Biology subjects

Khan, T. A.

Publications and source records attributed to Khan, T. A..

9 recordsLinked to original sources

bioRxiv2026

A metabolic labelling-based lipid imaging technology establishes VPS13A as a phosphatidylethanolamine lipid transfer protein

The ability to image specific lipid subtypes within cells can have a transformative impact on the study of lipid dynamics and trafficking mechanisms. Herein, we describe a technology for imaging phosphatidylethanolamine (PE) lipids in live mammalian cells that involved screening a library of ethanolamine derivatives to identify an azido compound that efficiently metabolically labels PE. Crucially, this probe evades the cellular methylation machinery specifically labelling PE without forming labelled methylated PE and phosphatidylcholine (PC) lipids. The administration of cyclooctyne dyes to cells metabolically labelled with this probe rendered azido PE lipids fluorescent via strain-promoted click chemistry, enabling imaging. We employed this technology to image PE in various cellular organelles, visualize PE externalization during apoptosis, and discover that the VPS13A protein transports PE from the endoplasmic reticulum to the mitochondria. This technology will facilitate addressing fundamental questions in PE biology and studying dysregulation of PE dynamics and trafficking in disease states.

cell biology↗

bioRxiv2024

Next Generation Neuropeptide Y Receptor Small Molecule Agonists Inhibit Mosquito Biting Behavior

Female Aedes aegypti mosquitoes can spread disease-causing pathogens when they bite humans to obtain blood nutrients required for egg production. Following a complete blood meal, host-seeking is suppressed until eggs are laid. Neuropeptide Y-like Receptor 7 (NPYLR7) plays a role in endogenous host-seeking suppression and previous work identified small molecule NPYLR7 agonists that suppress host-seeking and blood feeding when fed to mosquitoes at high micromolar doses. Using structure activity relationship analysis and structure-guided design we synthesized 128 compounds with similarity to known NPYLR7 agonists. Although in vitro potency (EC50) was not strictly predictive of in vivo effect, we identified 3 compounds that suppressed blood feeding from a live host when fed to mosquitoes at a 1 M dose, a 100-fold improvement over the original reference compound. Exogenous activation of NPYLR7 represents an innovative vector control strategy to block mosquito biting behavior and prevent mosquito/human host interactions that lead to pathogen transmission.

pharmacology and toxicology↗

bioRxiv2024

DNA-Diffusion: Leveraging Generative Models for Controlling Chromatin Accessibility and Gene Expression via Synthetic Regulatory Elements

The challenge of systematically modifying and optimizing regulatory elements for precise gene expression control is central to modern genomics and synthetic biology. Advancements in generative AI have paved the way for designing synthetic sequences with the aim of safely and accurately modulating gene expression. We leverage diffusion models to design context-specific DNA regulatory sequences, which hold significant potential toward enabling novel therapeutic applications requiring precise modulation of gene expression. Our framework uses a cell type-specific diffusion model to generate synthetic 200 bp regulatory elements based on chromatin accessibility across different cell types. We evaluate the generated sequences based on key metrics to ensure they retain properties of endogenous sequences: transcription factor binding site composition, potential for cell type-specific chromatin accessibility, and capacity for sequences generated by DNA diffusion to activate gene expression in different cell contexts using state-of-the-art prediction models. Our results demonstrate the ability to robustly generate DNA sequences with cell type-specific regulatory potential. DNA-Diffusion paves the way for revolutionizing a regulatory modulation approach to mammalian synthetic biology and precision gene therapy.

synthetic biology↗

bioRxiv2023

Honey varietals differentially impact Bifidobacterium animalis ssp lactis survivability in yogurt through simulated in vitro digestion

BackgroundBifidobacterium animalis ssp. lactis DN-173 010/CNCM I-2494 (B. animalis) is a probiotic strain commonly added to yogurt. Yogurt and honey are a popular culinary pairing. Honey improves bifidobacteria survival in vitro. However, probiotic survival in yogurt with honey during in vitro digestion has not been investigated. ObjectiveThe study aimed to evaluate the effects of different honey varietals and concentrations on B. animalis survivability in yogurt through in vitro digestion. MethodsYogurt with honey or control-treated samples underwent in vitro simulated oral, gastric, and intestinal digestion. B. animalis cells were enumerated on MRS medium followed by an overlay with a modified selective MRS medium; all underwent anaerobic incubation. B. animalis were enumerated pre-digestion and after oral, gastric, and intestinal digestion. There were two study phases: phase 1 tested four honey varietals at 20% w/w per 170g yogurt, and phase 2 tested seven dosages of clover honey (20, 14, 10, 9, 8, 6, and 4% w/w) per 170g yogurt. ResultsSimilar B. animalis counts were observed between all treatments after oral and gastric digestion (<1 Log CFU/g probiotic reduction). Higher B. animalis survivability was observed in yogurt with clover honey after exposure to simulated intestinal fluids ([~]3.5 Log CFU/g reduction; P < 0.05) compared to all control treatments ([~]5.5 Log CFU/g reduction; P < 0.05). Yogurt with 10 to 20% w/w clover honey increased B. animalis survivability after simulated in vitro digestion (up to [~]4.7 Log CFU/g survival; P < 0.05). ConclusionYogurt with added honey improves probiotic survivability during in vitro digestion. The effective dose of clover honey in yogurt was 10 to 20% w/w per serving (1 - 2 tablespoons per 170g yogurt) for increased probiotic survivability during in vitro digestion.

microbiology↗

bioRxiv2023

Direct optical measurement of intra-molecular distances down to the Angstrom scale

Optical investigations of nanometer distances between proteins, their subunits, or other biomolecules have been the exclusive prerogative of Forster Resonance Energy Transfer (FRET) microscopy for decades. Here we show that MINFLUX fluorescence nanoscopy measures intra-molecular distances down to 1 nm - and in planar projections down to 1 Angstrom - directly, linearly, and with Angstrom precision. Our method is validated by quantifying well-characterized 1-to-10 nm distances in polypeptides and proteins. Moreover, we visualize the orientations of immunoglobulin subunits and reveal specific configurations of a histidine kinase domain dimer. Our results open the door for examining proximities and interactions of macromolecules under physiological conditions.

biophysics↗

bioRxiv2022

MINSTED nanoscopy enters the Angstrom localization range

We report all-optical, room-temperature localization of fluorophores with precision in the [A]ngstrom range. These precisions are attained in a STED microscope, by encircling the fluorophore with the low-intensity edge of the STED donut beam, while constantly increasing the absolute donut power. Individual fluorophores bound to a DNA strand are localized with{sigma} = 4.7 [A], corresponding to a fraction of the fluorophore size, with only 2,000 detected photons. MINSTED fluorescence nanoscopy with single-digit nanometer resolution is exemplified by imaging nuclear pore complexes and the distribution of nuclear lamin in mammalian cells labeled by transient DNA hybridization. Since our experiments yield a localization precision{sigma} = 2.3 [A], estimated for 10,000 detected photons, we anticipate that MINSTED will open up entirely new areas of application in the study of macromolecular complexes in cells.

biophysics↗

bioRxiv2020

Genetic models suggest single and multiple origins of dihydrofolate reductase mutations in Plasmodium vivax

Pyrimethamine was first introduced for the treatment of malaria in Asia and Africa during the early 1980s, replacing chloroquine, and has become the first line of drugs in many countries. In recent years, development of pyrimethamine resistance in Plasmodium vivax has become a barrier to effective malaria control strategies. Here, we describe the use of meta-barcoded deep amplicon sequencing technology to assess the evolutionary origin of pyrimethamine resistance by analysing the flanking region of dihydrofolate reductase (dhfr) locus. The genetic modelling suggests that 58R and 173L single mutants and 58R/117N double mutants are present on a single lineage; suggesting a single origin of these mutations. The triple mutants (57L/58R/117N, 58R/61M/117N and 58R/117N/173L) share the lineage of 58R/117N, suggesting a common origin. In contrast, the 117N mutant is present on two separate lineages suggesting that there are multiple origins of this mutation. We characterised the allele frequency of the P. vivax dhfr locus. Our results support the view that the single mutation of 117N and double mutations of 58R/117N arise commonly, whereas the single mutation of 173L and triple mutations of 57L/58R/117N, 58R/61M/117N and 58R/117N/173L are less common. Our work will help to inform mitigation strategies for pyrimethamine resistance in P. vivax.

genetics↗

bioRxiv2020

Convergent selection in antibody repertoires is revealed by deep learning

Adaptive immunity is driven by the ability of lymphocytes to undergo V(D)J recombination and generate a highly diverse set of immune receptors (B cell receptors/secreted antibodies and T cell receptors) and their subsequent clonal selection and expansion upon molecular recognition of foreign antigens. These principles lead to remarkable, unique and dynamic immune receptor repertoires1. Deep sequencing provides increasing evidence for the presence of commonly shared (convergent) receptors across individual organisms within one species2-4. Convergent selection of specific receptors towards various antigens offers one explanation for these findings. For example, single cases of convergence have been reported in antibody repertoires of viral infection or allergy5-8. Recent studies demonstrate that convergent selection of sequence motifs within T cell receptor (TCR) repertoires can be identified on an even wider scale9,10. Here we report that there is extensive convergent selection in antibody repertoires of mice for a range of protein antigens and immunization conditions. We employed a deep learning approach utilizing variational autoencoders (VAEs) to model the underlying process of B cell receptor (BCR) recombination and assume that the data generation follows a Gaussian mixture model (GMM) in latent space. This provides both a latent embedding and cluster labels that group similar sequences, thus enabling the discovery of a multitude of convergent, antigen-associated sequence patterns. Using a linear, one-versus-all support vector machine (SVM), we confirm that the identified sequence patterns are predictive of antigenic exposure and outperform predictions based on the occurrence of public clones. Recombinant expression of both natural and in silico-generated antibodies possessing convergent patterns confirms their binding specificity to target antigens. Our work highlights to which extent convergence in antibody repertoires can occur and shows how deep learning can be applied for immunodiagnostics and antibody discovery and engineering.

immunology↗

bioRxiv2019

Novel metabarcoded DNA sequencing tool for the detection of Plasmodium species in malaria positive patients

Various PCR based methods have been described for the diagnosis of malaria, but most depend on the use of Plasmodium species-specific probes and primers; hence only the tested species are identified and there is limited available data on the true circulating species diversity. Sensitive diagnostic tools and platforms for their use are needed to detect Plasmodium species in both clinical cases and asymptomatic infections that contribute to disease transmission. We have been recently developed for the first time a novel high throughput haemoprotobiome metabarcoded DNA sequencing method and applied it for the quantification of haemoprotozoan parasites (Theleria and Babesia) of livestock. Here, we describe a novel, high throughput method using an Illumina MiSeq platform to demonstrate the proportions of Plasmodium species in metabarcoded DNA samples derived from human malaria patients. Plasmodium falciparum and Plasmodium vivax positive control gDNA was used to prepare mock DNA pools of parasites to evaluate the detection threshold of the assay for each of the two species and to assess the accuracy of proportional quantification. We then applied the assay to malaria-positive human samples to show the species composition of Plasmodium communities in the Punjab province of Pakistan and in the Afghanistan-Pakistan tribal areas. The diagnostic performance of the deep amplicon sequencing method was compared to an immunochromatographic assay that is widely used in the region. Metabarcoded DNA sequencing showed better diagnostic performance, greatly increasing the estimated prevalence of Plasmodium infection. The next-generation sequencing method using metabarcoded DNA has potential applications in the diagnosis, surveillance, treatment, and control of Plasmodium infections, as well as to study the parasite biology.

genetics↗