Biology subjects

Senatori, B.

Publications and source records attributed to Senatori, B..

6 recordsLinked to original sources

bioRxiv2026

3D printing and deep learning enable holistic and dynamic analyses of tens of thousands of parasites infecting hundreds of genotypes

Host-parasite interactions are dynamic systems, where parasites usually outnumber hosts by one or more orders of magnitude. However, our understanding is often limited by the assessment of parts of the host, at arbitrary time points, and/or aggregate parasite responses. Here we combined custom-built 3D-printed hardware and deep-learning-based algorithms to enable holistic (i.e. all infecting individuals on the whole plant), spatio-temporal, and parasite-centric analyses of plant-parasitism by nematodes from timelapse videos of infection over months. In so doing, we tracked the dynamic growth and development of all individual parasites, at the organismal level, for thousands of hosts across hundreds of genotypes of Arabidopsis thaliana. Categorising traits into the static (i.e. in an acquired image at a given time point) and dynamic (i.e. phenotypic changes over time), we revealed a greater extent of host-genetic control of parasite traits, and new physiological limits of the species under these conditions. Using this capability, we identify Quantitative Trait Loci (QTL) in the host plant associated with 18 phenotypic traits in the parasite as a resource for the community. Finally, we leverage the large and diverse dataset to understand fundamental features of the parasite, independent of host genotype, revealing aspects of the life cycle which are pseudo-deterministic as well as local, deleterious interactions between co-infecting parasites. Given that plant-parasitic nematodes cause an estimated $100 billion in agricultural damages per year, these insights are contextualised in a global challenge driven by plant-parasitic nematodes.

pathology↗

bioRxiv2025

The host range paradox of Meloidogyne incognita: a physiological and transcriptomic analysis of nine susceptible interactions across six plant orders

The plant-parasitic nematode Meloidogyne incognita is the pathogen with the broadest host range among all known biotrophic interactions. This species is also the single most damaging of a group of agriculturally important plant-parasites, which together are estimated to contribute to losses in excess of $170 billion/year to world agriculture. Understanding how M. incognita is able to infect representatives from most orders of flowering plants, covering more than 3000 species, addresses a fundamentally important question of how pathogens adapt to their host-environment, and may inform control of a pathogen which threatens global food security. Here, we analyse the plant-nematode infection phenotype, and cross-kingdom transcriptome, of nine interactions across six orders of flowering plants at 25 days post infection. At this stage, majority of nematodes found within roots were immature and mature females (49.2% - 91.8%). Our data show that the phylogenetic distribution of hosts does not explain the phenotypic distribution of parasitism. Interestingly, though, M. incognita do have distinct transcriptional responses to different groups of hosts, but in a pattern which is independent of host phylogenetic. Three distinct nematode "transcriptional programmes" - Group 1, 2, and 3 - are evident, and we find that effectors are neither uniformly deployed across hosts, nor across groups of hosts. Importantly, we show that this differential deployment of effectors can have profound consequences for host specificity. Finally, we show that there is essentially no widespread core gall transcriptome at 25 days post infection, prompting the proposal of a model best described as "all roads lead to Rome".

plant biology↗

bioRxiv2024

The SUbventral-Gland master Regulator (SUGR) of nematode virulence

All pathogens must tailor their gene expression to their environment. Therefore, targeting host:parasite biology that regulates these changes in gene expression could open up routes to pathogen control. Here, we show that in the plant-parasitic nematode Heterodera schachtii, host signals (termed effectostimulins) within plant roots activate the master regulator sugr1. SUGR1, then, directly binds effector promoters, and orchestrates their production. Effector production, in turn, facilitates host entry, releasing more effectostimulins. These data show that gene expression during the very earliest stages of parasitism is defined by a feed forward loop for host entry. Importantly, we demonstrate that blocking SUGR1 blocks parasitism, underlining the SUGR1 signalling cascade as a valuable target for crop protection. Given that nematodes also parasitise humans and other animals, the potential impact is broad: disrupting effector production could, in principle, be applied to any pathogen that secrets effectors. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=146 SRC="FIGDIR/small/576598v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@cebedaorg.highwire.dtl.DTLVardef@153fe87org.highwire.dtl.DTLVardef@16b6957org.highwire.dtl.DTLVardef@d0e920_HPS_FORMAT_FIGEXP M_FIG C_FIG

pathology↗

bioRxiv2024

The origin, deployment, and evolution of a plant-parasitic nematode effectorome

Plant-parasitic nematodes constrain global food security. During parasitism, they secrete effectors into the host plant from two types of pharyngeal gland cells. These effectors elicit profound changes in host biology to suppress immunity and establish a unique feeding organ from which the nematode draws nutrition. Despite the importance of effectors in nematode parasitism, there has been no comprehensive identification and characterisation of the effector repertoire of any plant-parasitic nematode. To address this, we advance techniques for gland cell isolation and transcriptional analysis to define a stringent annotation of putative effectors for the cyst nematode Heterodera schachtii at three key life-stages. We define 659 effector gene loci: 293 "known" high-confidence homologs of plant-parasitic nematode effectors, and 366 "novel" effectors with high gland cell expression. In doing so we define a comprehensive "effectorome" of a plant-parasitic nematode. Using this effector definition, we provide the first systems-level understanding of the origin, deployment and evolution of a plant-parasitic nematode effectorome. The robust identification of the comprehensive effector repertoire of a plant-parasitic nematode will underpin our understanding of nematode pathology, and hence, inform strategies for crop protection.

plant biology↗

bioRxiv2023

A gene with a thousand alleles: the HYPer-variable effectors of plant-parasitic nematodes

Pathogens are engaged in a fierce evolutionary arms race with their host. The genes at the forefront of the engagement between kingdoms, including effectors and immune receptors, are part of diverse and highly mutable gene families. Even in this context, we discovered unprecedented variation in the HYPer-variable (HYP) effectors of plant-parasitic nematodes. We discovered single effector gene loci that can harbour potentially thousands of allelic variants. These alleles vary in the number, but principally in the organisation, of motifs within a central Hyper Variable Domain (HVD). Using targeted long-read sequencing, we dramatically expand the HYP repertoire of two plant-parasitic nematodes, Globodera pallida and G. rostochiensis, such that we can define distinct sets of species-specific "rules" underlying the apparently flawless genetic rearrangements. Finally, by analysing the HYP complement of 68 individual nematodes we made the unexpected finding that despite the huge number of alleles, most individuals are homozygous. Taken together, these data point to a novel mechanism of programmed genetic variation, termed HVD-editing, where alterations are locus-specific, strictly governed by rules, and can theoretically produce thousands of variants without errors.

genetics↗

bioRxiv2022

A low-cost and open-source solution to automate imaging and analysis of cyst nematode infection assays for Arabidopsis thaliana

BackgroundCyst nematodes are one of the major groups of plant-parasitic nematode, responsible for considerable crop losses worldwide. Improving genetic resources, and therefore resistant cultivars, is an ongoing focus of many pest management strategies. One of the major bottlenecks in identifying the plant genes that impact the infection, and thus the yield, is phenotyping. The current available screening method is slow, has unidimensional quantification of infection limiting the range of scorable parameters, and does not account for phenotypic variation of the host. The ever-evolving field of computer vision may be the solution for both the above-mentioned issues. To utilise these tools, a specialised imaging platform is required to take consistent images of nematode infection in quick succession. ResultsHere, we describe an open-source, easy to adopt, imaging hardware and trait analysis software method based on a pre-existing nematode infection screening method in axenic culture. A cost-effective, easy-to-build and -use, 3D-printed imaging device was developed to acquire images of the root system of Arabidopsis thaliana infected with the cyst nematode Heterodera schachtii, replacing costly microscopy equipment. Coupling the output of this device to simple analysis scripts allowed the measurement of some key traits such as nematode number and size from collected images, in a semi-automated manner. Additionally, we used this combined solution to quantify an additional trait, root area before infection, and showed both the confounding relationship of this trait on nematode infection and a method to account for it. ConclusionTaken together, this manuscript provides a low-cost and open-source method for nematode phenotyping that includes the biologically relevant nematode size as a scorable parameter, and a method to account for phenotypic variation of the host. Together these tools highlight great potential in aiding our understanding of nematode parasitism.

plant biology↗