Where are we going with genomics in plant pathogenic bacteria?

Xanthomonas as a Model System for Studying Pathogen Emergence and Evolution

In this review, we highlight studies in which whole-genome sequencing, comparative genomics, and population genomics have provided unprecedented insights into past and ongoing pathogen evolution. These include new understandings of the adaptive evolution of secretion systems and their effectors. We focus on Xanthomonas pathosystems that have seen intensive study and improved our understanding of pathogen emergence and evolution, particularly in the context of host specialization: citrus canker, bacterial blight of rice, and bacterial spot of tomato and pepper. Across pathosystems, pathogens appear to follow a pattern of bursts of evolution and diversification that impact host adaptation. There remains a need for studies on the mechanisms of host range evolution and genetic exchange among closely related but differentially host-specialized species and to start moving beyond the study of specific strain and host cultivar pairwise interactions to thinking about these pathosystems in a community context.

Towards Small Scale: Overview and Applications of Microfluidics in Biotechnology

Thanks to recent and continuing technological innovations, modern microfluidic systems are increasingly offering researchers working across all fields of biotechnology exciting new possibilities (especially with respect to facilitating high throughput analysis, portability, and parallelization). The advantages offered by microfluidic devices-namely, the substantially lowered chemical and sample consumption they require, the increased energy and mass transfer they offer, and their comparatively small size-can potentially be leveraged in every sub-field of biotechnology. However, to date, most of the reported devices have been deployed in furtherance of healthcare, pharmaceutical, and/or industrial applications. In this review, we consider examples of microfluidic and miniaturized systems across biotechnology sub-fields. In this context, we point out the advantages of microfluidics for various applications and highlight the common features of devices and the potential for transferability to other application areas. This will provide incentives for increased collaboration between researchers from different disciplines in the field of biotechnology.

Whole-Genome-Sequence-Based Classification of Xanthomonas euvesicatoria pv. eucalypti and Computational Analysis of the Type III Secretion System

Xanthomonas spp. infect a wide range of annual and perennial plants. Bacterial blight in young seedlings of Eucalyptus spp. in Indonesia was originally identified as X. perforans. However, these strains failed to elicit a hypersensitive response (HR) on either tomatoes or peppers. Two of the strains, EPK43 and BCC 972, when infiltrated into tomato and pepper leaves, failed to grow to significant levels in comparison with well-characterized X. euvesicatoria pv. perforans (Xp) strains. Furthermore, spray inoculation of 'Bonny Best' tomato plants with a bacterial suspension of the Eucalyptus strains resulted in no obvious symptoms. We sequenced the whole genomes of eight strains isolated from two Eucalyptus species between 2007 and 2015. The strains had average nucleotide identities (ANIs) of at least 97.8 with Xp and X. euvesicatoria pv. euvesicatoria (Xeu) strains, both of which are causal agents of bacterial spot of tomatoes and peppers. A comparison of the Eucalyptus strains revealed that the ANI values were >99.99% with each other. Core genome phylogeny clustered all Eucalyptus strains with X. euvesicatoria pv. rosa. They formed separate clades, which included X. euvesicatoria pv. alangii, X. euvesicatoria pv. citrumelonis, and X. euvesicatoria pv. alfalfae. Based on ANI, phylogenetic relationships, and pathogenicity, we designated these Eucalyptus strains as X. euvesicatoria pv. eucalypti (Xee). Comparative analysis of sequenced strains provided unique profiles of type III secretion effectors. Core effector XopD, present in all pathogenic Xp and Xeu strains, was absent in the Xee strains. Comparison of the hrp clusters of Xee, Xp, and Xeu genomes revealed that HrpE in Xee strains was very different from that in Xp and Xeu. To determine if it was functional, we deleted the gene and complemented with the Xee hrpE, confirming it was essential for secretion of type III effectors. HrpE has a hypervariable N-terminus in Xanthomonas spp., in which the N-terminus of Xee strains differs significantly from those of Xeu and Xp strains.

Deep learning for plant bioinformatics: an explainable gradient-based approach for disease detection

Emerging in the realm of bioinformatics, plant bioinformatics integrates computational and statistical methods to study plant genomes, transcriptomes, and proteomes. With the introduction of high-throughput sequencing technologies and other omics data, the demand for automated methods to analyze and interpret these data has increased. We propose a novel explainable gradient-based approach EG-CNN model for both omics data and hyperspectral images to predict the type of attack on plants in this study. We gathered gene expression, metabolite, and hyperspectral image data from plants afflicted with four prevalent diseases: powdery mildew, rust, leaf spot, and blight. Our proposed EG-CNN model employs a combination of these omics data to learn crucial plant disease detection characteristics. We trained our model with multiple hyperparameters, such as the learning rate, number of hidden layers, and dropout rate, and attained a test set accuracy of 95.5%. We also conducted a sensitivity analysis to determine the model's resistance to hyperparameter variations. Our analysis revealed that our model exhibited a notable degree of resilience in the face of these variations, resulting in only marginal changes in performance. Furthermore, we conducted a comparative examination of the time efficiency of our EG-CNN model in relation to baseline models, including SVM, Random Forest, and Logistic Regression. Although our model necessitates additional time for training and validation due to its intricate architecture, it demonstrates a faster testing time per sample, offering potential advantages in real-world scenarios where speed is paramount. To gain insights into the internal representations of our EG-CNN model, we employed saliency maps for a qualitative analysis. This visualization approach allowed us to ascertain that our model effectively captures crucial aspects of plant disease, encompassing alterations in gene expression, metabolite levels, and spectral discrepancies within plant tissues. Leveraging omics data and hyperspectral images, this study underscores the potential of deep learning methods in the realm of plant disease detection. The proposed EG-CNN model exhibited impressive accuracy and displayed a remarkable degree of insensitivity to hyperparameter variations, which holds promise for future plant bioinformatics applications.

Decoding Metabolic Reprogramming in Plants under Pathogen Attacks, a Comprehensive Review of Emerging Metabolomics Technologies to Maximize Their Applications

In their environment, plants interact with a multitude of living organisms and have to cope with a large variety of aggressions of biotic or abiotic origin. What has been known for several decades is that the extraordinary variety of chemical compounds the plants are capable of synthesizing may be estimated in the range of hundreds of thousands, but only a fraction has been fully characterized to be implicated in defense responses. Despite the vast importance of these metabolites for plants and also for human health, our knowledge about their biosynthetic pathways and functions is still fragmentary. Recent progress has been made particularly for the phenylpropanoids and oxylipids metabolism, which is more emphasized in this review. With an increasing interest in monitoring plant metabolic reprogramming, the development of advanced analysis methods should now follow. This review capitalizes on the advanced technologies used in metabolome mapping in planta, including different metabolomics approaches, imaging, flux analysis, and interpretation using bioinformatics tools. Advantages and limitations with regards to the application of each technique towards monitoring which metabolite class or type are highlighted, with special emphasis on the necessary future developments to better mirror such intricate metabolic interactions in planta.

Pulmonary arterial hypertension associated with congenital heart disease: An omics study

Pulmonary arterial hypertension associated with congenital heart disease (PAH-CHD) is a severely progressive condition with uncertain physiological course. Hence, it has become increasingly relevant to clarify the specific mechanisms of molecular modification, which is crucial to identify more treatment strategies. With the rapid development of high-throughput sequencing, omics technology gives access to massive experimental data and advanced techniques for systems biology, permitting comprehensive assessment of disease occurrence and progression. In recent years, significant progress has been made in the study of PAH-CHD and omics. To provide a comprehensive description and promote further in-depth investigation of PAH-CHD, this review attempts to summarize the latest developments in genomics, transcriptomics, epigenomics, proteomics, metabolomics, and multi-omics integration.

Understanding the Proteomes of Plant Development and Stress Responses in Brassica Crops

Brassica crops have great economic value due to their rich nutritional content and are therefore grown worldwide as oilseeds, vegetables, and condiments. Deciphering the molecular mechanisms associated with the advantageous phenotype is the major objective of various Brassica improvement programs. As large technological advancements have been achieved in the past decade, the methods to understand molecular mechanisms underlying the traits of interest have also taken a sharp upturn in plant breeding practices. Proteomics has emerged as one of the preferred choices nowadays along with genomics and other molecular approaches, as proteins are the ultimate effector molecules responsible for phenotypic changes in living systems, and allow plants to resist variable environmental stresses. In the last two decades, rapid progress has been made in the field of proteomics research in Brassica crops, but a comprehensive review that collates the different studies is lacking. This review provides an inclusive summary of different proteomic studies undertaken in Brassica crops for cytoplasmic male sterility, oil content, and proteomics of floral organs and seeds, under different biotic and abiotic stresses including post-translational modifications of proteins. This comprehensive review will help in understanding the role of different proteins in controlling plant phenotypes, and provides information for initiating future studies on Brassica breeding and improvement programs.

Current understanding of plant-microbe interaction through the lenses of multi-omics approaches and their benefits in sustainable agriculture

The success of sustainable agricultural practices has now become heavily dependent on the interactions between crop plants and their associated microbiome. Continuous advancement in high throughput sequencing platforms, omics-based approaches, and gene editing technologies has remarkably accelerated this area of research. It has enabled us to characterize the interactions of plants with associated microbial communities more comprehensively and accurately. Furthermore, the genomic and post-genomic era has significantly refined our perspective toward the complex mechanisms involved in those interactions, opening new avenues for efficiently deploying the knowledge in developing sustainable agricultural practices. This review focuses on our fundamental understanding of plant-microbe interactions and the contribution of existing multi-omics approaches, including those under active development and their tremendous success in unraveling different aspects of the complex network between plant hosts and microbes. In addition, we have also discussed the importance of sustainable and eco-friendly agriculture and the associated outstanding challenges ahead.

Genomics and Informatics, Conjoined Tools Vital for Understanding and Protecting Plant Health

Genomics' impact on crop production continuously expands. The number of sequenced plant and microbial species and strains representing diverse populations of individual species rapidly increases thanks to the advent of next-generation sequencing technologies. Their genomic blueprints revealed candidate genes involved in various functions and processes crucial for crop health and helped in understanding how the sequenced organisms have evolved at the genome level. Functional genomics quickly translates these blueprints into a detailed mechanistic understanding of how such functions and processes work and are regulated; this understanding guides and empowers efforts to protect crops from diverse biotic and abiotic threats. Metagenome analyses help identify candidate microbes crucial for crop health and uncover how microbial communities associated with crop production respond to environmental conditions and cultural practices, presenting opportunities to enhance crop health by judiciously configuring microbial communities. Efficient conversion of disparate types of massive genomics data into actionable knowledge requires a robust informatics infrastructure supporting data preservation, analysis, and sharing. This review starts with an overview of how genomics came about and has quickly transformed life science. We illuminate how genomics and informatics can be applied to investigate various crop health-related problems using selected studies. We end the review by noting why community empowerment via crowdsourcing is crucial to harnessing genomics to protect global food and nutrition security without continuously expanding the environmental footprint of crop production.

Virus-Mediated Protein Overexpression (VOX) in Monocots to Identify and Functionally Characterize Fungal Effectors

One of the important armories that pathogens utilize to successfully colonize the plants is small secreted effector proteins, which could perform a variety of functions from suppression of plant innate immunity to manipulation of plant physiology in favor of the disease. Plants, on the other hand, evolved disease resistance genes that recognize some of the effectors or avirulence (Avr) proteins. Both, identification of the Avr proteins and understanding of the mechanisms of action of other effectors, are important areas of research in the molecular plant-pathogen interactions field as this knowledge is critical for the development of new effective pathogen control measures. To enable functional analysis of the effectors, it is desirable to be able to overexpress them readily in the host plants. Here we describe detailed experimental protocols for transient effector overexpression in wheat and other monocots using binary Barley stripe mosaic virus (BSMV)- and Foxtail mosaic virus (FoMV)-derived vectors. This functional genomics tool, better known as VOX (Virus-mediated protein OvereXpression), is rapid and relatively simple and inexpensive.

Bacterial effectors mimicking ubiquitin-proteasome pathway tweak plant immunity

Plant pathogenic Gram-negative bacteria evade the host plant immune system by secreting Type III (T3E) and Type IV effector (T4E) proteins into the plant cytoplasm. Mostly T3Es are secreted into the plant cells to establish pathogenicity by affecting the vital plant process viz. metabolic pathways, signal transduction and hormonal regulation. Ubiquitin-26S proteasome system (UPS) exists as one of the important pathways in plants to control plant immunity and various cellular processes by employing several enzymes and enzyme components. Pathogenic and non-pathogenic bacteria are found to secrete effectors into plants with structural and/or functional similarity to UPS pathway components like ubiquitin E3 ligases, F-box domains, cysteine proteases, inhibitor of host UPS or its components, etc. The bacterial effectors mimic UPS components and target plant resistance proteins for degradation by proteasomes, thereby taking control over the host cellular activities as a strategy to exert virulence. Thus, the bacterial effectors circumvent plant cellular pathways leading to infection and disease development. This review highlights known bacterial T3E and T4E proteins that function and interfere with the ubiquitination pathway to regulate the immune system of plants.

Predicting microbial growth dynamics in response to nutrient availability

Developing mathematical models to accurately predict microbial growth dynamics remains a key challenge in ecology, evolution, biotechnology, and public health. To reproduce and grow, microbes need to take up essential nutrients from the environment, and mathematical models classically assume that the nutrient uptake rate is a saturating function of the nutrient concentration. In nature, microbes experience different levels of nutrient availability at all environmental scales, yet parameters shaping the nutrient uptake function are commonly estimated for a single initial nutrient concentration. This hampers the models from accurately capturing microbial dynamics when the environmental conditions change. To address this problem, we conduct growth experiments for a range of micro-organisms, including human fungal pathogens, baker's yeast, and common coliform bacteria, and uncover the following patterns. We observed that the maximal nutrient uptake rate and biomass yield were both decreasing functions of initial nutrient concentration. While a functional form for the relationship between biomass yield and initial nutrient concentration has been previously derived from first metabolic principles, here we also derive the form of the relationship between maximal nutrient uptake rate and initial nutrient concentration. Incorporating these two functions into a model of microbial growth allows for variable growth parameters and enables us to substantially improve predictions for microbial dynamics in a range of initial nutrient concentrations, compared to keeping growth parameters fixed.

Pectobacterium brasiliense: Genomics, Host Range and Disease Management

Pectobacterium brasiliense (Pbr) is considered as one of the most virulent species among the Pectobacteriaceae. This species has a broad host range within horticulture crops and is well distributed elsewhere. It has been found to be pathogenic not only in the field causing blackleg and soft rot of potato, but it is also transmitted via storage causing soft rot of other vegetables. Genomic analysis and other cost-effective molecular detection methods such as a quantitative polymerase chain reaction (qPCR) are essential to investigate the ecology and pathogenesis of the Pbr. The lack of fast, field deployable point-of-care testing (POCT) methods, specific control strategies and current limited genomic knowledge make management of this species difficult. Thus far, no comprehensive review exists about Pbr, however there is an intense need to research the biology, detection, pathogenicity and management of Pbr, not only because of its fast distribution across Europe and other countries but also due to its increased survival to various climatic conditions. This review outlines the information available in peer-reviewed literature regarding host range, detection methods, genomics, geographical distribution, nomenclature and taxonomical evolution along with some of the possible management and control strategies. In summary, the conclusions and a further directions highlight the management of this species.

Genome-Wide Analyses Revealed Remarkable Heterogeneity in Pathogenicity Determinants, Antimicrobial Compounds, and CRISPR-Cas Systems of Complex Phytopathogenic Genus Pectobacterium

The Pectobacterium genus comprises pectolytic enterobacteria defined as the causal agents of soft rot, blackleg, and aerial stem rot diseases of potato and economically important crops. In this study, we undertook extensive genome-wide comparative analyses of twelve species that conform the Pectobacterium genus. Bioinformatics approaches outlined a low nucleotide identity of P. parmentieri and P. wasabiae with other species, while P. carotovorum subsp. odoriferum was shown to harbor numerous pseudogenes, which suggests low coding capacity and genomic degradation. The genome atlases allowed for distinguishing distinct DNA structures and highlighted suspicious high transcription zones. The analyses unveiled a noteworthy heterogeneity in the pathogenicity determinants. Specifically, phytotoxins, polysaccharides, iron uptake systems, and the type secretion systems III-V were observed in just some species. Likewise, a comparison of gene clusters encoding antimicrobial compounds put in evidence for high conservation of carotovoricin, whereas a few species possessed the phenazine, carbapenem, and carocins. Moreover, three clustered regularly interspaced short palindromic repeats-Cas (CRISPR-Cas) systems: I-E, I-F, and III-A were identified. Surrounding some CRISPR-Cas regions, different toxin and antitoxin systems were found, which suggests bacterial suicide in the case of an immune system failure. Multiple whole-genome alignments shed light on to the presence of a novel cellobiose phosphotransferase system (PTS) exclusive to P. parmenteri, and an unreported T5SS conserved in almost all species. Several regions that were associated with virulence, microbe antagonism, and adaptive immune systems were predicted within genomic islands, which underscored the essential role that horizontal gene transfer has imparted in the dynamic evolution and speciation of Pectobacterium species. Overall, the results decipher the different strategies that each species has developed to infect their hosts, outcompete for food resources, and defend against bacteriophages. Our investigation provides novel genetic insights that will assist in understanding the pathogenic lifestyle of Pectobacterium, a genus that jeopardizes the agriculture sustainability of important crops worldwide.