Biology subjects

Pandit, K.

Publications and source records attributed to Pandit, K..

3 recordsLinked to original sources

bioRxiv2026

Spatial proteomics on repurposed sequencers reveals early astrocytic remodeling in an ALS mouse model

Spatial proteomics can reveal how disease reshapes cells and their local environments, but extending these measurements across replicated tissue cohorts requires validated antibodies, consistent sample processing and integrated analysis. These requirements are particularly pressing in studies of amyotrophic lateral sclerosis (ALS), where pathology evolves unevenly across spinal-cord regions and disease stages. Here, we established an end-to-end spatial proteomics workflow linking a validated 28-antibody panel to automated fluorescence decoding and imaging on repurposed high-throughput sequencers, followed by multicycle image processing, cellular profiling and probabilistic spatial-neighborhood analysis. We applied it to 70 lumbar spinal-cord sections from nine SOD1-G93A and nine wild-type mice at presymptomatic, disease-onset and symptomatic stages. Spatial neighborhood analysis revealed that the environments surrounding motor neurons were already remodeled at disease onset. GFAP-high neighborhoods expanded in the ventral gray matter, with 43% of motor neurons embedded in these environments in SOD1-G93A mice, compared with 15% in wild-type mice. This early expansion preceded the later decline of non-reactive gray matter and detectable motor-neuron loss. The regional organization of the protein-defined changes shared features with neuronal and astrocytic patterns mapped by spatial transcriptomics in mouse and human ALS. This work enables spatial proteomics across replicated tissue cohorts and identifies localized remodeling of the environments around surviving motor neurons as an early feature of disease in the SOD1-G93A model.

neuroscience↗

bioRxiv2025

Real-Time Viability Assessment of Ex Vivo Mouse Kidneys for Transplant Applications Using Dynamic Optical Coherence Tomography

Kidney transplantation remains the preferred treatment for patients with end-stage kidney disease. However, the ongoing shortage of donor organs continues to limit the availability of transplant treatments. Existing evaluation methods, such as the kidney donor profile index (KDPI) and pre-transplant donor biopsy (PTDB), have various limitations, including low discriminative power, invasiveness, and sampling errors, which reduce their effectiveness in organ quality assessment and contribute to the risk of unnecessary organ discard. In this study, we explored the dynamic optical coherence tomography (DOCT) as a real-time, non-invasive approach to monitor the viability of ex vivo mouse kidneys during static cold storage over 48 hours. The dynamic metrics logarithmic intensity variance (LIV), early OCT correlation decay speed (OCDSe), and late OCT correlation decay speed (OCDSl) were extracted from OCT signal fluctuations to quantify temporal and spatial tissue activity and deterioration. Our results demonstrate that DOCT provides complementary functional information to morphological assessment offered by conventional OCT imaging, showing potential to improve pre-transplant organ evaluation and clinic decision-making.

bioengineering↗

bioRxiv2021

PySeq2500: An open source toolkit for repurposing HiSeq 2500 sequencing systems as versatile fluidics and imaging platforms.

Fluorescence microscopy is a key method in the life sciences. State of the art -omics methods combine fluorescence microscopy with complex protocols to visualize tens to thousands of features in each of millions of pixels across samples. These -omics methods require precise control of temperature, reagent application, and image acquisition parameters during iterative chemistry and imaging cycles conducted over the course of days or weeks. Automated execution of such methods enables robust and reproducible data generation. However, few commercial solutions exist for temperature controlled, fluidics coupled fluorescence imaging, and implementation of bespoke instrumentation requires specialized engineering expertise. Here we present PySeq2500, an open source Python code base and flow cell design that converts the Illumina HiSeq 2500 instrument into an open platform for programmable applications. Customizable PySeq2500 protocols enable experimental designs involving simultaneous 4-channel image acquisition, temperature control, reagent exchange, stable positioning, and sample integrity over extended experiments. To demonstrate accessible automation of complex, multi-day workflows, we use the PySeq2500 system for unattended execution of iterative indirect immunofluorescence imaging (4i). Our automated 4i method uses off-the-shelf antibodies over multiple cycles of staining, imaging, and antibody elution to build highly multiplexed maps of cell types and pathological features in mouse and postmortem human spinal cord sections. As demonstrated here, PySeq2500 enables non-specialists to develop and implement state of the art fluidics coupled imaging methods in a widely available benchtop system.

genomics↗