Biology subjects

Reddy, R.

Publications and source records attributed to Reddy, R..

At least 19 recordsLinked to original sources

bioRxiv2026

Caffeinated Coli: Inspiring the Next Generation of Scientists through Synthetic Biology

The Caffeinated Coli Educational Module brings inquiry-driven learning to high schools, introducing students to scientific research, synthetic biology, and genetic engineering. The module focuses on the exploration of a genetically engineered strain of E. coli modified to grow exclusively on caffeine and, as such, can be used as a measurement device to determine the amount of caffeine in a liquid or beverage. Students conduct two bioassay experiments using these bacteria. During this process, they learn to create cultures and then measure bacterial growth followed by calculating the caffeine concentrations of unknown samples using their own data. This flexible module contains five weeks of original lectures and student learning materials that follow Next Generation Science Standards (NGSS), allowing the content to be adapted for basic, intermediate, or advanced biology courses. Upon completion of the module, students and teachers expressed that the most memorable aspects of the module include collaboration with peers, hands-on learning of content, and the opportunity to interact with the professor/mentors through office hours. Already implemented in 8 Texas high schools over the past two academic years, our module inspires STEM learning while bringing 21st century biology research to new audiences.

scientific communication and education↗

bioRxiv2026

Patient-Derived Organoids Functionally Stratify Epithelial Ovarian Cancer into Clinically Relevant Chemotherapy Response Phenotypes

BackgroundOvarian cancer (OC) exhibits substantial heterogeneity in response to platinum-based chemotherapy, resulting in variable clinical outcomes and frequent recurrence. Current biomarkers, including serum CA-125 kinetics and BRCA mutational status, incompletely predict therapeutic response. We investigated whether patient-derived organoids (PDOs) could functionally stratify chemotherapy sensitivity and better reflect patient-specific clinical behaviour. MethodsTwenty patients with OC treated between January 2024 and May 2026 were included, from whom fourteen PDO lines were successfully established. Eight PDOs with robust low-passage expansion and comprehensive longitudinal follow-up underwent functional profiling against carboplatin, paclitaxel, olaparib, and doxorubicin. Drug responses were assessed using half-maximal inhibitory concentration (IC50) and area under the curve (AUC) analyses and integrated with radiological response, serum CA-125 kinetics, BRCA status, and progression-free survival (PFS). ResultsClinical outcomes varied considerably despite similar platinum-taxane regimens. Although post-treatment CA-125 reduction was associated with prolonged PFS, neither CA-125 kinetics nor BRCA mutational status consistently predicted therapeutic response. PDO-guided functional stratification segregated tumours into four clinically relevant platinum-taxane response phenotypes: dual-sensitive, platinum-sensitive/taxane-resistant, platinum-resistant/taxane-sensitive, and dual-resistant. These functional categories closely mirrored radiological response, CA-125 normalisation, and disease progression patterns. PDOs exhibiting low IC50 and AUC values were associated with durable clinical benefit, whereas resistant PDOs tracked with persistent disease and early recurrence. ConclusionsPDO-guided functional stratification captures clinically meaningful therapeutic heterogeneity in OC and complements conventional biomarkers by directly measuring tumour-specific drug susceptibility. Prospective integration of PDO testing may facilitate patient-specific therapeutic selection and support functional precision oncology approaches in ovarian cancer.

Cancer Biology↗

bioRxiv2026

Contrast-induced changes in chemical exchange saturation transfer MRI differentiate tumor progression from pseudoprogression

Tumor pseudo-progression (PsP) refers to an initial increase in tumor size or the appearance of new lesions. These pseudo-progressive lesions are predominantly composed of infiltrative inflammatory cells, such as macrophages. This phenomenon commonly occurs in patients undergoing radiation therapy or immunotherapy and typically indicates a positive treatment response. However, it often leads to premature treatment cessation due to misinterpretation as disease progression. Non-invasive imaging biomarkers capable of distinguishing pseudo-progression from true progression would greatly aid in treatment decision-making. In our preliminary study, we explored the potential of gadoterate meglumine (Gd-DOTA, a macrocyclic Gd-contrast) in combination with amine chemical-exchange saturation transfer (amine-CEST) imaging to differentiate tumor from radiation necrosis by assessing Gd-DOTA uptake by infiltrating immune cells, such as macrophages. To evaluate whether amine-CEST, in combination with Gd-DOTA, can differentiate macrophages from cancer cells, we incubated them with Gd-DOTA for 30 minutes. Subsequently, the cells were processed, and amine-CEST imaging was performed on a 9.4 Tesla preclinical scanner. Upon treatment with Gd-DOTA, we did not observe a significant change in amine-CEST contrast in F98 cells compared with untreated cells, whereas treated macrophages exhibited a marked decrease ([~]40%) in amine-CEST signal compared with untreated macrophages. This reduction in signal was attributed to the uptake of Gd-DOTA by macrophages, which notably shortened water T1 relaxation, thereby quenching the amine-CEST signal. Conversely, cancer cells showed no appreciable change in the amine-CEST signal, indicating no Gd-DOTA uptake. Furthermore, to validate that T1 shortening influences amine-CEST signal, cancer cells were also treated with manganese chloride (MnCl2) for 30 minutes. The uptake of MnCl2 by cancer cells similarly induced T1 shortening, as observed in macrophages, resulting in a decrease in the amine-CEST signal from these cells. Next, we performed the amin-CEST imaging on F98 tumor-bearing rats and radiation necrotic rats. Post-injection with Gd-DOTA showed no appreciable change in the amine-CEST contrast in the tumor-bearing rat, whereas a significant decrease in contrast was observed in the radiation necrotic rat. This further demonstrates that no change in the amine-CEST contrast in tumor-bearing rats is due to cancer cells failing to take up Gd-DOTA. The decrease in amine-CEST contrast in radiation-treated rats reflects the uptake of Gd-DOTA by macrophages infiltrating the radiation-necrotic regions. This straightforward imaging approach holds promise for clinical translation. It offers a novel method for characterizing pseudo-progressive lesions and monitoring diverse treatment responses in cancer patients using standard clinical scanners.

cancer biology↗

bioRxiv2026

Unsupervised anomaly detection for tumor delineation in a preclinical model of glioblastoma using CEST MRI

IntroductionGlioblastoma is characterized by heterogeneous tumor characteristics and infiltrative tumor boundaries, making accurate delineation difficult with extensive manual annotations. Chemical exchange saturation transfer (CEST) is a non-invasive MRI technique used for in vivo assessment of metabolic and macromolecular information through a Z-spectrum. CEST may provide insight into metabolic changes present in early-stage disease that are not visible in routine clinical imaging, thereby improving tumor delineation. In this work, we use an unsupervised anomaly detection (UAD) strategy to learn the distribution of features present in Z-spectra of healthy tissue and capture their deviations in pathology, foregoing the need for extensive labels. The approach leverages the metabolic information provided by CEST to improve the detection and delineation of glioblastoma and inform further treatment planning. MethodsA 1D convolutional autoencoder (CAE) was implemented to reconstruct Z-spectra from individual tissue voxels. The network was trained on Z-spectra acquired at 9.4T from healthy Sprague-Dawley rats and tested on data acquired from F98 glioma-bearing rats post Gd-administration. For baseline comparisons, Isolation Forest and Local Outlier Factor, which have shown success in anomaly detection, were implemented. For the CAE, our anomaly score was determined to be the mean squared reconstruction error. To facilitate clinical translation and evaluate the robustness of our model for under sampled Z-spectra, acceleration factors of 2x and 7x were performed with two sampling schemes: uniformly skipping frequency offsets and selecting offsets based on feature importance identified by Shapley value analysis and Integrated Gradients (IG). Binarization was performed by determining an optimal anomaly threshold, followed by comparison to ground truth tumor masks. Metrics related to model performance were assessed for baseline anomaly detectors on the fully sampled dataset and for the CAE on fully and under sampled datasets. ResultsThe best baseline anomaly detector was Isolation Forest, with an ROC-AUC of 0.967 and an F1-score of 0.584. Our method, the CAE, accurately reconstructed Z-spectral features, achieving Dice scores of up to 0.72 and outperforming the baseline model with an ROC-AUC of 0.968 and F1-score of 0.642. This model performance remained robust across sampling schemes and acceleration factors, with ROC-AUCs of [~]0.96 and similar Dice scores (up to 0.7). Feature importance analysis indicated that offsets in the range of {+/-}3.0 to 5.0ppm contributed most to the anomaly score. DiscussionThis study successfully demonstrated a UAD pipeline utilizing the Z-spectrum from CEST MRI for metabolically informed tumor delineation. The framework captures biochemical deviations that may precede or extend beyond morphologic abnormalities, enabling sensitive detection of tumor regions and intra-tumoral heterogeneity that previous methods may fail to capture. The offsets from the feature analysis indicated a strong contribution from the magnetization transfer (MT) pool to the spectral deviations captured by the model, with additional contributions from relayed nuclear Overhauser effect (rNOE) and amide proton transfer (APT). Model robustness with under sampling further highlights the pipelines potential in accelerated acquisitions, thus improving clinical practicality. While there is a need for validation on larger cohorts and clinical datasets, the current results demonstrate that this label-free, Z-spectral anomaly mapping can serve as an interpretable and scalable tool for monitoring tumor heterogeneity and progression, with potential applicability to other diffuse or metabolically subtle pathologies.

cancer biology↗

bioRxiv2026

Diversified Portfolios of Bacterial Communities in Peri-urban Miyawaki Forests and Grassland Shaping Ecosystem Functions and Services

Soil microflora is fundamental to ecosystem functioning, yet their contribution in Miyawaki afforestation, a globally implemented ecological engineering approach, remains poorly characterized. In the present study, we examined the bacterial taxonomic diversity and their functional potential in a peri-urban Miyawaki mini-forest and compared with a nearby grassland the pre-existing ecosystem across dry and wet seasons. The Miyawaki plantation comprised of highly diverse native trees, sub-trees and shrubs spanning evergreen and deciduous varieties, potentiating nitrogen-fixation, diverse litter generation and rooting strategies resulting in pronounced functional heterogeneity. Notably relative to grassland, the Miyawaki forest was intensively managed and supplemented with organic amendments, and supportive irrigation, buffering the seasonal moisture stress. Using 16S rRNA amplicon sequencing of soil eDNA, we characterized seasonal variation in soil bacterial communities in both the systems. The observed soil bacterial community organization in forest as compared to the unmanaged grassland indicates combined influence of vegetation structure, dense canopy cover, continuous litter generation and root exudates. Microbial assemblages in the forest specialised in heterotrophic complex carbon degradation, biofilm formation, exopolysaccharide production and sporulation pathways which suggests adaptive abilities to anoxic microsites and other stressful conditions. In contrast, grassland soils harboured less diversified bacterial communities dominated by phototrophic and oxidative stress adaptation pathways consistent with sun lit, non-irrigated and moisture-variable conditions. Nonetheless, functional divergence in dry season reflects temporal reorganization of microbial communities marking a gradual trend towards soil ecosystem development. Together, these findings establish microbial baseline for Miyawaki forests revealing how tree-dense mini-forests restructure soil bacterial communities relative to grasslands highlighting the value of identifying soil microbial indicators for critically evaluating urban afforestation outcomes over extended time scales to inform sustainable design and policy. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/704982v1_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@15e1bb1org.highwire.dtl.DTLVardef@16c1dddorg.highwire.dtl.DTLVardef@11c99ecorg.highwire.dtl.DTLVardef@bd6d1d_HPS_FORMAT_FIGEXP M_FIG C_FIG Schematic representation of the study depicting the Miyawaki forest and nearby grassland.

ecology↗

bioRxiv2025

Targeting ALC1 can safely expand the therapeutic utility of PARP inhibitors across high-grade serous ovarian cancers

Poly (ADP-ribose) polymerase inhibitors (PARPi) are approved for homologous recombination-deficient (HRD) high-grade serous ovarian cancers (HGSOCs), but their long-term effectiveness is limited by the emergence of resistance and hematological toxicity. Moreover, PARPi are largely ineffective in HR-proficient HGSOCs, particularly tumors with CCNE1 amplification, which exhibit marked therapeutic resistance and currently lack effective treatment options. Loss of a chromatin remodeling enzyme, Amplified in Liver Cancer 1 (ALC1), has been shown to enhance PARPi sensitivity. However, the clinical contexts in which ALC1 targeting will be clinically meaningful remain elusive. Here we demonstrate that ALC1 loss enhances PARPi sensitivity across HRD and CCNE1-amplified serous ovarian cancer lines, xenograft and patient-derived cells. ALC1 depletion can overcome clinically relevant mechanisms of PARPi resistance while having minimal effects in BRCA-wild-type or heterozygous non-cancerous cells. Consistent with this therapeutic safety, PARPi sensitivity upon ALC1 loss can be reliably predicted by the endogenous levels of phospho-T21 RPA2, a marker for replication stress which is typically higher in ovarian cancer cells compared to their normal counterparts. Together, our studies define the clinical contexts in which the therapeutic utility of PARPi can be expanded by targeting ALC1, whose inhibitors are currently in Phase I clinical trials.

cancer biology↗

bioRxiv2025

Cannabis Use and Glutamate across the Psychosis Spectrum: In Vivo Evidence from 7T Proton Magnetic Resonance Spectroscopy

Cannabis use is linked to elevated psychosis risk, yet the neurobiological mechanisms that couple use to symptom expression remain unclear. Because glutamatergic dysregulation has been implicated in both cannabis effects and psychosis vulnerability, we examined whether brain glutamate relates to dimensional symptoms as a function of cannabis use across the psychosis spectrum. Seventy-nine participants--typically developing controls, clinical high-risk individuals, and patients with psychosis--completed dimensional clinical assessments, detailed cannabis surveys, urine toxicology, and ultra-high-field 7T 1HMRS quantification of anterior cingulate cortex (ACC) glutamate levels. Linear models assessed the main and interactive effects of ACC glutamate and cannabis use on positive and negative symptoms. Self-reported cannabis use showed strong concordance with urine toxicology. Cannabis use was associated with higher positive and negative symptoms. Independently, higher ACC glutamate predicted greater positive and negative symptoms. Notably, lower glutamate levels were associated with higher positive symptoms in cannabis users. Exploratory analyses suggested interactions for depressive and manic symptoms, indicating that glutamatergic abnormalities may amplify the overall severity of cannabis-related symptoms. Sensitivity analyses revealed lower ACC glutamate in psychosis patients--especially cannabis users--highlighting diagnostic group differences and reinforcing the link between cannabis exposure and glutamatergic dysfunction. These findings implicate ACC glutamatergic dysfunction as a transdiagnostic correlate of symptom burden, particularly in those with psychosis who are cannabis users. Glutamate-targeted interventions and longitudinal designs will be needed to examine causal pathways linking cannabis exposure to psychosis-relevant outcomes.

neuroscience↗

bioRxiv2025

Multimodal MR Imaging for quantification of brain lipid in mice at 9.4T

BackgroundAdvanced MR imaging techniques like steady state Nuclear Overhauser enhancement (ssNOE), transient NOE (tNOE), and myelin water fraction (MWF) provide a non-invasive way to assess the biochemical and structural integrity of brain tissue. Their sensitivity to endogenous lipids and macromolecules allows for the early detection of neuropathological changes, making them valuable tools in studying brain health and disease progression. In this study, we systematically evaluate the repeatability and sensitivity of NOEMTR, tNOE, and MWF for quantifying lipid and myelin content in the brains of wild-type (WT) mice, correlating the results with immunohistochemistry (IHC). MethodsFive 6-month-old C57BL6/J mice were imaged using 3D-NOE, and four mice underwent imaging with 2D tNOE and MWF across four repeated sessions using a 9.4T Scanner. For ssNOE imaging, CEST-weighted images at 56 frequency offsets were acquired using B1rms of 1.0 T and 3s saturation duration. For tNOE, 52 offsets were acquired with a hyperbolic secant inversion pulse (bandwidth = 400Hz, duration = 44ms) and a mixing time of 200ms. For MWF, a multi-echo spin-echo (MESE) sequence was acquired with 40 evenly spaced echoes from 5.5ms to 200ms. For both ssNOE and tNOE, B0 correction was performed using WASSR. Repeatability was quantified using intra- and inter-subject coefficients of variation (COV%). Pearson correlation was performed to see the association between imaging matrices and IHC measures, Luxol fast blue (LFB) stained sections, and myelin basic protein (MBP). ResultsAll techniques demonstrated high repeatability across the whole brain (WB) and selected regions of interest (ROIs). Whole-brain intra-subject COV% for NOEMTR ranged from 1.92% to 3.40%, with corresponding inter-subject COVs of 1.50%. tNOE exhibited improved intra-subject repeatability with COVs ranging from 0.75% to 5.57%, but a reduced inter-subject COV of 2.97%. MWF imaging showed the highest stability overall, with an intra-subject COV ranging from 0.47% to 2.03% and an inter-subject COV of 0.75%. Visually, tNOE offers superior contrast in myelin-rich areas compared to NOEMTR and MWF imaging, showing greater sensitivity to myelinated regions. tNOE strongly correlates with histological markers: r = 0.83 with MBP staining and r = 0.72 with LFB staining (both p < 0.001). MWF and NOEMTR showed correlations with MBP (r = 0.63 and r = 0.57, respectively). ConclusionNOEMTR, tNOE, and MWF imaging are reliable and repeatable methods for quantifying macromolecules in the brain. Among these, tNOE emerges as the most sensitive for detecting myelin lipids as confirmed by histological validation. These findings highlight the translational potential of tNOE for studying demyelinating disorders and neurodegenerative diseases.

neuroscience↗

bioRxiv2025

Ultrabright NIR-II Nanoprobes for Ex Vivo Bioimaging: Protein Nanoengineering Meets Molecular Engineering

Near-infrared (NIR) fluorescence imaging is a powerful, non-invasive tool for cancer diagnosis, enabling real-time, high-resolution visualization of biological systems. While most probes target the first NIR window (NIR-I, 750-950 nm), recent advances focus on the second window (NIR-II, 1000-1700 nm), which offers deeper tissue penetration and reduced interferences from scattering and autofluorescence. However, many current NIR-II nanoprobes show suboptimal brightness and limited validations in more human-centric models. Here, we present an orthogonal strategy combining molecular engineering, by modulating the amount and position of thiophene moieties in semiconducting polymers (SPs), with protein nanoengineering to develop ultrabright NIR-II imaging probes optimized for ex vivo bioimaging in large animal models. The molecular tuning amplifies the NIR-II fluorescence brightness while screening endogenous proteins as encapsulating matrices to improve colloidal stability and enable active targeting. Molecular docking identified bovine serum albumin as the effective candidate, and the resulting protein-complexed nanoprobes were characterized for size, colloidal stability under physiological conditions, and optical performances. Imaging performances were evaluated using tumor-mimicking phantoms in porcine lungs, simulating cancer surgery, and injected at clinically relevant concentrations into ovine brains and porcine ovaries for microvascular visualization and tissue discrimination, respectively. In all scenarios, our protein-complexed nanoprobes outperformed the FDA-approved clinical dye indocyanine green in signal-to-background ratios. Initial in vitro assays confirmed their hemocompatibility, biocompatibility, and cellular uptake in ovarian adenocarcinoma cells. This integrated approach offers a promising platform for developing next-generation ultrabright NIR-II nanoprobes with improved brightness and stability, advancing the potential for image-guided surgery and future clinical translation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=91 SRC="FIGDIR/small/665782v2_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@c8a20org.highwire.dtl.DTLVardef@1403bedorg.highwire.dtl.DTLVardef@1e474corg.highwire.dtl.DTLVardef@1daed69_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2025

Evaluation of Multiplexed Liquid Glycan Array (LiGA) for Serological Detection of Glycan-binding Antibodies

We test the performance of the multiplexed liquid glycan array (LiGA) technology in serological assays. Specifically, we use LiGA to detect ABO blood group antibodies in human serum. This LiGA, which we name ABO-LiGA, contains ABO blood group trisaccharide glycans with an ethylazido aglycone conjugated to groups of ten multi-barcoded M13 particles carrying dibenzocyclooctyne (DBCO) on p8 proteins. ELISA clonal binding assays to anti-A/B antibodies confirmed the functional performance of ABO-clones and aligned with next-generation sequencing (NGS) of the mixed clones. Multiple DNA-barcoded technical replicates in LiGA allow for quantification of reproducibility and robustness as determined by the Z-score using NGS. We then tested ABO-LiGA for specific detection of IgG and IgM anti-A and anti-B IgG and IgM antibodies in human serum samples. Comparison of antibody binding responses in sera from 31 healthy donors to ABO-LiGA with an ABO-Luminex-based method revealed consistent responses to LiGA-ABO but also minor deficiencies of ABO-LiGA such as low robustness of the current assay format and a limited ability to detect low intensity antibody responses. Some results point to undesired interactions of serum antibodies with small-footprint glycans conjugated to phage via the bulky DBCO moiety. This report illuminates the path for future development of LiGA-based serological assays and suggests the need to develop alternative methods for conjugating glycans to phage to avoid liabilities of the hydrophobic DBCO moiety.

biochemistry↗

bioRxiv2025

Magnetic Resonance Imaging for Improved Brain Tumor Detection

Precise demarcation of brain tumor boundaries is critical for optimizing treatment strategies and improving patient outcomes. In vivo characterization of tumor using PET/CT and MRI is clinical standard. PET/CT highlights the metabolic aspects of the tumor, while MRI provides information on functional, metabolic and structural changes. Even with technological advancements in both PET/CT and MRI, a method that can precisely delineate infiltrative tumor boundaries from normal-appearing brain regions (NABR) in vivo is still lacking. To address this limitation, we explored a relatively new MR imaging method, the Nuclear Overhauser Effect Magnetization Transfer Ratio (NOEMTR), in conjunction with a gadolinium-based contrast agent (Gd-DOTA), to precisely delineate the tumor boundaries in a rat model of infiltrative gliosarcoma. NOEMTR imaging was performed in the rat model (n=5) before and after Gd-DOTA administration. The post-Gd-DOTA NOEMTR map was subtracted from the pre-Gd-DOTA map and compared with contrast-enhanced T1-weighted images and immuno-histological findings. The resulting NOEMTR difference map clearly highlighted both the tumor core and infiltrative boundaries, which was not discernible on the post-contrast T1-weighted images. The extended tumor boundaries observed on the NOEMTR difference map corroborated with the IHC image, which confirmed the presence of infiltrative tumor cells and macrophages in these regions. Guided by the NOEMTR difference map, regions of interest (ROI) were drawn to quantify NOEMTR signal changes in the tumor core, tumor boundaries, and NABR post-Gd-DOTA. Tumor core showed a significant [~]43% reduction in NOEMTR signal (plJ=lJ0.003), while the tumor periphery exhibited a moderate reduction of [~]10%, (plJ=lJ0.045). No appreciable change in was observed in the NABR (plJ=lJ0.371). In contrast, the post contrast T1-weighted signal changes in tumor core, tumor periphery and NABR were, 33.32% (p = 0.092), 3.8% (p = 0.478), and 8.7% (p = 0.464) respectively. These findings suggest that NOEMTR imaging provides enhanced tumor contrast, particularly at the infiltrative tumor margins, where conventional contrast enhanced T1-weighted MRI may underestimate tumor extent. Histological validation confirmed the presence of infiltrative tumor cells and macrophages in the tumor periphery, as highlighted by the NOEMTR difference map. Overall, NOEMTR imaging, in combination with Gd-DOTA administration, demonstrates superior delineation of brain tumor boundaries compared to conventional MRI. As NOEMTR imaging is a fast acquisition scan (under 10 minutes) and performed on standard 3 Tesla, it can be easily integrated into clinical protocols. By improving visualization of tumor infiltration and distinguishing tumor regions from NABR, NOEMTR imaging holds promise for advancing neuro-oncological diagnostics and treatment planning.

bioengineering↗

bioRxiv2024

CCT-217: A Landmark Gene Silencing Therapeutic for Weight Loss That Enhances Lean Mass Composition, Reduces Visceral, Subcutaneous Fat and Restores Metabolic Health in Obesity through Browning

According to the CDC, between 2017 and March 2020, 41.9% of U.S. adults aged 20 and older had obesity, with 9.2% experiencing severe obesity, affecting over 100 million and 22 million adults, respectively. Obesity prevalence increased from 30.5% in 1999-2000 to 41.9% in 2017-2020, while severe obesity rose from 4.7% to 9.2%. As per CDC projection, by 2030, nearly half of the US adults will be obese, with a quarter of them being severely obese. Current therapeutic approaches predominantly focus on appetite suppression and caloric restriction. This approach results in both fat mass and lean mass loss and thus compromises long term metabolic health. Preserving lean mass during weight loss is crucial. Remodeling of the white fat into beige fat through the process called browning offers a promising alternative to appetite suppression dependent weight loss, and complements with reduction of visceral fat, marrow adipose tissue, improve liver steatosis, enhancing insulin sensitivity, reduced cardiovascular risk and suppression of inflammation. Here, we present CCT-217, a groundbreaking siRNA therapy targeting CB1R and ZFP423 genes, with strong adipose tissue-specific tropism with nil brain and liver penetration in diet-induced obese (DIO) C57BL/6J male mice model (n=7 control, n=5 treated). Mice received 7 subcutaneous doses over 20 days (initial half-dose, followed by once after three days CB1R siRNA 2.0 mg/kg and ZFP423 siRNA 1.8 mg/kg dose). CCT-217 induced browning of the WAT and resulted in a significant 26% reduction in body weight with a modest 12% decrease in feed intake after the 4th dose, preserved normal clinical behavior and nutrition. Lean mass composition significantly improved to 79% versus 62% in controls, while total fat mass decreased by 43.5%. Notably, visceral fat depots, including retroperitoneal (59.4%), mesenteric (54.3%), and gonadal (42.0%) fat showed substantial reductions, alongside a reduction of 61.7% inguinal white adipose tissue (iWAT). Histological analysis revealed extensive browning of iWAT, reduced adipocyte size, and increased adipocyte count, indicating enhanced thermogenesis and adipose tissue remodeling. Liver pathology showed significant improvement, with reduced hepatocellular adipose vacuolation and the absence of fibrosis, inflammation, or macrophage infiltration, highlighting the hepatoprotective effects of CCT-217. Metabolic markers demonstrated a 20% reduction in plasma cholesterol and decreased systemic inflammation (21% reduction in CRP), accompanied by significantly improved leptin sensitivity and favorable trends in insulin sensitivity. Mechanistically, CCT-217 achieved 42-fold silencing of CB1R and 14.5-fold silencing of ZFP423 specifically in iWAT, with no off-target effects observed in liver or brain. In conclusion, CCT-217 emerges as a landmark therapy that effectively reduces visceral fat, enhances lean mass composition, and restores metabolic health through precise, tissue-specific gene silencing. These findings position CCT-217 as a transformative and highly promising next generation therapeutic for addressing obesity and its associated complications.

pharmacology and toxicology↗

bioRxiv2024

Quantification of NAD+ T1 and T2 relaxation times using downfield 1H MRS at 7 T in human brain in vivo

IntroductionThe purpose of this study was to use a single-slice spectrally-selective sequence to measure T1 and T2 relaxation times of NAD+ proton resonances in the downfield 1H MRS spectrum in human brain at 7 T in vivo and assess the propagation of relaxation time uncertainty in NAD+ quantification. MethodsDownfield spectra from 7 healthy volunteers were acquired at multiple echo times in all subjects to measure T2 relaxation, and saturation recovery data were to measure T1 relaxation. The downfield acquisition used a spectrally-selective 90{degrees} sinc pulse for excitation centered at 9.1 ppm with a bandwidth of 2 ppm, followed by a 180{degrees} spatially-selective Shinnar-Le Roux refocusing pulse for localization. For the multiple echo experiment, spectra were collected with echo times ranging from 13 to 33 ms. For the saturation recovery experiment, saturation was performed prior to excitation using the same spectrally-selective sinc pulse as was used for excitation. Saturation delay times (TS) ranged from 100 to 600 ms. Uncertainty propagation analysis was performed analytically and with Monte Carlo simulation. ResultsThe mean {+/-} standard deviation of T1 relaxation times of the H2, H6, and H4 protons were 152.7 {+/-} 16.6, 163.6 {+/-} 22.3, and 169.9 {+/-} 11.2 ms, respectively. The mean {+/-} standard deviation of T2 relaxation times of the H2, H6, and H4 protons were 32.5 {+/-} 7.0, 27.4 {+/-} 5.2, and 38.1 {+/-} 11.7 ms, respectively. The mean R2 of the H2 and H6 T1 fits were 0.98. The mean R2 of the H4 proton T1 fit was 0.96. The mean R2 of the T2 fits of the H2 and H4 proton resonances were 0.98, while the mean R2 of the T2 fits of the H4 proton was 0.93. The relative uncertainty in NAD+ concentration due to relaxation time uncertainty was 8.5%-11%. ConclusionUsing downfield spectrally-selective spectroscopy with single-slice localization, we found NAD+ T1 and T2 relaxation times to be approximately 162 ms and 32 ms respectively in the human brain in vivo at 7 T.

bioengineering↗

bioRxiv2023

Ketone supplementation dampens subjective and objective responses to alcohol in rats and humans

Previous preclinical and human studies have shown that high-fat ketogenic diet and ketone supplements (KS) are efficacious in reducing alcohol craving, alcohol consumption, and signs of alcohol withdrawal. However, the effects of KS on alcohol sensitivity are unknown. In this single-blind, cross-over study, 10 healthy participants (3 females) were administered a single, oral dose of a KS (25 g of ketones from D-{beta}-hydroxybutyric acid and R-1,3-butanediol) or placebo 30 min prior to an oral alcohol dose (0.25 g/kg for women; 0.31 g/kg for men). Assessments of breath alcohol concentration (BrAC) and blood alcohol levels (BAL) and responses on the Drug Effect Questionnaire were repeatedly obtained over 180 min after alcohol consumption. In a parallel preclinical study, 8 Wistar rats (4 females) received an oral gavage of KS (0.42 g ketones/kg), water, or the sweetener allulose (0.58 g/kg) followed 15 min later by an oral alcohol dose (0.8 g/kg). BAL were monitored for 240 min after alcohol exposure. In humans, the intake of KS prior to alcohol significantly blunted BrAC and BAL, reduced ratings of alcohol liking and wanting, and increased disliking for alcohol. In rats, KS reduced BAL more than either allulose or water. In conclusion, KS altered physiological and subjective responses to alcohol in both humans and rats and the effects were likely not mediated by the sweetener allulose present in the KS drink. Therefore, KS could potentially reduce the intoxicating and rewarding effects of alcohol and thus be a novel intervention for treating alcohol use disorder.

pharmacology and toxicology↗

bioRxiv2022

Metagenomic analysis unravels novel taxonomic differences in the uterine microbiome between healthy mares and mares with endometritis

The application of high throughput technologies has enabled unravelling of unique differences between healthy mares and mares with endometritis at transcriptomic and proteomic levels. However, differences in the uterine microbiome are yet to be investigated. The present study was aimed at evaluating the differences in uterine microbiome between healthy mares and mares with endometritis. Low-volume lavage (LVL) samples were collected from the uterus of 30 mares classified into healthy (n=15) and endometritis (n=15) based on their reproductive history, intrauterine fluid accumulation, gross appearance of LVL samples, endometrial cytology, and bacterial culture. The samples were subjected to metagenomic analysis using 16S rRNA sequencing. Notable differences in the uterine microbiome were observed between healthy mares and mares with endometritis at various taxonomic levels. In healthy mares, the most abundant phylum, class, order, and family were Firmicutes, Bacilli, Bacillales, and Paenibacillaceae, respectively. In contrast, the most abundant corresponding taxonomic levels in mares with endometritis were Proteobacteria, Gammaproteobacteria, Enterobacterales, and Enterobacteriaceae, respectively. At the genus level, Brevibacillus and Paenibacillus were more abundant in healthy mares, whereas Escherichia, Salmonella, and Klebsiella were more abundant in mares with endometritis. In healthy mares, Brevibacillus brevis was the most abundant species, followed by Brevibacillus choshinensis and Paenibacillus sp JDR-2. However, in mares with endometritis, Escherichia coli was the most abundant species, followed by Salmonella enterica and Klebsiella pneumoniae. These results indicate novel differences in the uterine microbiome between healthy mares and mares with endometritis. The findings can potentially help formulate new approaches to prevent or treat equine endometritis.

genomics↗

bioRxiv2022

Graph neural networks ameliorate potential impacts of imprecise large-scale autonomous immunofluorescence labeling of immune cells on whole slide images

The characteristics of tumor-infiltrating lymphocytes (TIL) are essential in cancer prognostication and treatment through the ability to indicate the tumors capacity to evade the immune system (e.g., as evidenced by nodal involvement). Machine learning technologies have demonstrated remarkable success for localizing TILs, though these methods require extensive curation of manual annotations or restaining procedures that can degrade tissue quality, resulting in imprecise annotation. In this study, we co-registered tissue slides stained for both hematoxylin and eosin (H&E) and immunofluorescence (IF) as means to rapidly perform large-scale annotation of nuclei. We integrated the following approaches to improve the prediction of TILs: 1) minimized tissue degradation on same-section tissue restaining, 2) developed a scoring algorithm to improve the selection of patches for machine learning modeling and 3) utilized a graph neural network deep learning approach to identify relevant contextual features for lymphocyte prediction. Our graph neural network approach accounts for surrounding contextual micro/macro-architecture tissue features to facilitate interpretation of registered IF. The graph neural network compares favorably (F1-score=0.9235, AUROC=0.9462) to two alternative modeling approaches. This study brings insight to the importance of contextual information leveraged from within and around neighboring cells in a nuclei classification workflow, as well as elucidate approaches which enable the rapid generation of large-scale annotations of lymphocytes for machine learning approaches for immune phenotyping. Such approaches can help further interrogate the spatial biology of colorectal cancer tumors and tumor metastasis.

pathology↗

bioRxiv2022

Spatial MIST Technology for Rapid, Highly Multiplexed Detection of Protein Distribution on Brain Tissue

Highly multiplexed analysis of biospecimens significantly advances the understanding of biological basics of diseases, but these techniques are limited by the number of multiplexity and the speed of processing. Here, we present a rapid multiplex method for quantitative detection of protein markers on brain sections with the cellular resolution. This spatial multiplex in situ tagging (MIST) technology is built upon a MIST microarray that contains millions of small microbeads carrying barcoded oligonucleotides. Using antibodies tagged with UV cleavable oligonucleotides, the distribution of protein markers on a tissue slice could be "printed" on the MIST microarray with high fidelity. The performance of this technology in detection sensitivity, resolution and signal-to-noise level has been fully characterized by detecting brain cell markers. We showcase the codetection of 31 proteins simultaneously within 2 h which is about 10 times faster than the other immunofluorescence-based approaches of similar multiplexity. A full set of computational toolkits was developed to segment the small regions and identify the regional differences across the entire mouse brain. This technique enables us to rapidly and conveniently detect dozens of biomarkers on a tissue specimen, and it can find broad applications in clinical pathology and disease mechanistic studies.

bioengineering↗

bioRxiv2022

Single-Cell Proteomics Study of Immune Cell Diversity by Quantitating 465 Proteins

The identification and characterization of T cell subpopulations is critical to reveal cell development throughout life and immune responses to environmental factors. Next-generation sequencing technologies have dramatically advanced the single-cell genomics and transcriptomics for T cell classification. However, gene expression is often not correlated with protein expression, and immunotyping is mostly accepted in the protein format. Current single-cell proteomics technologies are either limited in multiplex capacity or not sensitive enough to detect the critical functional proteins. Herein we present a cyclic multiplex in situ tagging (Cyclic MIST) technology to simultaneously measure 465 proteins, a scale of >10 times than similar technologies, in single cells. Such a high multiplexity is achieved by reiterative staining of the single cells coupled with a MIST array for detection. This technology has been thoroughly validated through comparison with flow cytometry and fluorescence immunostaining techniques. Both THP1 and CD4+ T cells are analyzed by the Cyclic MIST technology, and over 300 surface markers have been profiled to classify the subpopulations. This represents the most comprehensive mapping of the diversity of immune cells at the protein level. With additional information from intracellular proteins of the same single cells, our technology can potentially facilitate mechanistic studies of immune responses, particularly cytokine storm that results in sepsis.

bioengineering↗