Biology subjects

Mukhopadhyay, A.

Publications and source records attributed to Mukhopadhyay, A..

79 records · Page 5Linked to original sources

bioRxiv2019

A chromosome-scale assembly of allotetraploid Brassica juncea (AABB) elucidates comparative architecture of the A and B genomes

Brassica juncea (AABB; genome size [~]920 Mb), commonly referred to as mustard, is a natural allopolyploid of two diploid species - B. rapa (AA) and B. nigra (BB). We report a highly contiguous genome assembly of an oleiferous type of B. juncea variety Varuna, an archetypical Indian gene pool line of mustard, with [~]100x PacBio single-molecule real-time (SMRT) reads providing contigs with an N50 value of >5Mb. Assembled contigs were corrected and scaffolded with BioNano optical mapping. Three different linkage maps containing a large number of GBS markers were developed and used to anchor scaffolds/contigs to the 18 linkage groups of B. juncea. The resulting chromosome-scale assembly is a significant improvement over the previous draft assembly of B. juncea Tumida, a vegetable type of mustard. The assembled genome was characterized for transposons, centromeric repeats, gene content, and gene block associations. Both A and B genomes contain highly fragmented gene block arrangements. In comparison to the A genome, the B genome contains a significantly higher content of LTR/Gypsy retrotransposons, distinct centromeric repeats and a large number of B. nigra specific gene clusters that break the gene collinearity between the A and the B genomes. The genome assembly reported here will provide a fillip to the breeding work on oleiferous types of mustard that are grown extensively in the dry land areas of South Asia and elsewhere.

genomics↗

bioRxiv2019

A toolset of constitutive promoters for metabolic engineering of Rhodosporidium toruloides

BackgroundRhodosporidium toruloides is a promising host for the production of bioproducts from lignocellulosic biomass. A key prerequisite for efficient pathway engineering is the availability of robust genetic tools and resources. However, there is a lack of characterized promoters to drive expression of heterologous genes for strain engineering in R. toruloides.\n\nResultsOur data describes a set of native R. toruloides promoters, characterized over time in four different media commonly used for cultivation of this yeast. The promoter sequences were selected using transcriptional analysis and several of them were found to drive expression bidirectionally. We measured promoter expression strength by flow cytometry using a dual fluorescent reporter system. From these analyses, we found a total of 20 constitutive promoters (12 monodirectional and 8 bidirectional) of potential value for genetic engineering of R. toruloides.\n\nConclusionsWe present a list of robust and constitutive, native promoters to facilitate genetic engineering of R. toruloides. This set of thoroughly characterized promoters significantly expands the range of engineering tools available for this yeast and can be applied in future metabolic engineering studies.

synthetic biology↗

bioRxiv2019

BjuWRR1, a CC-NB-LRR gene identified in Brassica juncea, confers resistance to white rust caused by Albugo candida

White rust caused by oomycete pathogen Albugo candida is a significant disease of crucifer crops including Brassica juncea (mustard), a major oilseed crop of the Indian subcontinent. Earlier a resistance-conferring locus named AcB1-A5.1 was mapped in an east European gene pool line of B. juncea - Donskaja-IV. This line was tested along with some other lines of B. juncea (AABB), B. rapa (AA) and B. nigra (BB) for resistance to six isolates of A. candida collected from different mustard growing regions of India. Donskaja-IV was found to be completely resistant to all the tested isolates. Sequencing of a BAC spanning the locus AcB1-A5.1 showed the presence of a single CC-NB-LRR protein encoding R gene. The genomic sequence of the putative R gene with its native promoter and terminator was used for the genetic transformation of a susceptible Indian gene pool line Varuna and was found to confer complete resistance to all the isolates. This is the first white rust resistance-conferring gene described from Brassica species and has been named BjuWRR1. Allelic variants of the gene in B. juncea germplasm and orthologues in the Brassicaceae genomes were studied to understand the evolutionary dynamics of the BjuWRR1 gene.\n\nHighlightBjuWRR1, a CNL type R gene, was identified from an east European gene pool line of Brassica juncea and validated for conferring resistance to white rust by genetic transformation.

plant biology↗

bioRxiv2018

Methyl ketone production by Pseudomonas putida is enhanced by plant-derived amino acids

Plant biomass is an attractive source of renewable carbon for conversion to biofuels and bio-based chemicals. Conversion strategies often use a fraction of the total biomass, focusing on sugars from cellulose and hemicellulose. Strategies that use plant components such as plant-derived aromatics and amino acids have the potential to improve the efficiency of overall biomass conversion. Pseudomonas putida is a promising host for biomass conversion for its ability to metabolize a wide variety of organic compounds, including aromatics derived from lignin. P. putida was engineered to produce medium chain methyl ketones, which are promising diesel blendstocks and potential platform chemicals, from glucose and lignin-related aromatics, 4-hydroxybenzoate (4-HB) and protocatechuate (PCA). Unexpectedly, P. putida methyl ketone production was enhanced 2-to 5-fold compared to sugar controls when Arabidopsis thaliana hydrolysates derived from engineered plants that overproduce 4-HB and PCA, while E. coli production was lowered in these hydrolysates. This enhancement was more pronounced (~7-fold increase) with hydrolysates derived from non-engineered switchgrass (Panicum virgatum L.) suggesting it did not arise from overproduction of 4-HB and PCA. Global proteomic analysis of the methyl ketone-producing P. putida suggested that plant-derived amino acids may be the source of this enhancement. Mass spectrometry-based measurements of plant-derived amino acids demonstrated a high correlation between methyl ketone production and amino acid concentration in plant hydrolysates. Amendment of glucose-containing minimal media with a defined mixture of amino acids similar to those found in the hydrolysates studied led to a 9-fold increase in methyl ketone titer (1.1 g/L).

bioengineering↗

bioRxiv2018

Habitat-Net: Segmentation of habitat images using deep learning

Understanding environmental factors that influence forest health, as well as the occurrence and abundance of wildlife, is a central topic in forestry and ecology. However, the manual processing of field habitat data is time-consuming and months are often needed to progress from data collection to data interpretation. Computer-assisted tools, such as deep-learning applications can significantly shortening the time to process the data while maintaining a high level of accuracy. Here, we propose Habitat-Net: a novel method based on Convolutional Neural Networks (CNN) to segment habitat images of tropical rainforests. Habitat-Net takes color images as input and after multiple layers of convolution and deconvolution, produces a binary segmentation of the input image. We worked on two different types of habitat datasets that are widely used in ecological studies to characterize the forest conditions: canopy closure and understory vegetation. We trained the model with 800 canopy images and 700 understory images separately and then used 149 canopy and 172 understory images to test the performance of Habitat-Net. We compared the performance of Habitat-Net with a simple threshold based method, a manual processing by a second researcher and a CNN approach called U-Net upon which Habitat-Net is based. Habitat-Net, U-Net and simple thresholding reduced total processing time to milliseconds per image, compared to 45 seconds per image for manual processing. However, the higher mean Dice coefficient of Habitat-Net (0.94 for canopy and 0.95 for understory) indicates that accuracy of Habitat-Net is higher than that of both the simple thresholding (0.64, 0.83) and U-Net (0.89, 0.94). Habitat-Net will be of great relevance for ecologists and foresters, who need to monitor changes in their forest structures. The automated workflow not only reduces the time, it also standardizes the analytical pipeline and, thus, reduces the degree of uncertainty that would be introduced by manual processing of images by different people (either over time or between study sites). Furthermore, it provides the opportunity to collect and process more images from the field, which might increase the accuracy of the method. Although datasets from other habitats might need an annotated dataset to first train the model, the overall time required to process habitat photos will be reduced, particularly for large projects.

ecology↗

bioRxiv2018

A Visualization Tool to Evaluate Pairwise Protein Structure Alignment Algorithms

The alignment of two protein structures is a fundamental problem in structural bioinformatics. In this paper, we propose a novel approach to measure the effectiveness of a sample of three such algorithms, DALI, TM-align and EDAlignsse. The underlying premise of our approach is that structural proximity should translate into spatial proximity.

bioinformatics↗

bioRxiv2017

Plasmid DNA analysis of pristine groundwater microbial communities reveal extensive presence of metal resistance genes

Native plasmids constitute a major category of extrachromosomal DNA elements responsible for harboring and transferring genes important in survival and fitness. A focused evaluation of plasmidomes can reveal unique adaptations required by microbial communities. We examined the plasmid DNA from two pristine wells at the Oak Ridge Field Research Center. Using a cultivation-free method that targets plasmid DNA, a total of 42,440 and 32,232 (including 67 and 548 complete circular units) scaffolds > 2 kb were obtained from the two wells. The taxonomic distribution of bacteria in the two wells showed greater similarity based on their plasmidome sequence, relative to 16S rRNA sequence comparison. This similarity is also evident in the plasmid encoded functional genes. Among functionally annotated genes, candidates providing resistance to copper, zinc, cadmium, arsenic, and mercury were particularly abundant and common to the plasmidome of both wells. The primary function encoded by the most abundant circularized plasmid, common to both wells, was mercury resistance, even though the current ground water does not contain detectable levels of mercury. This study reveals that the plasmidome can have a unique ecological role in maintaining the latent capacity of a microbiome enabling rapid adaptation to environmental stresses.

microbiology↗