Biology subjects

Khan, M. F.

Publications and source records attributed to Khan, M. F..

6 recordsLinked to original sources

bioRxiv2025

Signal Attrition in Whole Cell Crosslinking Mass Spectrometry

Crosslinking mass spectrometry (XL-MS) could replace traditional techniques for sampling the cellular interactome, such as affinity pulldown MS. It generates superior interaction data that can be used to better model cellular structure and function. However, the sampling depth of current XL-MS techniques is disappointing. Poor sampling is often blamed on a low-yielding crosslinking reaction, estimated to be [~]0.1% based on relative ion abundance in the mass spectrometer. Here, using a new two-step crosslinker installation process, we demonstrate that the yield of the chemical reaction is not the limiting factor in sampling the interactome. Low crosslink detection levels persist even when crosslink yields approach 30% of total peptide. We show that crosslinked peptides are not preferentially lost during sample workup; they enter the mass spectrometer at least as efficiently as linear peptides. Low detection rates arise mostly from severe signal splitting that reduces the S/N of crosslinked peptides, which is likely exacerbated by low-sensitivity database search tools and compounded by ion suppression.

biochemistry↗

bioRxiv2024

SingleFrag: A deep learning tool for MS/MS fragment and spectral prediction and metabolite annotation

Metabolite and small molecule identification via MS/MS involves matching experimental spectra with prerecorded spectra of known compounds. This process is hindered by the current lack of comprehensive reference spectral libraries. To address this gap, we need accurate in silico fragmentation tools for predicting MS/MS spectra of compounds for which empirical spectra do not exist. Here, we present SingleFrag, a novel deep learning tool that predicts individual fragments separately, rather than attempting to predict the entire fragmentation spectrum at once. Our results demonstrate that SingleFrag surpasses state-of-the-art in silico fragmentation tools, providing a powerful method for annotating unknown MS/MS spectra of known compounds. As a proof of concept, we successfully annotate three previously unidentified compounds frequently found in human samples.

bioinformatics↗

bioRxiv2023

CD1d-dependent neuroinflammation impairs tissue repair and functional recovery following a spinal cord injury

Tissue damage resulting from a spinal cord injury (SCI) is primarily driven by a robust neuroimmune/neuroinflammatory response. This intricate process is mainly governed by a multitude of cytokines and cell surface proteins in the central nervous system (CNS). However, the critical components of the neuroimmune/neuroinflammatory response during SCI are still not well-defined. In this study, we investigated the impact of CD1d, an MHC class I-like molecule mostly known for presenting lipid antigens to natural killer T (NKT) cells and regulating immune/inflammatory responses, on neuroimmune/neuroinflammatory responses induced by SCI. We observed an increased expression of CD1d on various cell types within the spinal cord, including microglia/macrophages, oligodendrocytes (ODCs), and endothelial cells (DCs), but not on neurons or astrocytes post-SCI. In comparison to wildtype (WT) mice, a T10 contusive SCI in CD1d knockout (CD1dKO or Cd1d-/-) mice resulted in markedly reduced proinflammatory cytokine release, microglia/macrophage activation and proliferation. Following SCI, the levels of inflammatory cytokines and activation/proliferation of microglia/macrophages were dramatically reduced, while anti-inflammatory cytokines such as IL-4 and growth factors like VEGF were substantially increased in the spinal cord tissues of CD1dKO mice when compared to WT mice. In the post-acute phase of SCI (day 7 post-SCI), CD1dKO mice had a significantly higher frequency of tissue-repairing macrophages, but not other types of immune cells, in the injured spinal cord tissues compared to WT mice. Moreover, CD1d-deficiency protected spinal cord neuronal cells and tissue, promoting functional recovery after a SCI. However, the neuroinflammation in WT mouse spinal cords was independent of the canonical CD1d/NKT cell axis. Finally, treatment of injured mice with a CD1d-specific monoclonal antibody significantly enhanced neuroprotection and improved functional recovery. Therefore, CD1d promotes the proinflammatory response following a SCI and represents a potential therapeutic target for spinal cord repair. Significance StatementThe cell surface molecule, CD1d, is known to be recognized by cells of the immune system. To our knowledge, this is the first observation that the CD1d molecule significantly contributes to neuroinflammation following a spinal cord injury (SCI) in a manner independent of the CD1d/NKT cell axis. This is important, because this work reveals CD1d as a potential therapeutic target following an acute SCI for which there are currently no effective treatments.

neuroscience↗

bioRxiv2023

Automating data analysis for hydrogen/deuterium exchange mass spectrometry using data-independent acquisition methodology

We developed a hydrogen/deuterium exchange workflow coupled to tandem mass spectrometry (HX-MS2) that supports the acquisition of peptide fragment ions alongside their peptide precursors. The approach enables true auto-validation of HX data by mining a rich set of deuterated fragments, generated by collisional-induced dissociation (CID), to simultaneously confirm the peptide ID and authenticate MS1-based deuteration calculations. The high redundancy provided by the fragments supports a confidence assessment of deuterium calculations using a combinatorial strategy. The approach requires data-independent acquisition (DIA) methods that are available on most MS platforms, making the switch to HX-MS2 straightforward. Importantly, we find that HX-DIA enables a proteomics-grade approach and wide-spread applications. Considerable time is saved through auto-validation and complex samples can now be characterized and at higher throughput. We illustrate these advantages in a drug binding analysis of the ultra-large protein kinase DNA-PKcs, isolated directly from mammalian cells.

biochemistry↗

bioRxiv2022

Habitat suitability modeling of Himalayan Monal and Koklass Pheasant in Western Himalayas and Hindukush, Pakistan

The Himalayan pheasants are under the greatest threat due to habitat degradation, and loss. Quantifying geographical range and suitable habitat of a species can help in better management and conservation decisions. Himalayan Monal (Lophophorus impejanus) and Koklass (Pucrasia macrolopha) are endemic to the Himalayas and Hindukush mountains. This study aims to investigate habitat suitability of these pheasants in the western Himalayas and Hindukush. MaxEnt and Cringing models were used to document habitat suitability and to identify valleys with most suitable habitat. MaxEnt model displayed excellent predictive performance showing a strong prediction of the probability distribution and habitat. The area under cover (AUC) values quantified for the replicate runs were 0.994 ({+/-}0.001) and 0.991 ({+/-}0.005) for Himalayan Monal and Koklass pheasant respectively. The climatic parameters including temperature, precipitation of the warmest quarter (bio_18) contributed the maximum 21.3% and 23.5%, followed by annual precipitation (bio_12) 12.3% and 8.9% for habitat prediction of Monal and Koklass. The topographical variables, altitude, slope, and distance to settlements contributed 15.2%, 2.6%, and 16% in the Monal habitat prediction model while 8.4%, 10.5%, and 15.8% for the Koklass habitat prediction model respectively. We quantified highly suitable (844.4 sq. km), moderately suitable (2819.42 sq. km), and less suitable (3933.09 sq. km) habitat for Monal pheasant. Whereas, highly suitable habitat for Koklass pheasant was (611.5 sq. km), followed by moderately suitable (2551.3 sq. km), and less suitable (4494.11 sq. km). Bar Palas region of Koli Palas district, Jalkot and Kandia valley of district upper Kohistan and Kayal valley of district lower Kohistan were identified as core zones or hot spots for these pheasant species. Areas identified as core zone/hotspot and suitable habitat for the pheasant species should be legally protected for the conservation of pheasants.

ecology↗

bioRxiv2019

Chikungunya Outbreak in Bangladesh (2017): Clinical and hematological findings

A massive outbreak of Chikungunya occurred in Bangladesh during the period of April-September, 2017 and over two million people were at risk of getting infected by the virus. A prospective cohort of viremic patients was constituted and analyzed to define the clinical, hematological and long-term aspects of this outbreak. A 35-day long comprehensive survey was conducted in two major, neighboring cities, Dhaka and Mymensingh. One-hundred and eighty-seven clinically proven Chikungunya cases were enrolled in the cross-sectional cohort study. Additionally, a smaller group of 48 Chikungunya patients was monitored for post-infection effects for 12 months. Clinical data revealed that a combination of fever and arthralgia (oligoarthralgia and/or polyarthralgia) was the cardinal hallmark (97.9% of cases) of the infection. Hematological analysis showed that, irrespective of age groups, hemoglobin level significantly decreased and erythrocyte sedimentation rate remarkably increased in Chikungunya confirmed patients. However, the majority of the patients had a normal range of whole WBC and platelet counts; RBC counts for mid aged (40 - 60 years) and senior (61+ years) patients (especially in the females) were beyond the reference values. The post-infection study revealed that children had an early recovery from the infection compared to the adults. Moreover, post-infection weakness, successive relapse of arthralgic pain and memory problems were the most significant aftereffects, which had an impact on daily activities of patients. This study represents a comprehensive overview of clinical and epidemiological features of the 2017 outbreak of Chikungunya in Bangladesh as well as its chronic outcomes till the 12th month. It provides insights into the natural history of this disease which may help to improve management of the Chikungunya patients.\n\nAuthor summeryThe clinical profile, epidemiology and the economic impacts during the acute phase of Chikungunya infection has been studied quite rigorously. However, studies regarding the hematological features and chronic consequences are very limited. In this study, a dataset of 187 clinically proven chikungunya patients were analyzed for the clinical and hematological features at acute phase of the infection. Additionally, the long-term consequences till month 12 after the infection were studied for a smaller group of 48 patients. Clinical data revealed that a combination of fever and joint pain (arthralgia) was the cardinal hallmark in the acute phase of the infection. Hematological analysis showed that, hemoglobin levels of the patients were significantly reduced and erythrocyte sedimentation rate increased remarkably. Also, RBC counts for mid-aged and older patients were beyond the reference values. The post-infection consequence study unveiled that children recovered better from the infection compared to the adults. Further, post-infection weakness, successive relapse of joint pain and memory problems were the most significant aftereffects. Overall, the infection had moderate to severe impact on daily activities of the respondents. This study provides insights into the clinical and hematological aspects of Chikungunya infection during the acute phase as well as describes an account for its chronic outcomes which puts forward to the knowledge for clinicians and epidemiologists regarding the infection diversity and to help improved patient management.

epidemiology↗