Samarasinghe, A. | bioRxiv Science

bioRxiv2026

Quantifying Crop Disease Trait Dynamics through Longitudinal Imaging and Temporal Analytics

Reliable and objective phenotyping is essential for plant breeding programs to characterize genetic variation and accelerate crop improvement. Conventional disease assessment relies on expert visual scoring, which is labor-intensive, subjective, and prone to inter- and intra-rater variability. Although image-based phenotyping methods have been proposed, many require manual intervention, specialized imaging setups, or single time-point measurements, limiting their ability to capture disease progression over time. Here, we present a pipeline for longitudinal plant disease phenotyping that quantifies wheat stripe rust and leaf rust progression from time-series images. The pipeline performs semi-automated leaf and automated pustule segmentation from images acquired in situ, enabling objective disease severity estimation with minimal user intervention and without requiring solid backgrounds or manual leaf manipulation or detachment. By extracting temporal traits, including disease severity trajectories and standardized area under the disease progress curve, the method provides a comprehensive characterization of disease development throughout infection. Association between automated and expert assessments was moderate for stripe rust (R2 = 0.58) and strong for leaf rust (R2 = 0.85), while expert inter-rater reliability was moderate for both diseases (ICC = 0.675 and 0.800, respectively). The proposed approach establishes a scalable and reproducible framework for longitudinal disease phenotyping in controlled environments, with broad applications in disease resistance screening and crop breeding.

bioinformatics↗

bioRxiv2019

Allergic inflammation hinders synergistic viral-bacterial co-infection in C57BL/6 mice

Asthma is a chronic airways disease that can be exacerbated during respiratory infections. Our previous findings that the inflammatory state of allergic airways at the time of influenza A virus (IAV) infection in combination with epidemiologic findings that asthmatics were less likely to suffer from severe influenza during the 2009 pandemic suggest that additional complications of influenza, such as increased susceptibility to bacterial superinfection, may be mitigated in the allergic host. To test this hypothesis, we developed a murine model of triple-disease in which mice were first rendered allergic to Aspergillus fumigatus and co-infected with IAV and Streptococcus pneumoniae seven days apart. Significant alterations to known synergistic effects of co-infection were noted in the allergic mice including reduced morbidity and mortality, bacterial burden, maintenance of alveolar macrophages, and reduced lung inflammation and damage. The lung microbiome of allergic mice differed from that of non-allergic mice during co-infection. To investigate the impact of the microbiome on the pathogenesis of lung disease, we induced a perturbation with a short course of fluoroquinolone antibiotic that is often prescribed for lung infections. A significant change in the microbiome was complemented with alterations to the inflammatory profile and a drastic increase in pro-inflammatory cytokines in allergic mice which were now susceptible to severe disease from IAV and S. pneumoniae co-infection. Our data suggest that responses to co-infection in allergic hosts likely depends on the immune and microbiome states and that antibiotics should be used with caution in individuals with underlying chronic lung disease. Author Summary Asthma is a condition of the lungs that affects millions worldwide. Traditionally, respiratory infections are considered to have a negative impact on asthmatics. However, epidemiological data surrounding the 2009 influenza pandemic suggest that asthmatics may be better equipped to counter severe influenza including bacterial pneumonia. Herein, we introduce a novel mouse model system designed to recapitulate an influenza virus and Streptococcal co-infection in a host with fungal asthma. We found that underlying allergic asthma protects against severe disease induced by co-infection. Mice with underlying allergic inflammation had reduced damage to the lungs and did not show signs of respiratory distress. Among the differences noted in the allergic mice that were protected from viral and bacterial co-infection, was the lung microbiome. Allergic mice lost their protection from co-infection after we perturbed their lung microbiome with antibiotics suggesting that the lung microbiome plays a role in host immunity against invading pathogens.

pathology↗