Biology subjects

Haseeb, M.

Publications and source records attributed to Haseeb, M..

5 recordsLinked to original sources

bioRxiv2026

Evaluating MaxEnt Modeling Strategies for Predicting Suitable Habitats of Invasive Insects Under Climate Change Scenarios

Invasive insect species pose serious threats to agriculture and ecosystems, with their spread increasingly accelerated by global trade and climate change. To support prevention and mitigation efforts, it is essential to map the regions where these pests can survive and thrive. Here, we apply MaxEnt, a leading species distribution modeling framework, to estimate current (2020) and future (2040-2060) suitable habitats for five major invasive insects across the contiguous United States: brown marmorated stink bug, corn earworm, spongy moth, root weevil, and spotted lanternfly. To account for an uncertain climatic future, these projections are generated under four shared socioeconomic pathways, which reflect a range of plausible climate change scenarios. Beyond forecasting distributions, we examine several key modeling decisions, especially those often overlooked in practice. In particular, we find that background sampling strategies play a critical role in model calibration and that a hybrid sampling approach with a moderate buffer bias provides better predictive accuracy. We also show that permutation importance scores, commonly used to rank environmental variables, are highly sensitive to small changes in the background data and should be interpreted with caution. Finally, to bridge the gap between ecological modeling and applied machine learning, we provide a self-contained, math-focused background to MaxEnt aimed at practitioners outside of traditional ecological fields. Overall, this work delivers reproducible modeling workflows and critical insights into building robust, transparent, and ecologically meaningful MaxEnt models for climate-informed species distribution analysis.

ecology↗

bioRxiv2023

Mobilisation and analyses of publicly available SARS-CoV-2 data for pandemic responses

The COVID-19 pandemic has seen large-scale pathogen genomic sequencing efforts, becoming part of the toolbox for surveillance and epidemic research. This resulted in an unprecedented level of data sharing to open repositories, which has actively supported the identification of SARS-CoV-2 structure, molecular interactions, mutations and variants, and facilitated vaccine development and drug reuse studies and design. The European COVID-19 Data Platform was launched to support this data sharing, and has resulted in the deposition of several million SARS-CoV-2 raw reads. In this paper we describe (1) open data sharing, (2) tools for submission, analysis, visualisation and data claiming (e.g. ORCiD), (3) the systematic analysis of these datasets, at scale via the SARS-CoV-2 Data Hubs as well as (4) lessons learned. As a component of the Platform, the SARS-CoV-2 Data Hubs enabled the extension and set up of infrastructure that we intend to use more widely in the future for pathogen surveillance and pandemic preparedness.

bioinformatics↗

bioRxiv2022

P176S polymorphism in Maspin rewires electrostatic interaction that alters Maspin functionality

Maspin has been known to regress tumors by inhibiting angiogenesis, however, its roles have been reported to be context and sequence-dependent. There are various proteins and cofactors that bind with maspin possibly explaining the conflicting roles of maspin. Moreover, maspin polymorphic forms have also been linked to tumor regression or survival, for instance, maspin with Ser at 176 (maspin-S176) promotes tumor while maspin with Pro at 176 (maspin-Pro176) has opposing roles in cancer pathogenesis. With the help of long molecular dynamic simulation, a possible link between polymorphic forms and tumor progression has been established. First, the maspin is dynamically stable with either amino acid at 176 position, secondly, differential contacts have been observed among various regions, thirdly, these contacts have significantly altered the electrostatic energetics of various residues, and finally, these altered electrostatics of maspin-S176 and maspin-P176 rewired the polar contacts that abolished the allosteric control in protein. By combining these factors, the altered electrostatics can substantially affect the localization, and the preference of maspin binding partners, thus, culminating in a different maspin-protein (cofactor)-interaction landscape that could have been manifested with conflicting reports in previous studies. Here, the underlying reason has been highlighted and discussed that could be helpful for better therapeutic manipulations. SignificanceProtein altered functions in response to mutations are well documented, however, a slight perturbation in structure can lead to dramatic effects that are being felt at longer distances are rare. Here, we have reported that the substitution of Pro to Ser at 176th position in Maspin can substantially alter the protein electrostatic interactions that can hamper the allosteric control. This could lead to different binding partners, localization preferences, and altered cytoplasmic retention duration resulting in functions that are not associated with normal protein. Moreover, the electrostatic attraction/repulsion can immensely affect the allosteric cohesion of protein resulting in unexpected outcomes.

biophysics↗

bioRxiv2021

Natural variation in the maternal and zygotic mRNA complements of the early embryo in Drosophila melanogaster

Maternal gene products supplied to the egg during oogenesis drive the earliest events of development in all metazoans. After the initial stages of embryogenesis, maternal transcripts are degraded as zygotic transcription is activated, this is known as the maternal to zygotic transition (MZT). Altering the abundances of maternally deposited factors in the laboratory can have a dramatic effect on development, adult phenotypes and ultimately fitness. Zygotic transcription activation is a tightly regulated process, where the zygotic genome takes over control of development from the maternal genome, and is required for the viability of the organism. Recently, it has been shown that the expression of maternal and zygotic transcripts have evolved in the Drosophila genus over the course of 50 million years of evolution. However, the extent of natural variation of maternal and zygotic transcripts within a species has yet to be determined. We asked how the maternal and zygotic pools of mRNA vary within and between populations of D. melanogaster. In order to maximize sampling of genetic diversity, African lines of D. melanogaster originating from Zambia as well as DGRP lines originating from North America were chosen for transcriptomic analysis. Single embryo RNA-seq was performed at a stage before and a stage after zygotic genome activation in order to determine which transcripts are maternally deposited and which are zygotically expressed within and between these populations. Differential gene expression analysis has been used to quantify quantitative changes in RNA levels within populations as well as fixed expression differences between populations at both stages. Generally, we find that maternal transcripts are more highly conserved, and zygotic transcripts evolve at a higher rate. We find that there is more within population variation in transcript abundance than between populations and that expression variation is highest post-MZT between African lines. Determining the natural variation of gene expression surrounding the MZT in natural populations of D. melanogaster gives insight into the extent of how a tightly regulated process may vary within a species, the extent of developmental constraint at both stages and on both the maternal and zygotic genomes, and reveals expression changes allowing this species to adapt as it spread across the world.

evolutionary biology↗

bioRxiv2019

SLM-Transform: A Method for Memory-Efficient Indexing of Spectra for Database Search in LC-MS/MS Proteomics

The most commonly used strategy for peptide identification in shotgun LC-MS/MS proteomics involves searching of MS/MS data against an in-silico digested protein sequence database. Typically, the digested peptide sequences are indexed into the memory to allow faster search times. However, subjecting a database to post-translational modifications (PTMs) during digestion results in an exponential increase in the number of peptides and therefore memory consumption. This limits the usage of existing fragment-ion based open-search algorithms for databases with several PTMs. In this paper, we propose a novel fragment-ion indexing technique which is analogous to suffix array transformation and allows constant time querying of indexed ions. We extend our transformation method, called SLM-Transform, by constructing ion buckets that allow querying of all indexed ions by mass by only storing information on distribution of ion-frequencies within buckets. The stored information is used with a regression technique to locate the position of ions in constant time. Moreover, the number of theoretical b- and y-ions generated and indexed for each theoretical spectrum are limited. Our results show that SLM-Transform allows indexing of up to 4x peptides than other leading fragment-ion based database search tools within the same memory constraints. We show that SLM-Transform based index allows indexing of over 83 million peptides within 26GB RAM as compared to 80GB required by MSFragger. Finally, we show the constant ion retrieval time for SLM-Transform based index allowing ultrafast peptide search speeds. Source code will be made available at: https://github.com/pcdslab/slmindex

bioinformatics↗