Facilitating the transition from physiology to hospital wards through an interdisciplinary case study of septic shock

BACKGROUND: In order to develop clinical reasoning, medical students must be able to integrate knowledge across traditional subject boundaries and multiple disciplines. At least two dimensions of integration have been identified: horizontal integration, bringing together different disciplines in considering a topic; and vertical integration, bridging basic science and clinical practice. Much attention has been focused on curriculum overhauls, but our approach is to facilitate horizontal and vertical integration on a smaller scale through an interdisciplinary case study discussion and then to assess its utility. METHODS: An interdisciplinary case study discussion about a critically ill patient was implemented at the end of an organ system-based, basic sciences module at New York University School of Medicine. Three clinical specialists—a cardiologist, a pulmonologist, and a nephrologist—jointly led a discussion about a complex patient in the intensive care unit with multiple medical problems secondary to septic shock. The discussion emphasized the physiologic underpinnings behind the patient’s presentation and the physiologic considerations across the various systems in determining proper treatment. The discussion also highlighted the interdependence between the cardiovascular, respiratory, and renal systems, which were initially presented in separate units. After the session students were given a brief, anonymous three-question free-response questionnaire in which they were asked to evaluate and freely comment on the exercise. RESULTS: Students not only took away physiological principles but also gained an appreciation for various thematic lessons for bringing basic science to the bedside, especially horizontal and vertical integration. The response of the participants was overwhelmingly positive with many indicating that the exercise integrated the material across organ systems, and strengthened their appreciation of the role of physiology in understanding disease presentations and guiding appropriate therapy. CONCLUSIONS: Horizontal and vertical integration can be presented effectively through a single-session case study, with complex patient cases involving multiple organ systems providing students opportunities to integrate their knowledge across organ systems while emphasizing the importance of physiology in clinical reasoning. Furthermore, having several clinicians from different specialties discuss the case together can reinforce the matter of integration across multiple organ systems and disciplines in students’ minds

Signals that stop the rot : regulation of secondary metabolite defences in cereals

Plants accumulate a vast arsenal of chemically diverse secondary metabolites for defence against pathogens. This review will focus on the signal transduction and regulation of defence secondary metabolite production in five food security cereal crops: maize, rice, wheat, sorghum and oats. Recent research advances in this field have revealed novel processes and chemistry in these monocots that make this a rich field for future research.The National Research Foundation (NRF) and the Genomics Research Institute at the University of Pretoria (UP), South Africa.http://www.elsevier.com/locate/pmpp2017-04-30hb2016Forestry and Agricultural Biotechnology Institute (FABI)Plant Scienc

Time-course RNAseq reveals exserohilum turcicum effectors and pathogenicity determinants

Exserohilum turcicum (sexual stage Setosphaeria turcica) is the hemibiotrophic causal agent of northern leaf blight ofmaize and sorghum. This study aimed to identify the genes involved in host colonization during the biotrophic and necrotrophic phases of infection. It also aimed to identify race-specific differences in gene expression. RNAseq of maize seedlings inoculated with a race 13N or 23N E. turcicum isolate was conducted before inoculation and at 2, 5, 7, and 13 days post-inoculation (dpi). Biological replicates were pooled per time point for each race and sequenced. A bioinformatics pipeline was used to identify candidate effectors, and expression was validated for selected candidates. Fungal biomass was positively correlated with the percentages of E. turcicum reads mapped, which were low at early time points (2–7 dpi) with a significant increase at 13 dpi, indicating a lifestyle switch from biotrophy to necrotrophy between 7 and 13 dpi. AVRHt1 is the putative E. turcicum effector recognized by the maize resistance gene Ht1. Consistent with this, AVRHt1 was expressed in planta by race 23N, but transcripts were absent in race 13N. In addition, specific transposable elements were expressed in 23N only. Genes encoding the virulence-associated peptidases leupeptin-inhibiting protein 1 and fungalysin were expressed in planta. Transcriptional profiles of genes involved in secondary metabolite synthesis or cell wall degradation revealed the importance of these genes during late stages of infection (13 dpi). A total of 346 expressed candidate effectors were identified, including Ecp6 and proteins similar to the secreted in xylem (SIX) effectors common to formae speciales of Fusarium oxysporum, SIX13 and SIX5. Expression profiling of Ecp6 and SIX13-like indicated a peak in expression at 5 and 7 dpi compared to 2 and 13 dpi. Sequencing of SIX13-like from diverse isolates of E. turcicum revealed host-specific polymorphisms that were mostly non-synonymous, resulting in two groups of SIX13-like proteins that corresponded to the maize or sorghum origin of each isolate. This study suggests putative mechanisms whereby E. turcicum causes disease. Identification of the candidate effector SIX13-like is consistent with the infection mode of E. turcicum through the xylem of susceptible hosts.The National Research Foundation of South Africahttp://www.frontiersin.org/Microbiologyam2020Forestry and Agricultural Biotechnology Institute (FABI)Plant Production and Soil Scienc

Putative pathogenicity genes of Phytophthora cinnamomi identified via RNA-Seq analysis of pre-infection structures

Phytophthora cinnamomi is an economically important oomycete that infects more than 3,000 plant species. We aimed to identify the repertoire of genes expressed during preinfection stages by analysing an RNA-Seq library of cysts and germinating cysts of a P. cinnamomi isolate, originating from Persea americana. Over 70,000 transcripts were identified from 225,049 contigs, assembled from 13 million Illumina paired-end reads. Contaminant sequences were eliminated, resulting in 37,534 transcripts used in further analysis. A total of 1,394 transcripts had a putative role in pathogenesis. Genes aiding in detoxification and metabolite transport (cytochrome P450 and ABC transporters) and protection against oxidative stress were most abundant, followed by the genes coding cell wall degrading enzymes. The transcript set included 44 putative RXLR effector genes and genes encoding elicitin and necrosis-inducing proteins. Expression patterns of seven putative pathogenicity genes (encoding RXLR-, necrosis-inducing Phytophthora protein 1 (NPP1), elicitin, polygalacturonase, cellulose binding and elicitor lectin (CBEL), mucin, and adhesion proteins) were assessed across four in vitro developmental stages of P. cinnamomi. High expression of these genes in zoospores suggests their functional importance in the subsequent developmental stage, germination of cysts, implying a role in pre-infection. This work is the first step towards understanding the molecular basis of infection strategies employed by P. cinnamomi.Supplement 1: Online Resource 1, 2, 3, 4, 5, 9.Supplement 2: Online Resource 6 .Supplement 3: Online Resource 7.Supplement 4: Online Resource 8.The National Research Foundation (NRF) and The Hans Merensky Foundation.http://link.springer.com/journal/106582018-01-31hb2017GeneticsMicrobiology and Plant PathologyPlant Scienc

Imaging ATUM ultrathin section libraries with WaferMapper: a multi-scale approach to EM reconstruction of neural circuits

The automated tape-collecting ultramicrotome (ATUM) makes it possible to collect large numbers of ultrathin sections quickly—the equivalent of a petabyte of high resolution images each day. However, even high throughput image acquisition strategies generate images far more slowly (at present ~1 terabyte per day). We therefore developed WaferMapper, a software package that takes a multi-resolution approach to mapping and imaging select regions within a library of ultrathin sections. This automated method selects and directs imaging of corresponding regions within each section of an ultrathin section library (UTSL) that may contain many thousands of sections. Using WaferMapper, it is possible to map thousands of tissue sections at low resolution and target multiple points of interest for high resolution imaging based on anatomical landmarks. The program can also be used to expand previously imaged regions, acquire data under different imaging conditions, or re-image after additional tissue treatments

Deep learning diagnostics of gray leaf spot in maize under mixed disease field conditions

Maize yields worldwide are limited by foliar diseases that could be fungal, oomycete, bacterial, or viral in origin. Correct disease identification is critical for farmers to apply the correct control measures, such as fungicide sprays. Deep learning has the potential for automated disease classification from images of leaf symptoms. We aimed to develop a classifier to identify gray leaf spot (GLS) disease of maize in field images where mixed diseases were present (18,656 images after augmentation). In this study, we compare deep learning models trained on mixed disease field images with and without background subtraction. Performance was compared with models trained on PlantVillage images with single diseases and uniform backgrounds. First, we developed a modified VGG16 network referred to as “GLS_net” to perform binary classification of GLS, which achieved a 73.4% accuracy. Second, we used MaskRCNN to dynamically segment leaves from backgrounds in combination with GLS_net to identify GLS, resulting in a 72.6% accuracy. Models trained on PlantVillage images were 94.1% accurate at GLS classification with the PlantVillage testing set but performed poorly with the field image dataset (55.1% accuracy). In contrast, the GLS_net model was 78% accurate on the PlantVillage testing set. We conclude that deep learning models trained with realistic mixed disease field data obtain superior degrees of generalizability and external validity when compared to models trained using idealized datasets.The National Research Foundation, South Africa.https://www.mdpi.com/journal/plantsdm2022BiochemistryComputer ScienceForestry and Agricultural Biotechnology Institute (FABI)GeneticsMicrobiology and Plant PathologyPlant Production and Soil Scienc

Application of chloroplast phylogenomics to resolve species relationships within the plant genus Amaranthus

Amaranthus species are an emerging and promising nutritious traditional vegetable food source. Morphological plasticity and poorly resolved dendrograms have led to the need for well resolved species phylogenies. We hypothesized that whole chloroplast phylogenomics would result in more reliable differentiation between closely related amaranth species. The aims of the study were therefore: to construct a fully assembled, annotated chloroplast genome sequence of Amaranthus tricolor; to characterize Amaranthus accessions phylogenetically by comparing barcoding genes (matK, rbcL, ITS) with whole chloroplast sequencing; and to use whole chloroplast phylogenomics to resolve deeper phylogenetic relationships. We generated a complete A. tricolor chloroplast sequence of 150,027 bp. The three barcoding genes revealed poor inter- and intra-species resolution with low bootstrap support. Whole chloroplast phylogenomics of 59 Amaranthus accessions increased the number of parsimoniously informative sites from 92 to 481 compared to the barcoding genes, allowing improved separation of amaranth species. Our results support previous findings that two geographically independent domestication events of Amaranthus hybridus likely gave rise to several species within the Hybridus complex, namely Amaranthus dubius, Amaranthus quitensis, Amaranthus caudatus, Amaranthus cruentus and Amaranthus hypochondriacus. Poor resolution of species within the Hybridus complex supports the recent and ongoing domestication within the complex, and highlights the limitation of chloroplast data for resolving recent evolution. The weedy Amaranthus retroflexus and Amaranthus powellii was found to share a common ancestor with the Hybridus complex. Leafy amaranth, Amaranthus tricolor, Amaranthus blitum, Amaranthus viridis and Amaranthus graecizans formed a stable sister lineage to the aforementioned species across the phylogenetic trees. This study demonstrates the power of next-generation sequencing data and reference-based assemblies to resolve phylogenies, and also facilitated the identification of unknown Amaranthus accessions from a local genebank. The informative phylogeny of the Amaranthus genus will aid in selecting accessions for breeding advanced genotypes to satisfy global food demand.The Department of Science and Technology of South Africa, the National Research Foundation and the Professional Development Program of the Agricultural Research Council (ARC) in South Africa.https://link.springer.com/journal/2392019-04-01hj2018Forestry and Agricultural Biotechnology Institute (FABI)GeneticsPlant Production and Soil Scienc

Genome-wide mapping of histone H3 lysine 4 trimethylation in Eucalyptus grandis developing xylem

BACKGROUND : Histone modifications play an integral role in plant development, but have been poorly studied in woody plants. Investigating chromatin organization in wood-forming tissue and its role in regulating gene expression allows us to understand the mechanisms underlying cellular differentiation during xylogenesis (wood formation) and identify novel functional regions in plant genomes. However, woody tissue poses unique challenges for using high-throughput chromatin immunoprecipitation (ChIP) techniques for studying genome-wide histone modifications in vivo. We investigated the role of the modified histone H3K4me3 (trimethylated lysine 4 of histone H3) in gene expression during the early stages of wood formation using ChIP-seq in Eucalyptus grandis, a woody biomass model. RESULTS : Plant chromatin fixation and isolation protocols were optimized for developing xylem tissue collected from field-grown E. grandis trees. A “nano-ChIP-seq” procedure was employed for ChIP DNA amplification. Over 9 million H3K4me3 ChIP-seq and 18 million control paired-end reads were mapped to the E. grandis reference genome for peak-calling using Model-based Analysis of ChIP-Seq. The 12,177 significant H3K4me3 peaks identified covered ~1.5% of the genome and overlapped some 9,623 protein-coding genes and 38 noncoding RNAs. H3K4me3 library coverage, peaking ~600 - 700 bp downstream of the transcription start site, was highly correlated with gene expression levels measured with RNA-seq. Overall, H3K4me3-enriched genes tended to be less tissue-specific than unenriched genes and were overrepresented for general cellular metabolism and development gene ontology terms. Relative expression of H3K4me3-enriched genes in developing secondary xylem was higher than unenriched genes, however, and highly expressed secondary cell wall-related genes were enriched for H3K4me3 as validated using ChIP-qPCR. CONCLUSIONS : In this first genome-wide analysis of a modified histone in a woody tissue, we optimized a ChIP-seq procedure suitable for field-collected samples. In developing E. grandis xylem, H3K4me3 enrichment is an indicator of active transcription, consistent with its known role in sustaining pre-initiation complex formation in yeast. The H3K4me3 ChIP-seq data from this study paves the way to understanding the chromatin landscape and epigenomic architecture of xylogenesis in plants, and complements RNA-seq evidence of gene expression for the future improvement of the E. grandis genome annotation.Additional file 1: Supplementary Note S1.Additional file 2: Figure S1, Figure S2, Figure S3, Figure S4, Figure S5, Figure S6, Figure S6, Figure S7, Figure S8, Figure S9, Figure S10, Figure S11, Figure S12, Figure S13, Figure S14, Figure S15, Figure S16.Additional file 3: Table S1, Table S2, Table S3, Table S4, Table S5, Table S6, Table S7.Additional file 4: Genomic locations and fragment coverage of significant H3K4me3 peaks.Additional file 5: Genomic locations of annotated genes overlapping with significant H3K4me3 peaks.Additional file 6: Genomic locations of low-confidence gene models overlapping with significant H3K4me3 peaks.SH, EM and AM acknowledge funding from the Department of Science and Technology (DST), South Africa, the National Research Foundation of South Africa (NRF) Incentive Funding for Rated Researchers Grant (UID 81111) and NRF Bioinformatics and Functional Genomics Program (UID 71255, UID 86936), Sappi and Mondi through the Forest Molecular Genetics (FMG) Program at the University of Pretoria (UP), and the Technology and Human Resources for Industry Program (THRIP) (UID 80118). AG acknowledges funding from USDA National Institute of Food and Agriculture and the Office of Science (BER), US Department of Energy.http://www.biomedcentral.com/bmcplantbiolam201

Benefits of maize resistance breeding and chemical control against northern leaf blight in smallholder farms in South Africa

Maize underpins food security in South Africa. An annual production of more than 10 million tons is a combination of the output of large-scale commercial farms plus an estimated 250 000 ha cultivated by smallholder farmers. Maize leaves are a rich source of nutrients for fungal pathogens. Farmers must limit leaf blighting by fungi to prevent sugars captured by photosynthesis being ‘stolen’ instead of filling the grain. This study aimed to fill the knowledge gap on the prevalence and impact of fungal foliar diseases in local smallholder maize fields. A survey with 1124 plant observations from diverse maize hybrids was conducted over three seasons from 2015 to 2017 in five farming communities in KwaZulu-Natal Province (Hlanganani, Ntabamhlophe, KwaNxamalala) and Eastern Cape Province (Bizana, Tabankulu). Northern leaf blight (NLB), common rust, Phaeosphaeria leaf spot, and grey leaf spot had overall disease incidences of 75%, 77%, 68% and 56%, respectively, indicating high disease pressure in smallholder farming environments. NLB had the highest disease severity (LSD test, p<0.05). A yield trial focused on NLB in KwaZulu-Natal showed that this disease reduced yields in the three most susceptible maize hybrids by 36%, 71% and 72%, respectively. Eighteen other hybrids in this trial did not show significant yield reductions due to NLB, which illustrates the progress made by local maize breeders in disease resistance breeding. This work highlights the risk to smallholder farmers of planting disease-susceptible varieties, and makes recommendations on how to exploit the advances of hybrid maize disease resistance breeding to develop farmer-preferred varieties for smallholder production. SIGNIFICANCE : • Northern leaf blight, grey leaf spot, Phaeosphaeria leaf spot and common rust diseases were widespread in KwaZulu-Natal and Eastern Cape smallholder maize fields where fungicides were not applied. • NLB was the most severe maize leaf disease overall. • NLB caused maize leaf blighting, which reduced grain yields by 36–72% in susceptible maize hybrids. • Maize resistance breeding has produced locally adapted hybrids that do not have significant yield losses under NLB disease pressure.Department of Agriculture, Forestry and Fisheries Research Technology Fund through the National Research Foundation of South Africa; USAID through the University of California Davis Research and Innovation Fellowship for Agriculture.http://www.sajs.co.zaam2021BiochemistryForestry and Agricultural Biotechnology Institute (FABI)GeneticsMicrobiology and Plant PathologyPlant Production and Soil Scienc