improvements in sensitivity, response time and cost over other miRNA detection methods, and has application potential at point-of-care.

Mycobacterium avium subsp. paratuberculosis (MAP) causes a chronic inflammatory intestinal disease, called Johne's disease (JD) in many ruminants. In the dairy industry, JD is responsible for significant economic losses due to decreased milk production and premature culling of infected animals. Test-and-cull strategy in conjunction with risk management is currently recommended for JD control in dairy herds. However, current diagnostic tests are labor-intensive, time-consuming, and/or too difficult to operate on site. In this study, we developed a new method for the detection of anti-M. paratuberculosis antibodies from sera of M. paratuberculosis-infected animals. M. paratuberculosis antigen-coated magnetic beads were sequentially reacted with bovine serum followed by a horseradish peroxidase (HRP)-labeled secondary antibody. The reaction of HRP with its substrate was then quantitatively measured electrochemically using a redox-active probe, ferrocyanide. After optimization of electrochemical conditions and concentration of the redox-active probe, we showed that the new electrochemical detection method could distinguish samples of M. paratuberculosis-infected cattle from those of uninfected cattle with greater separation between the two groups of samples when compared with a conventional colorimetric testing method. Since electrochemical detection can be conducted with an inexpensive, battery-operated portable device, this new method may form a basis for the development of an on-site diagnostic system for JD.

Bovine mastitis is the most economically important infectious disease in dairy industry, and Escherichia coli (E. coli) is one of the major causative pathogens. Rapid identification and quantitative detection of E. coli are of great importance for bovine mastitis control and milk quality monitoring. Capitalizing on dielectrophoresis and interphase capacitance sensing, we have developed an immunosensor for E. coli detection by modifying low cost commercial microelectrodes with an E. coli specific antibody. The limit of detection reaches as low as 775 cells/mL within a 15 s' response time, which can satisfy the requirement for on-site detection and field diagnosis of bovine mastitis. To demonstrate the sensor's specificity, tests against Staphylococcus aureus and Streptococcus uberis samples are performed showing negligible responses, and the selectivity is calculated to be 3063: 1. Furthermore, a simple pretreatment protocol is developed for on-site testing of raw milk, which only involves incubation, centrifugation and dilution steps. Then correct detection of E. coli is demonstrated for both artificially inoculated and infected field milk samples. This immunosensor and the corresponding protocol have advantages in speed, sensitivity, specificity, operability, and low cost, which make it highly promising for on-site pathogen detection of bovine mastitis.

Abstract Cornus kousa (Asian dogwood), an East Asia native tree, is the most economically important species of the dogwood genus, owing to its desirable horticultural traits and ability to hybridize with North America‐native dogwoods. To assess the species genetic diversity and to better inform the ongoing and future breeding efforts, we assembled an herbarium and arboretum collection of 131 noncultivated C. kousa specimens. Genotyping and capillary electrophoresis analyses of our C. kousa collection with the newly developed genic and published nuclear genomic microsatellites permitted assessment of genetic diversity and evolutionary history of the species. Regardless of the microsatellite type used, the study yielded generally similar insights into the C. kousa diversity with subtle differences deriving from and underlining the marker used. The accrued evidence pointed to the species distinct genetic pools related to the plant country of origin. This can be helpful in the development of the commercial cultivars for this important ornamental crop with increased pyramided utility traits. Analyses of the C. kousa evolutionary history using the accrued genotyping datasets pointed to an unsampled ancestor population, possibly now extinct, as per the phylogeography of the region. To our knowledge, there are few studies utilizing the same gDNA collection to compare performance of genomic and genic microsatellites. This is the first detailed report on C. kousa species diversity and evolutionary history inference.