Important wheat diseases in the US and their management in the 21st century

Wheat is a crop of historical significance, as it marks the turning point of human civilization 10,000 years ago with its domestication. Due to the rapid increase in population, wheat production needs to be increased by 50% by 2050 and this growth will be mainly based on yield increases, as there is strong competition for scarce productive arable land from other sectors. This increasing demand can be further achieved using sustainable approaches including integrated disease pest management, adaption to warmer climates, less use of water resources and increased frequency of abiotic stress tolerances. Out of 200 diseases of wheat, 50 cause economic losses and are widely distributed. Each year, about 20% of wheat is lost due to diseases. Some major wheat diseases are rusts, smut, tan spot, spot blotch, fusarium head blight, common root rot, septoria blotch, powdery mildew, blast, and several viral, nematode, and bacterial diseases. These diseases badly impact the yield and cause mortality of the plants. This review focuses on important diseases of the wheat present in the United States, with comprehensive information of causal organism, economic damage, symptoms and host range, favorable conditions, and disease management strategies. Furthermore, major genetic and breeding efforts to control and manage these diseases are discussed. A detailed description of all the QTLs, genes reported and cloned for these diseases are provided in this review. This study will be of utmost importance to wheat breeding programs throughout the world to breed for resistance under changing environmental conditions.

A Comprehensive Review of High Throughput Phenotyping and Machine Learning for Plant Stress Phenotyping

During the last decade, there has been rapid adoption of ground and aerial platforms with multiple sensors for phenotyping various biotic and abiotic stresses throughout the developmental stages of the crop plant. High throughput phenotyping (HTP) involves the application of these tools to phenotype the plants and can vary from ground-based imaging to aerial phenotyping to remote sensing. Adoption of these HTP tools has tried to reduce the phenotyping bottleneck in breeding programs and help to increase the pace of genetic gain. More specifically, several root phenotyping tools are discussed to study the plant's hidden half and an area long neglected. However, the use of these HTP technologies produces big data sets that impede the inference from those datasets. Machine learning and deep learning provide an alternative opportunity for the extraction of useful information for making conclusions. These are interdisciplinary approaches for data analysis using probability, statistics, classification, regression, decision theory, data visualization, and neural networks to relate information extracted with the phenotypes obtained. These techniques use feature extraction, identification, classification, and prediction criteria to identify pertinent data for use in plant breeding and pathology activities. This review focuses on the recent findings where machine learning and deep learning approaches have been used for plant stress phenotyping with data being collected using various HTP platforms. We have provided a comprehensive overview of different machine learning and deep learning tools available with their potential advantages and pitfalls. Overall, this review provides an avenue for studying various HTP platforms with particular emphasis on using the machine learning and deep learning tools for drawing legitimate conclusions. Finally, we propose the conceptual challenges being faced and provide insights on future perspectives for managing those issues.

Multi-Trait Multi-Environment Genomic Prediction for End-Use Quality Traits in Winter Wheat

Soft white wheat is a wheat class used in foreign and domestic markets to make various end products requiring specific quality attributes. Due to associated cost, time, and amount of seed needed, phenotyping for the end-use quality trait is delayed until later generations. Previously, we explored the potential of using genomic selection (GS) for selecting superior genotypes earlier in the breeding program. Breeders typically measure multiple traits across various locations, and it opens up the avenue for exploring multi-trait-based GS models. This study's main objective was to explore the potential of using multi-trait GS models for predicting seven different end-use quality traits using cross-validation, independent prediction, and across-location predictions in a wheat breeding program. The population used consisted of 666 soft white wheat genotypes planted for 5 years at two locations in Washington, United States. We optimized and compared the performances of four uni-trait- and multi-trait-based GS models, namely, Bayes B, genomic best linear unbiased prediction (GBLUP), multilayer perceptron (MLP), and random forests. The prediction accuracies for multi-trait GS models were 5.5 and 7.9% superior to uni-trait models for the within-environment and across-location predictions. Multi-trait machine and deep learning models performed superior to GBLUP and Bayes B for across-location predictions, but their advantages diminished when the genotype by environment component was included in the model. The highest improvement in prediction accuracy, that is, 35% was obtained for flour protein content with the multi-trait MLP model. This study showed the potential of using multi-trait-based GS models to enhance prediction accuracy by using information from previously phenotyped traits. It would assist in speeding up the breeding cycle time in a cost-friendly manner.

Prospectus of Genomic Selection and Phenomics in Cereal, Legume and Oilseed Breeding Programs

The last decade witnessed an unprecedented increase in the adoption of genomic selection (GS) and phenomics tools in plant breeding programs, especially in major cereal crops. GS has demonstrated the potential for selecting superior genotypes with high precision and accelerating the breeding cycle. Phenomics is a rapidly advancing domain to alleviate phenotyping bottlenecks and explores new large-scale phenotyping and data acquisition methods. In this review, we discuss the lesson learned from GS and phenomics in six self-pollinated crops, primarily focusing on rice, wheat, soybean, common bean, chickpea, and groundnut, and their implementation schemes are discussed after assessing their impact in the breeding programs. Here, the status of the adoption of genomics and phenomics is provided for those crops, with a complete GS overview. GS’s progress until 2020 is discussed in detail, and relevant information and links to the source codes are provided for implementing this technology into plant breeding programs, with most of the examples from wheat breeding programs. Detailed information about various phenotyping tools is provided to strengthen the field of phenomics for a plant breeder in the coming years. Finally, we highlight the benefits of merging genomic selection, phenomics, and machine and deep learning that have resulted in extraordinary results during recent years in wheat, rice, and soybean. Hence, there is a potential for adopting these technologies into crops like the common bean, chickpea, and groundnut. The adoption of phenomics and GS into different breeding programs will accelerate genetic gain that would create an impact on food security, realizing the need to feed an ever-growing population.

Comprehensive evaluation of mapping complex traits in wheat using genome-wide association studies

Genome-wide association studies (GWAS) are effectively applied to detect the marker trait associations (MTAs) using whole genome-wide variants for complex quantitative traits in different crop species. GWAS has been applied in wheat for different quality, biotic and abiotic stresses, and agronomic and yield-related traits. Predictions for marker-trait associations are controlled with the development of better statistical models taking population structure and familial relatedness into account. In this review, we have provided a detailed overview of the importance of association mapping, population design, high-throughput genotyping and phenotyping platforms, advancements in statistical models and multiple threshold comparisons, and recent GWA studies conducted in wheat. The information about MTAs utilized for gene characterization and adopted in breeding programs is also provided. In the literature that we surveyed, as many as 86,122 wheat lines have been studied under various GWA studies reporting 46,940 loci. However, further utilization of these is largely limited. The future breakthroughs in area of genomic selection, multi-omics-based approaches, machine, and deep learning models in wheat breeding after exploring the complex genetic structure with the GWAS are also discussed. This is a most comprehensive study of a large number of reports on wheat GWAS and gives a comparison and timeline of technological developments in this area. This will be useful to new researchers or groups who wish to invest in GWAS.

Omics for the Improvement of Abiotic, Biotic, and Agronomic Traits in Major Cereal Crops: Applications, Challenges, and Prospects

Omics technologies, namely genomics, transcriptomics, proteomics, metabolomics, and phenomics, are becoming an integral part of virtually every commercial cereal crop breeding program, as they provide substantial dividends per unit time in both pre-breeding and breeding phases. Continuous advances in omics assure time efficiency and cost benefits to improve cereal crops. This review provides a comprehensive overview of the established omics methods in five major cereals, namely rice, sorghum, maize, barley, and bread wheat. We cover the evolution of technologies in each omics section independently and concentrate on their use to improve economically important agronomic as well as biotic and abiotic stress-related traits. Advancements in the (1) identification, mapping, and sequencing of molecular/structural variants; (2) high-density transcriptomics data to study gene expression patterns; (3) global and targeted proteome profiling to study protein structure and interaction; (4) metabolomic profiling to quantify organ-level, small-density metabolites, and their composition; and (5) high-resolution, high-throughput, image-based phenomics approaches are surveyed in this review.

Omics in Major Cereals: Applications, Challenges, and Prospects.. [PMID: 0 DOI: 10.20944/preprints202104.0531.v1]

Omics technologies, viz., genomics, transcriptomics, proteomics, metabolomics, and phenomics, are becoming an integral part of virtually every commercial cereal breeding program because they provide substantial dividends per unit time in both pre-breeding and breeding phases. Continuous advances in cereal-omics promise—in combination with time efficiency—the cost benefits. In this review, we provide a comprehensive overview of the established cereal-omics methods in five major cereals, viz., rice, sorghum, maize, barley, and bread wheat. We cover the evolution of technologies in each omics section independently and concentrate on their use to improve economically important agronomic as well as biotic and abiotic stress-related traits. Advancements in the (1) identification, mapping, and sequencing of molecular/structural variants, (2) high-density transcriptomics data to study gene expression patterns, (3) global and targeted proteome profiling to study protein structure and interaction, (4) metabolomic profiling to quantify organ level small-density metabolites and their composition, and (5) high-resolution high-throughput image-based phenomics approaches are surveyed in this review.

Combining Genomic and Phenomic Information for Predicting Grain Protein Content and Grain Yield in Spring Wheat

Genomics and high throughput phenomics have the potential to revolutionize the field of wheat (Triticum aestivum L.) breeding. Genomic selection (GS) has been used for predicting various quantitative traits in wheat, especially grain yield. However, there are few GS studies for grain protein content (GPC), which is a crucial quality determinant. Incorporation of secondary correlated traits in GS models has been demonstrated to improve accuracy. The objectives of this research were to compare performance of single and multi-trait GS models for predicting GPC and grain yield in wheat and to identify optimal growth stages for collecting secondary traits. We used 650 recombinant inbred lines from a spring wheat nested association mapping (NAM) population. The population was phenotyped over 3 years (2014-2016), and spectral information was collected at heading and grain filling stages. The ability to predict GPC and grain yield was assessed using secondary traits, univariate, covariate, and multivariate GS models for within and across cycle predictions. Our results indicate that GS accuracy increased by an average of 12% for GPC and 20% for grain yield by including secondary traits in the models. Spectral information collected at heading was superior for predicting GPC, whereas grain yield was more accurately predicted during the grain filling stage. Green normalized difference vegetation index had the largest effect on the prediction of GPC either used individually or with multiple indices in the GS models. An increased prediction ability for GPC and grain yield with the inclusion of secondary traits demonstrates the potential to improve the genetic gain per unit time and cost in wheat breeding.

Deep Learning for Predicting Complex Traits in Spring Wheat Breeding Program

Genomic selection (GS) is transforming the field of plant breeding and implementing models that improve prediction accuracy for complex traits is needed. Analytical methods for complex datasets traditionally used in other disciplines represent an opportunity for improving prediction accuracy in GS. Deep learning (DL) is a branch of machine learning (ML) which focuses on densely connected networks using artificial neural networks for training the models. The objective of this research was to evaluate the potential of DL models in the Washington State University spring wheat breeding program. We compared the performance of two DL algorithms, namely multilayer perceptron (MLP) and convolutional neural network (CNN), with ridge regression best linear unbiased predictor (rrBLUP), a commonly used GS model. The dataset consisted of 650 recombinant inbred lines (RILs) from a spring wheat nested association mapping (NAM) population planted from 2014-2016 growing seasons. We predicted five different quantitative traits with varying genetic architecture using cross-validations (CVs), independent validations, and different sets of SNP markers. Hyperparameters were optimized for DL models by lowering the root mean square in the training set, avoiding model overfitting using dropout and regularization. DL models gave 0 to 5% higher prediction accuracy than rrBLUP model under both cross and independent validations for all five traits used in this study. Furthermore, MLP produces 5% higher prediction accuracy than CNN for grain yield and grain protein content. Altogether, DL approaches obtained better prediction accuracy for each trait, and should be incorporated into a plant breeder's toolkit for use in large scale breeding programs.

Real-Time Simulator based hybrid control of DFIG-WES

This paper presents the analysis and design of recurrent neural network (RNN) and proportional and integral(PI) controller based hybrid control(HC) of doubly fed induction generator (DFIG). The proposed HC shows the quick dynamic and good transient response during the sudden changes in wind speed as well as generator speed. Further performance of proposed hybrid controller has been analyzed independently with RNN and PI control as its components. The HC along with RNN gives effective performance compared to conventional DTC (CDTC) and PI DTC in terms of flux ripples,torque ripples and settling time. The proposed technique is implemented in real-time simulator (RTS) based OPAL-RT and MATLAB/SIMULINK environment at a rating of 5.5 KW system under steeply and randomly change in wind velocity.

Post-stroke fatigue: a problem of altered corticomotor control?

OBJECTIVES

We recently showed that diminished motor cortical excitability is associated with high levels of post-stroke fatigue. Motor cortex excitability impacts movement parameters such as reaction and movement times. We predicted that one or both would be influenced by the presence of post-stroke fatigue.

METHODS

41 first-time stroke survivors (high fatigue n=21, Fatigue Severity Scale 7 (FSS-7) score >5; low fatigue n=20, FSS-7 score <3) participated in the study. Movement times, choice and simple reaction times were measured in all participants.

RESULTS

A three way ANOVA with fatigue (high and low), task (movement time, simple reaction time and choice reaction time) and hand (affected and unaffected) as the three factors, revealed a significant difference between affected (but not unaffected) hand movement times in the high compared to low fatigue groups. Reaction times, however, were not different between the high-fatigue and low-fatigue groups in either the affected or unaffected hand.

CONCLUSIONS

Previously, we showed that motor cortex excitability is lower in patients with high post-stroke fatigue. Our current findings suggest that post-stroke fatigue (1) is a problem of movement speed (possibly a consequence of diminished motor cortex excitability) and not movement preparation, and (2) may have a focal origin confined to the lesioned hemisphere. We suggest that low motor cortex excitability in the lesioned hemisphere is a viable therapeutic target in post-stroke fatigue.

Inheritance and molecular mapping of a gene conferring seedling resistance against Puccinia hordei in the barley cultivar Ricardo

Genetic studies were undertaken to determine the inheritance and genomic location of uncharacterised seedling resistance to leaf rust, caused by Puccinia hordei, in the barley cultivar Ricardo. The resistance was shown to be conferred by a single dominant gene, which was tentatively designated RphRic. Bulk segregant analysis (BSA) and genetic mapping of an F(3) mapping population using multiplex-ready SSR genotyping and Illumina GoldenGate SNP assay located RphRic in chromosome 4H. Given that this is the first gene for leaf rust resistance mapped on chromosome 4H, it was designated Rph21. The presence of an additional gene, Rph2, in Ricardo, was confirmed by the test of allelism. The seedling gene Rph21 has shown effectiveness against all Australian pathotypes of P. hordei tested since at least 1992 and hence represents a new and useful source of resistance to this pathogen.

Evaluation of factors contributing to excessive nitrate accumulation in fodder crops leading to ill-health in dairy animals

A study was conducted to estimate nitrate content in commonly used fodder crops, viz., berseem (Trifolium alexandrinum), bajra (Pennisetum glaucum), maize (Zea mays), oats (Avena sativa), sorghum (Sorghum vulgare) and toriya (Brassica napus), collected from the fields of different villages of Punjab and farms of the university, and to evaluate the factors associated with nitrate accumulation in these crops. The nitrate level was highest in sorghum on dry matter basis, followed by oats and toriya, berseem, maize and bajra. The nitrate content was also determined in fodder samples harvested from young and mature stages and in different parts of plants. The stem part of forages had higher content than leaves; however, concentrations were low in mature crops as compared to immature ones. The environmental and soil factors associated with it are discussed and correlated with the experimental findings.

Serological survey of antibodies to Toxoplasma gondii in sheep, cattle, and buffaloes in Punjab, India

Sera from 186 sheep, 83 cattle, and 103 water buffaloes from Punjab, India, were evaluated for antibodies to Toxoplasma gondii using a commercial ELISA kit. This study was planned using a 2-stage random sampling procedure and sampling software 'survey toolbox.' In the first step, villages were selected randomly from a sampling frame of all the villages of Punjab, followed by selection of owners and animals in the second step. Antibodies to T. gondii were found in 7 of 186 sheep, 2 of 83 cattle, and 3 of 103 buffaloes. Results indicate a low prevalence of T. gondii in ruminants tested.

Sero-prevalence of Bovine Johne's disease in buffaloes and cattle population of North India using indigenous ELISA kit based on native Mycobacterium avium subspecies paratuberculosis ‘Bison type’ genotype of goat origin

Present pilot study is the first attempt in the country to estimate sero-prevalence of Bovine Johne's disease (BJD) by screening cattle and buffaloes representing large population belonging to farmer's and farm herds in the home tracts (Uttar Pradesh (UP) and Punjab) of Hariana cattle and Murrah buffaloes in North India. Indigenous and in-house plate ELISA kit (using protoplasmic antigen from native Mycobacterium avium subsp. paratuberculosis 'Bison type' strain of goat origin), originally developed for goats and sheep was standardized in bovines and used for screening. For this study, 33 villages of south and west UP were randomly selected and surveyed from 2001 to 2003. There were 7943 farmer's families having 38,251 livestock, including cattle, buffaloes, goats and sheep (per family 4.8% livestock). Numerically, buffaloes and cattle were 54.7% and 22.1%, respectively. Serum samples were collected from 726 animals (4.2% of 16, 981 livestock with 4375 farmer's families) located in 33 randomly surveyed villages. Serum samples (699), submitted to Epidemiology Department of Veterinary College (Punjab Agricultural University, Ludhiana), in the year 2004 by farmer's and organized farm herds (Buffaloes, 372, Cattle, 327), were screened by this ELISA kit. Soluble protoplasmic antigen was prepared from Map (S 5) 'Bison type' strain isolated from a terminally sick goat with Johne's disease. Of the total 1425 bovine (Buffaloes and cattle) serum samples screened using indigenous ELISA kit, sero-prevalence of Johne's disease was 29.0% (28.6% in buffalo and 29.8% in cattle) in Northern India. State-wise sero-prevalence was 31.9% and 23.3% in UP and Punjab, respectively. In UP, of the 601 randomly sampled buffaloes, sero-prevalence was 40.3% (16.6% in young and 40.9% adults) and 25.5% (10.5% in young and 26.3% adults) in south and west UP, respectively. Of the 125 cattle screened, sero-prevalence was 42.6% (nil in young and 44.4% adults) and 30.0% (nil in young and 30.6% adults) in south and west UP, respectively. Of the 699 serum samples screened from Ludhiana, Punjab, sero-prevalence of BJD was 23.0%. Sero-prevalence was 23.3% (12.1% in young and 24.4% in adults) and 26.9% (27.2% in young and 26.8% in adults) in buffaloes and cattle, respectively. High prevalence of BJD in buffaloes in native tract of Murrah breed, and Hariana breed of cattle correlated with poor per-animal productivity and BJD may be the major cause. Indigenous ELISA kit was rapid, economic and sensitive test for large-scale screening of buffaloes and cattle population against incurable BJD.

Seroprevalence of Neospora caninum antibodies in cattle and water buffaloes in India

Neospora caninum is now recognized as a major cause of abortion in cattle worldwide, but there is no report of N. caninum infection in cattle in India. Serum samples from 427 dairy cattle and 32 dairy water buffaloes from 7 organized dairy farms located in Punjab, India, were tested for N. caninum antibodies using a commercial monoclonal antibody-based competitive enzyme-linked immunosorbent assay (ELISA). Antibodies to N. caninum were found in 35 of 427 cattle from 6 of the 7 farms; 9.6% of cows, 5.1% of heifers, and 5.0% of calves were seropositive, suggesting postnatal transmission of N. caninum on the farm. Antibodies to N. caninum were found in 16 of 32 buffaloes tested from 2 dairy farms. In total, 64 cattle and 16 buffalo sera already tested by ELISA were also evaluated by an indirect fluorescent antibody test (IFAT) to verify ELISA results. Of the 64 cattle samples, 29 sera were negative by both tests and of the 35 ELISA-positive sera, 12 had IFAT titers of 1:100 or higher (1 had IFAT titer of 100, 2 had IFAT titer of 200, and 9 had IFAT titers of 400 or higher). Of the 16 buffalo sera positive by ELISA, 1 had an IFAT titer of 1:400. Thus, antibodies to N. caninum were demonstrated in cattle sera by 2 serologic methods. To our knowledge this is the first report of N. caninum infection in cattle and buffaloes in India.

Evaluation of highly sensitive indigenous milk ELISA kit with fecal culture, milk culture and fecal-PCR for the diagnosis of bovine Johne's disease (BJD) in India

Country lacks indigenous diagnostic kits against Johne's disease in animals. Indigenous ELISA and IS 900 PCR kits, originally developed for goats and sheep, have been adapted for screening of lactating cows. Multiple diagnostic tests were used to screen 26 lactating dairy cows against Johne's disease. Milk ELISA was evaluated with fecal culture, milk culture and fecal PCR. Of the 26 samples from lactating cows, 84.6, 96.1, 88.4 and 23.0% were positive in fecal culture, milk culture, m-ELISA and m-PCR, respectively. Comparatively milk sediment and milk fat culture detected 84.6 and 76.9% cows positive, respectively. Comparatively fecal culture and milk culture detected 84.6 and 96.1% cows positive, respectively. M-ELISA detected 11.5, 0.0, 11.5, 61.0 and 15.3%, cows as negative, suspected, low positive, positive and strong positive, respectively. There was good correlation between milk and fecal culture with m-ELISA. Three negative cows in m-ELISA were also detected in milk and fecal culture. Of the 26 decontaminated fecal samples, 23.0% cows were positive using specific IS 900 f-PCR. Comparative evaluation of m-ELISA with fecal and milk culture showed agreement in 80.7 and 84.6% cows, respectively. Sensitivity of m-ELISA with respect to fecal and culture was 90.9 and 95.6%, respectively. Comparative evaluation of four tests (milk culture, fecal culture, m-ELISA and f-PCR) showed that only 15.3% cows were detected in all the four tests. In three tests (fecal and milk culture and m-ELISA), 57.6% cows were detected positive. None of the cow was exclusively detected in f-PCR. Of the four diagnostic tests used milk culture was most sensitive (96.15%), followed by fecal culture (86.6%), m-ELISA (76.9%) and IS 900 PCR (23.0%) for the diagnosis of bovine Johne's disease (BJD). Milk ELISA detected only one cow extra, which was negative in milk culture. In view of the simplicity, rapidity and efficacy present milk ELISA kit employing soluble protoplasmic antigen from native Map 'Bison type' genotype of goat origin can be reliable for screening of bovine population against Johne's disease in India.

A study on the epidemiology of brucellosis in Punjab (India) using Survey Toolbox

A random survey was conducted to study the epidemiology of brucellosis in Punjab (India), using the 'Survey Toolbox' sampling software. A two-stage sampling procedure was adopted: in the first stage, villages were selected, and in the second the selection of animals was made. In all, 52 villages were selected randomly from a sampling frame of all the villages of Punjab. The total number of animals in these villages was 18,644, out of which 973 animals (approximately 5%) belonging to various owners were randomly selected. Serum samples collected from the animals were screened for Brucella antibodies by an avidinbiotin enzyme-linked immunosorbent assay, which showed the apparent overall prevalence of brucellosis to be 12.09% (true prevalence, 11.23%). The prevalence varied from a low of 0% to a high of 24.3% in various districts. Higher variance (0.08) was noted within villages than between different villages (0.03). The prevalence rates among buffaloes and cattle were 13.4% and 9.9%, respectively. The seroprevalence of brucellosis was found to be significantly higher (chi square = 24.50, p < 0.001) in animals with a history of abortion (33.87%) than in those without such a history (11.63%).

Efficacy of abamectin against ivermectin-resistant strain of Trichostrongylus colubriformis in sheep

The efficacy of two formulations of abamectin, i.e. oral and injectable was determined against ivermectin-resistant strain of T. colubriformis in sheep. Twenty-four lambs were infected with 10,000 third stage larvae of ivermectin-resistant strain of T. colubriformis. Twenty-four days post-infection, the lambs were divided randomly into four groups of six animals each according to egg counts. The first group was left untreated and kept as a control. The second group was treated with ivermectin (oral) at 0.2mg kg(-1) body weight. The third group was treated with oral formulation of abamectin at 0.2mg kg(-1) body weight. The fourth group was treated with injectable formulation of abamectin at 0.2mg kg(-1) body weight. Fecal egg count and controlled slaughter tests were employed to determine the efficacy of abamectin (oral and injection) against ivermectin-resistant strain of T. colubriformis in sheep. Reduction in arithmetic mean fecal egg counts achieved by ivermectin (oral), abamectin (oral) and abamectin (injection) was 66, 98 and 76%, respectively 10 days after treatment. Ivermectin (oral), abamectin (oral) and abamectin (injection) reduced arithmetic mean worm burden by 63, 97 and 74%, respectively. The findings demonstrated that abamectin oral formulation was more effective than abamectin injection against ivermectin-resistant strain of T. colubriformis in sheep.

Pathogenic Shiga toxin-producing Escherichia coli in the intestine of calves

The purpose of this study was to compare the pathological effects of Shiga toxin-producing Escherichia coli (STEC) that vary in their association with bovine and human disease. Shiga toxin-producing E. coli of serotypes associated with both dysentery in calves and hemolytic uremic syndrome (HUS) in humans (O5:H-, O26:H11, O111:H-,O113:H21) were compared with O157:H7 STEC, which are associated with HUS in humans but not with disease in calves. The STEC were administered orally to 80 day-old chicks and into ligated loops in the ileum and colon of four 2- to 6-day-old calves. Examination of the ceca of the chickens 10 d postchallenge showed no adherence or tissue abnormality for any isolate. The calves were euthanized 8 to 10 h postinoculation, and sections of the intestinal loops were examined by light microscopy, transmission and scanning electron microscopy, and immunohistochemistry. All strains showed consistent focal adherence associated with mild lesions in the colon. Attaching and effacing lesions were observed with the eae-positive strains. Ileal lesions were similar to the colonic ones but were sometimes severe, with marked polymorphonuclear leukocyte proliferation in the lamina propria. It is concluded that chickens were unsuitable for studying interaction of STEC with the intestine and that there was no difference in the interaction of the ligated calf intestine with STEC of serotypes associated with disease in calves compared with O157:H7 STEC.

Virulence markers in Shiga toxin-producing Escherichia coli isolated from cattle

This study identified potential virulence markers in 93 eae-positive and 179 eae-negative Shiga toxin-producing Escherichia coli (STEC), isolated from a random sampling of healthy cattle in southwestern Ontario. PCR amplification was used to identify genes for enterohemorrhagic E. coli (EHEC)-hemolysin, the EAF plasmid, and bundle-forming pili (Bfp); adherence to HEp-2 cells and to bovine colonocytes, and the fluorescent actin staining (FAS) test were used to characterize interaction of the bacteria with epithelial cells. The EHEC-hemolysin sequences were detected in 98% of eae-positive isolates compared with 34% of eae-negative isolates. All isolates were negative for EAF and bfp sequences. There was 100% correlation between localized adherence (LA) to HEp-2 cells and the FAS test. Forty-eight (52%) of the eae-positive isolates were LA/FAS-positive, whereas none of the 179 eae-negative isolates was positive in either test. Among the eae-negative isolates, 20 (11%) showed diffuse adherence and 5 (2.8%) showed enteroaggregative adherence to HEp-2 cells. Seventy-three percent of the eae-positive isolates adhered to bovine colonocytes, whereas only 26% of 120 eae-negative isolates that were tested adhered. All 13 O157:H7 isolates were positive for eae and EHEC-hemolysin gene sequences, LA/FAS, and adherence to bovine colonocytes. It is concluded that possession of genes for eae and EHEC hemolysin is correlated with the serotype of STEC, that production of EHEC hemolysin was highly correlated with serotypes implicated in human disease, and that none of the potential markers that were examined can be used to predict the potential virulence of an isolate.

Hemolysin phenotypes and genotypes of eaeA-positive and eaeA-negative bovine verotoxigenic Escherichia coli

Intimin or EaeA protein has been implicated in the attaching/effacing lesion caused by entero-hemorrhagic Escherichia coli (EHEC) in the intestine but it is not produced by all EHEC and is therefore not adequate as a marker for EHEC. Hemolysins are produced by a high percentage of verotoxigenic E. coli (VTEC) and could be a marker for EHEC, but their distribution and relation to virulence are not known. We used PCR amplification to determine the presence or absence of eaeA sequences in 281 VTEC isolates from the feces of healthy cattle. There were 101 eaeA-positive isolates, which belonged to O groups 5, 26, 69, 80, 84, 98, 103, 111, 119, 145, 157 and 108 eaeA-negative isolates, which belonged to O groups 8, 22, 38, 113, 119, 116, 132, 153, 156 or untypable. All isolates were tested for hemolysis on horse blood agar and on washed sheep blood agar. PCR amplification was used to test for EHEC hemolysin, Ehly1, Ehly2 and alpha-hemolysin D sequences. Among eaeA-positive isolates 98% were positive for EHEC hemolysin sequences and were hemolytic on washed sheep red blood cell agar; the corresponding percentage for eaeA-negative isolates was 36%. Ehly1 and Ehly2 sequences were present in only 11 isolates (O groups 26, 84, 119 and 132). None of the eaeA-positive and 13 of the eaeA-negative isolates (including all 11 isolates of O group 132) were positive for alpha-hemolysin D gene sequences by PCR and alpha-hemolysin production on horse blood agar. We conclude that since Ehly1, Ehly2 and alpha-hemolysin occur at low frequency among bovine VTEC and serotypes implicated in human disease they are unlikely to be significant virulence factors. In contrast, EHEC hemolysin was present in almost all eaeA-positive VTEC isolates and in approximately one-third the eaeA-negative ones; it may be both a virulence marker and virulence factor but further testing is required. The study identified isolates with all combinations of eaeA and EHEC hly, which may be useful for further testing.

Vero cytotoxigenic Escherichia coli infection in dairy farm families

Fecal samples from 335 dairy farm residents and 1458 cattle on 80 farms were tested for Vero cytotoxin (VT)-producing Escherichia coli (VTEC). Residents were also tested for antibodies to VT1 and O157 lipopolysaccharide (LPS). Residents and cattle on farms with VTEC-positive persons or E. coli O157:H7-positive cattle were retested. Twenty-one persons (6.3%) on 16 farms (20.8%) and 46% of cattle on 100% of the farms had VTEC in fecal samples. Human VTEC isolates included E. coli O157:H7 and 8 other serotypes, 4 of which were present in cattle on the same farms. More persons had antibodies to VT1 (41%) than to O157 LPS (12.5%). Seropositivity to O157 LPS was associated with isolation of E. coli O157:H7 on the farm (P = .022). Human VTEC infection was negatively associated with age (P < .05) and was not associated with clinical illness. Many dairy farm residents experience subclinical immunizing VTEC infections at a young age, which frequently involve non-O157 VTEC found in cattle.

Prevalence of the eaeA gene in verotoxigenic Escherichia coli strains from dairy cattle in Southwest Ontario

This study determined the prevalence of the eaeA gene and its relationship to serotype and type of verotoxin produced in a collection of 432 verotoxigenic Escherichia coli (VTEC) obtained from the faeces of healthy cows and calves in a systematic random survey involving 80 dairy farms in Southwest Ontario. A PCR amplification procedure involving primer pairs which target the conserved central region of the O157:H7 eaeA gene showed that 151 (35.2%) strains were positive for the eaeA gene. All isolates (9-21 for each O group) of O groups 5, 26, 69, 84, 103, 111, 145 and 157 were positive, whereas all isolates (7-34 for each O group) of O groups 113, 132, and 153 and serotype O156:NM (38 isolates) were negative for eaeA. Seventy-three percent of 130 isolates of eaeA-positive serotypes produced VT1 only compared with 20% of 253 isolates of eaeA-negative serotypes. We conclude that there is a strong association between certain O groups and the eaeA gene, that serotypes of eaeA-positive and eaeA-negative VTEC implicated in human and cattle disease are present at high frequency in the faeces of healthy cattle, that VT1 is more frequently associated with eaeA-positive than with eaeA-negative serogroups, and that the eaeA gene is more frequently found in VTEC from calves compared with VTEC from adult cattle.

Comparative study in cattle and buffaloes for evaluation of various diagnostic tests for brucellosis

Serum samples from 1134 vaccinated and non vaccinated animals (775 cattle and 359 buffaloes) were screened with different serological tests like Rose Bengal plate Test (RBPT), plate agglutination test (PAT) and standard tube agglutination test (SAT). The agreement between these three screening tests was 87.19% and 97.86% in vaccinated and non vaccinated cattle while corresponding figures in buffaloes were 91.56% and 84.42%. Among vaccinated animals a positive percentage of 12.8 and 8.8 was noticed in cattle was 4.7 and 6.3, respectively by RBPT. All the positive sera samples were further tested by mercaptoethanol test (MET) and heat inactivation test (HIT) to conform the result of screening tests and to differentiate vaccinal titre from that of active infection. It was concluded that RBPT is overall best screening test to diagnose bovine brucellosis. MET and HIT are good supplementary tests but MET is better than HIT both in cattle and buffaloes. Some high titered non vaccinated buffaloes were negative in RBPT but positive by all other tests.

Cecal perforation following fiberoptic flexible sigmoidoscopy

The superiority of flexible to rigid sigmoidoscopy is resulting in its increasing utilization by primary care physicians. The procedure is relatively risk-free, but complications including perforations may occur. An unusual case of cecal perforation as a result of flexible sigmoidoscopy is presented in order to draw attention to this complication.

Blue rubber bleb nevus syndrome presenting with recurrences

An unusual patient with blue rubber bleb nevus syndrome is presented. At birth a single abdominal wall hemangioma was noted, and over a 21-year follow-up the full syndrome developed, including many cutaneous and intestinal lesions and anemia. Our long-term follow-up of this patient allows an understanding of the natural history of this condition, especially regarding recurrence of lesions after excision.

Effect of pectin on gastric emptying and gastroduodenal motility in normal subjects

The effects of pectin ingestion on gastric emptying, gastroduodenal motility, and plasma levels of glucose, insulin, and glucagon were studied. Initial studies demonstrated that 15 g of pectin was the optimal dose. Subsequently 6 healthy male volunteers were studied on 4 separate days at random. On day 1, gastric emptying of a liquid and a solid meal was assessed by radioisotope technique using 99mTc-dithiopropylthiomine. On day 2, the gastric emptying study was repeated with the addition of pectin to each meal. Plasma levels of glucose, insulin, and glucagon also were determined during these 2 days. On day 3, the effects of liquid and solid meals on gastroduodenal motility were assessed by means of a perfused catheter system. On day 4, the motility study was repeated with the addition of pectin to each meal. Pectin supplementation caused a significant prolongation of gastric emptying half-time of both liquid and solid meals (p less than 0.05). The addition of pectin, however, did not have any significant effect on gastroduodenal motility other than increasing the duodenal motility index 10 min after the liquid meal. The addition of pectin to the liquid meal lowered plasma levels of insulin at 15, 30, and 45 min, and glucagon levels 15 min after the meal. No effect was noted on blood sugar levels. On the other hand, the addition of pectin to the solid meal had no effect on plasma levels of glucose, insulin, and glucagon. We conclude that pectin supplementation delays gastric emptying of both liquid and solid meals in normal human subjects without causing notable changes in gastroduodenal motility or significant variations in pancreatic hormone plasma levels. The pectin effect on gastric emptying may be caused solely by increasing the viscosity of the meals.