Biology subjects

Lovelace, A.

Publications and source records attributed to Lovelace, A..

6 recordsLinked to original sources

bioRxiv2025

From minutes to bounds: A probabilistic UV-C control and a shape-only morphological fingerprint for postharvest Colletotrichum

Postharvest losses in high-value horticultural crops such as cacao and coffee are often driven by Colletotrichum spp. and other latent fruit pathogens. Ultraviolet-C (UV-C) is increasingly deployed as a chemical-free postharvest technology, yet prescriptions remain framed in minutes rather than in probabilistic guarantees of disease control and safety. We present a dual framework that (1) establishes conservative confidence bounds on survival and (2) validates a "shape-only" morphological fingerprint. This approach addresses the biological complexity of host-pathogen interactions by quantifying isolate-specific heterogeneity, rather than averaging it away. We utilized a large Colletotrichum dataset (n = 5,363) from cacao and coffee, spanning diverse treatments including UV-C, UV-B, and sonication. First, focusing on the Coffee UV-C cohort ([~]10 min), we quantified this heterogeneity; the most conservative Clopper-Pearson upper 95% bound on survival reached 1.000, highlighting partial survival events (e.g., isolate P24-88) under otherwise high-efficacy conditions. This probabilistic framework captures the "tail-risk" of biological resilience instead of assuming complete kill. Second, we trained machine learning models on the full dataset using only geometric features (e.g., aspect ratio, asymmetry), explicitly excluding all primary size metrics. Serving as a rapid physiological indicator of UV-induced stress, these "shape-only" models successfully predicted pathogen host-origin (Accuracy {approx} 0.93) and post-treatment survival (R{superscript 2} {approx} 0.74). The signals ability to generalize across UV-B and sonication confirms that geometry, not just growth reduction, carries a robust and transferable physiological stress signature. This work provides a device-agnostic, probabilistic control platform, replacing time-based heuristics with quantitative guarantees and a generalizable, shape-based diagnostic. HighlightsO_LIA conservative upper 95 % confidence bound (on survival = 1.000) was observed for the Coffee UV-C ([~]10 min) cohort, revealing strong isolate-specific heterogeneity rather than a universal kill guarantee C_LIO_LIIsolate-specific heterogeneity (e.g., localized P24-88 survival) was quantified rather than averaged away. C_LIO_LIA size-free morphological fingerprint predicted host-origin (Accuracy {approx} 0.93) and survival (R{superscript 2} {approx} 0.74). C_LIO_LIThe shape-only signal generalized across diverse stressors, including UV-C, UV-B, and sonication. C_LIO_LIA probabilistic, device-agnostic control framework replaces traditional time-based heuristics. C_LI

microbiology↗

bioRxiv2025

Decoding pathogen ecological memory from chemical-stress phenotypes

Can standardized chemical stress reveal a reproducible, taxonomy-agnostic stress-response fingerprint that is predictive of sample-source labels (crop-of-isolation) in fungal isolates? Six coffee{square}associated Colletotrichum isolates were profiled using four phenolic{square}branched compounds and compared them with a previously characterized cacao panel. Quantitative morphology, hyperspectral imaging (HSI), and supervised machine learning (ML) yielded panel-specific fingerprints under uniform, isotropic in vitro conditions. Circularity, a measure of edge symmetry, was the most informative morphological feature, and ML classified the crop-of-isolation label (coffee vs cacao, in this panel) with 86.7% accuracy in within-panel cross-validation. HSI detected dose-dependent spectral shifts in a targeted subset of isolates and compounds, including changes near 1930 nm in the short-wave infrared, a moisture-sensitive region that warrants robustness checks (e.g., band masking or preprocessing sensitivity) prior to biochemical attribution. Multi{square}locus phylogeny showed the coffee isolates are polyphyletic, so the predictive signal should be interpreted conservatively as a taxonomy-agnostic phenotype fingerprint associated with crop background in this mixed-lineage panel, acknowledging that crop labels are partially confounded with phylogenetic structure. We propose a "chemical priors" framework as a working hypothesis, in which long-term environmental exposure may imprint stress-response pathways that become legible under simple, standardized probes. This integrative workflow supports scalable screening of eco-friendly antifungals and sensor-driven decision support for high-throughput phenotype-based screening workflows. HighlightsO_LITaxonomy-agnostic workflow integrates hyperspectral imaging and morphology. C_LIO_LIMachine learning predicts crop-source labels with 86.7% accuracy in mixed lineages. C_LIO_LISystem exhibits robustness, maintaining >86% accuracy even after feature ablation. C_LIO_LINon-linear ML captures structure missed by linear stats (1.7% variance). C_LIO_LIEnables rapid, sensor-driven antifungal screening without prior DNA sequencing. C_LI

microbiology↗

bioRxiv2024

A Witches' Broom Phytoplasma effector induces stunting by stabilizing a bHLH transcription factor in plants

O_LIPhytoplasmas are specialized phloem-limited bacteria that cause diseases on various crops resulting in significant agricultural losses. This research focuses on the jujube Witches Broom (JWB) phytoplasma and investigates the host-manipulating activity of the effector SJP39. C_LIO_LIWe found that SJP39 directly interacts with the plant transcription factor bHLH87 in the nuclei. SJP39 stabilizes the bHLH87 homologs in A. thaliana and jujube, leading to growth defects in the plants. C_LIO_LITranscriptomic analysis indicates that SJP39 affects the gibberellin (GA) pathway in jujube. We further demonstrate that ZjbHLH87 regulates GA signalling as a negative regulator and SJP39 enhances this regulation. C_LIO_LIThe research offers important insights into the pathogenesis of JWB disease and identified SJP39 as a virulence factor that can contribute to the growth defects caused by JWB phytoplasma infection. These findings open new opportunities to manage JWB and other phytoplasma diseases. C_LI

plant biology↗

bioRxiv2022

In planta transcriptomics reveals conflicts between pattern-triggered immunity and the AlgU sigma factor regulon

In previous work, we determined the transcriptomic impacts of flg22 pre-induced Pattern Triggered Immunity (PTI) in Arabidopsis thaliana on the pathogen Pseudomonas syringae pv. tomato DC3000 (Pto). During PTI exposure we observed expression patterns in Pto reminiscent of those previously observed in a Pto algU mutant. AlgU is a conserved extracytoplasmic function sigma factor which has been observed to regulate over 950 genes in Pto in vitro. We sought to identify the AlgU regulon in planta.and which PTI-regulated genes overlapped with AlgU-regulated genes. In this study, we analyzed transcriptomic data from RNA-sequencing to identify the AlgU in planta regulon and its relationship with PTI. Our results showed that approximately 224 genes are induced by AlgU, while another 154 genes are downregulated by AlgU in Arabidopsis during early infection. Both stress response and virulence-associated genes were induced by AlgU, while the flagellar motility genes are downregulated by AlgU. Under the pre-induced PTI condition, more than half of these AlgU-regulated genes have lost induction/suppression in contrast to naive plants, and almost all function groups regulated by AlgU were affected by PTI.

microbiology↗

bioRxiv2021

Transcriptome profiling of Candidatus Liberibacter asiaticus in citrus and psyllids

Candidatus Liberibacter asiaticus (Las) is an emergent bacterial pathogen that is associated with the devastating citrus Huanglongbing (HLB). Vectored by the Asian citrus psyllid, Las colonizes the phloem tissue of citrus, causing severe damage to infected trees. So far, cultivating pure Las culture in axenic media has not been successful and dual-transcriptome analyses aiming to profile gene expression in both Las and its host(s) have a low coverage of the Las genome due to the low abundance of bacterial RNA in total RNA extracts from infected tissues. Therefore, the lack of a Las transcriptome remains as a significant knowledge gap. Here, we used a bacterial cell enrichment procedure and confidently determined the expression profiles of approximately 84% of the Las genes. Genes that exhibited the highest expression levels in citrus include ion transporters, ferritin, outer membrane porins, and genes involved in phage-related functions, pilus formation, cell wall modification, and stress responses. One hundred and six genes were found to be differentially expressed in citrus vs psyllids. Genes related to transcription/translation and resilience to host defense response were upregulated in citrus; whereas genes involved in energy generation and the flagella system were expressed to higher levels in psyllids. We also determined the relative expression levels of potential Sec-dependent effectors, which are considered as key virulence factors of Las. This work advances our understanding of HLB biology and offers novel insight into the interactions of Las with its plant host and insect vector.

microbiology↗

bioRxiv2017

Validation of RT-qPCR approaches to monitor Pseudomonas syringae gene expression during infection and exposure to pattern-triggered immunity

Pseudomonas syringae pv. tomato DC3000 (DC3000) is an important model plant pathogen, with a fully annotated genome and multiple compatible plant hosts. Very few studies have examined the regulation of DC3000 gene expression in vivo. We developed a RT-qPCR assay to monitor transcriptional changes in DC3000 inoculated into Arabidopsis thaliana leaves during disease and exposure to pattern-triggered immunity (PTI). In our approach, bacterial RNA concentrations in total tissue RNA are standardized using P.syringae-specific16S ribosomal RNA primers. We validated multiple stable reference genes for normalization in calculating the relative expression of genes of interest. We used empirically derived rates of amplification efficiency to calculate relative expression of key marker genes for virulence-associated regulation. We demonstrated that exposure to PTI alters DC3000 expression of Type III secretion system, coronatine synthesis genes and flagellar marker genes.

microbiology↗