Biology subjects

Jindal, M.

Publications and source records attributed to Jindal, M..

3 recordsLinked to original sources

bioRxiv2025

Biophysically relevant network model of the piriform cortex predicts odor frequency encoding using network mechanisms

Olfactory-guided animals utilize fast concentration fluctuations in turbulent odor plumes to perceive olfactory landscapes. Recent studies have demonstrated that the olfactory bulb (OB) encodes such temporal features present in natural odor stimuli. However, whether this temporal information is encoded in the piriform cortex (PCx) remains unknown. Hence, we developed a biophysically relevant PCx network model and simulated it using previously recorded in vivo activities of mitral and tufted cells in response to 2Hz and 20Hz odor frequencies for three stimulus mixtures. Analysis of single-cell activity across trials revealed that individual pyramidal neurons (PYRs) were largely ineffective at discriminating between 2Hz and 20Hz. However, the trial-averaged activity of the PYR population could discriminate between the two frequencies significantly. Moreover, using log-likelihood scores we further discovered that odor frequency discrimination happened through a highly distributed mechanism among the PYRs. One-dimensional convolutional neural network models trained and tested on PYRs activities achieved discrimination accuracies up to 95%. Using virtual synaptic knockout models, we found that eliminating either feedback or feedforward inhibition onto PYRs improved the decoding accuracy across all odor conditions. Conversely, eliminating recurrent excitation among PYRs or simultaneously eliminating recurrent inhibition within both interneuron populations degraded decoding performance. Removing recurrent connections within individual interneuron populations had minimal effects on the performance. Overall, our PCx model demonstrates that it can discriminate between 2Hz and 20Hz odor stimuli, with a bidirectional capability of performance modulation by specific circuit motifs. These findings predict that the piriform cortex encodes and processes temporal features of odor stimuli. New & NoteworthyWe simulated the first biophysically relevant network model of the piriform cortex (PCx) to show differential encoding of odor frequencies at 2Hz and 20Hz. 1D convolutional neural networks demonstrated a distributed role of pyramidal neurons in the encoding. Surprisingly, eliminating feedforward or feedback inhibition improves frequency discrimination, while eliminating recurrency impairs it. Specific circuit motifs, not just baseline activity levels, determine odor frequency representation. Overall, our results predict the PCxs capacity for temporal odor processing.

neuroscience↗

bioRxiv2024

A new discrete-geometry approach for integrative docking of proteins using chemical crosslinks

The structures of protein complexes allow us to understand and modulate the biological functions of the proteins. Integrative docking is a computational method to obtain the structures of a protein complex, given the atomic structures of the constituent proteins along with other experimental data on the complex, such as chemical crosslinks or SAXS profiles. Here, we develop a new discrete geometry-based method, wall-EASAL, for integrative rigid docking of protein pairs given the structures of the constituent proteins and chemical crosslinks. The method is an adaptation of EASAL (Efficient Atlasing and Search of Assembly Landscapes), a state-of-the-art discrete geometry method for efficient and exhaustive sampling of macromolecular configurations under pairwise inter-molecular distance constraints. We provide a mathematical proof that the method finds a structure satisfying the crosslink constraints under a natural condition satisfied by energy landscapes. We compare wall-EASAL with IMP (Integrative Modeling Platform), a commonly used integrative modeling method, on a benchmark, varying the numbers, types, and sources of input crosslinks, and sources of monomer structures. The wall-EASAL method performs better than IMP in terms of the average satisfaction of the configurations to the input crosslinks and the average similarity of the configurations to their corresponding native structures. The ensembles from IMP exhibit greater variability in these two measures. Further, wall-EASAL is more efficient than IMP. Although the current study uses crosslinks, the method is general and any source of distance constraints can be used for integrative docking with wall-EASAL. However, the current implementation only supports binary rigid protein docking, i.e., assumes that the monomer structures are known and remain rigid. Additionally, the current implementation is deterministic, i.e., it does not account for uncertainties in the crosslinking data beyond using distance bounds. Neither of these appears to be a theoretical or algorithmic limitation of the EASAL methodology. Structures from wall-EASAL can be incorporated in methods for modeling large macromolecular assemblies, for example by suggesting rigid bodies or restraints for use in these methods. This will facilitate the characterization of assemblies and cellular neighborhoods at increased efficiency, accuracy, and precision. The wall-EASAL method is available at https://bitbucket.org/geoplexity/easal-dev/src/Crosslink and the benchmark is available at https://github.com/isblab/Integrative_docking_benchmark.

bioinformatics↗

bioRxiv2024

Guava cv. Allahabad Safeda Chromosome scale assembly and comparative genomics decodes breeder choice marker trait association for pink pulp colour

Deciphering chromosomal length genome assemblies has the potential to unravel an organisms evolutionary relationships and genetic mapping of traits of commercial importance. We assembled guava genome using a hybrid sequencing approach with [~]450x depth Illumina short reads, [~]35x PacBio long reads and Bionano maps to [~]594 MB Scaffold length on 11 pseudo chromosomes ([~]479 MB contig length). Maker pipeline predicted 17,395 genes, 23% greater from earlier draft produced in same cultivar Allahabad Safeda. The genome assembly clarified guava evolutionary history, for example revealing predominance of gene expansion by dispersed duplications, in particular contributing to abundance of monoterpene synthases; and supporting evidence of a whole genome duplication event in guava as in other Myrtaceae. Guava breeders have been aiming to reduce screening time for selecting pink pulp colour progenies using marker-trait associations, but a previous comparative transcriptomics and comparative genomics approach with draft genome assembly to identify the effector gene associated with pink pulp was unsuccessful. Here, genome re-sequencing with Illumina short reads at [~]25x depth of 20 pink fleshed and/or non-coloured guava cultivars and comprehensive analysis for genes in the carotenoid biosynthesis pathway identified structural variations in Phytoene Synthase 2. Further, ddRAD based association mapping in core-collection of 82 coloured and non-coloured genotypes from Indian sub-continent found strong association with the same causal gene. Subsequently, we developed PCR based Indel/SSR breeder friendly marker that can readily be scored in routine agarose gels and empowers accurate selection for seedlings that will produce fruits with pink pulp.

plant biology↗