Biology subjects

Moufarrej, M. N.

Publications and source records attributed to Moufarrej, M. N..

5 recordsLinked to original sources

bioRxiv2026

3D imaging of the pregnant uterus reveals an extensively invasive mouse placenta requiring CXCL12-CXCR4 signaling

Successful pregnancy requires exquisite balance: the placenta must invade just enough to access maternal blood but not so deep it remains attached at birth. Disrupting this balance causes life-threatening pregnancy complications, for which treatments remain limited. Animal models are desperately needed to discover mechanisms underlying balanced uteroplacental development and how pregnancy complications arise, but this is hampered by the view that mouse placentation lacks human characteristics such as extensive trophoblast invasion and targeting of uterine spiral arteries. Here, we utilize 3D imaging, mouse genetics, and pharmacological perturbations to demonstrate that: (1) The mouse placenta invades more extensively than previously recognized with most spiral arteries heavily enveloped by fetal trophoblasts, (2) This process is disrupted without CXCL12-CXCR4 signaling specifically during early pregnancy, and (3) Disrupting early uteroplacental development ultimately results in excessively deep trophoblast invasion, closely mimicking the pregnancy complication placenta accreta. Mechanistically, uterine epithelium, stroma, and arteries activate CXCR4 signaling in early pregnancy, and inhibition causes decidualization failure, followed by dissolution of spiral artery development. Trophoblasts consequently migrate deep into uterine muscle and its arteries, reproducing hallmarks of human accreta. Thus, with 3D imaging, the mouse more effectively models human uteroplacental development and defines an early etiological window for intervention.

developmental biology↗

bioRxiv2025

Cell-free RNA reveals host and microbial correlates of broadly neutralizing antibody development against HIV

A small number of people living with HIV (PLWH) develop broadly neutralizing antibodies (bNAbs) targeting multiple HIV strains. Although several viral and immune factors contribute to bNAb development, the genetic and environmental factors driving this response remain largely unknown. We performed combined cell-free DNA (cfDNA) and cell-free RNA (cfRNA) sequencing in 42 plasma samples from a longitudinal cohort of 14 PLWH (7 who develop bNAbs and 7 matched controls). This approach enabled us to non-invasively monitor the host transcriptome, viral genetic variation, and microbiome composition during HIV infection, and to identify molecular correlates of bNAb development. We find that development of bNAbs is associated with a transcriptomic signature of early immune activation characterized by elevated levels of MHC class I antigen presentation genes. This signature is independent of viral load or CD4 count and declines over time. In addition to host features, we recovered sufficient viral reads to reconstruct HIV consensus sequences, supporting the utility of cfRNA for viral genotyping. Finally, we also identified an enrichment of several microbial taxa in bNAb producers and increased levels of GB virus C (GBV-C), a non-pathogenic lymphotropic virus. Our findings suggest a distinct early immune activation profile in PLWH who develop bNAbs. More broadly, we show that combined cfDNA/cfRNA sequencing can reveal relationships between a protective immunogenic response to HIV infection, the host immune system, and microbiome, highlighting its potential for biomarker discovery in future vaccine and therapeutic studies. Author SummaryA subset of people living with HIV develop broadly neutralizing antibodies (bNAbs), a phenomenon that remains poorly understood but relevant to vaccine development. We applied combined cell-free RNA and DNA sequencing to 42 longitudinal plasma samples (7 bNAb producers, 7 controls) to monitor the host transcriptome, viral variation, and microbiome composition during bNAb development. Early in infection, bNAb producers showed an MHC class I-linked immune activation signature that declined over time, alongside changes in commensal microbial sequences and increased levels of GB virus C in cfRNA. These findings support the use of cfDNA/cfRNA sequencing for biomarker discovery in HIV research.

genomics↗

bioRxiv2021

Cell Types of Origin in the Cell Free Transcriptome in Human Health and Disease

Cell-free RNA (cfRNA) can be used to noninvasively measure dynamic and longitudinal physiological changes throughout the body. While there is considerable effort in the liquid biopsy field to determine disease tissue-of-origin, pathophysiology occurs at the cellular level. Here, we describe two approaches to identify cell type contributions to cfRNA. First we used Tabula Sapiens, a transcriptomic cell atlas of the human body to computationally deconvolve the cell-free transcriptome into a sum of cell type specific transcriptomes, thus revealing the spectrum of cell types readily detectable in the blood. Second, we used individual tissue transcriptomic cell atlases in combination with the Human Protein Atlas RNA consensus dataset to create cell type signature scores which can be used to infer the implicated cell types from cfRNA for a variety of diseases. Taken together, these results demonstrate that cfRNA reflects cellular contributions in health and disease from diverse cell types, potentially enabling determination of pathophysiological changes of many cell types from a single blood test.

systems biology↗

bioRxiv2020

An inexpensive semi-automated sample processing pipeline for cell-free RNA

Despite advances in automated liquid handling and microfluidics, preparing samples for RNA sequencing at scale generally requires expensive equipment, which is beyond the reach of many academic labs. Manual sample preparation remains a slow, expensive, and error-prone process. Here, we describe a low-cost, semi-automated pipeline to extract cell-free RNA (cfRNA) that like many RNA isolation protocols, can be decomposed into three subparts - RNA extraction, DNA digestion, and RNA cleaning and concentration. RT-qPCR data using a synthetic spike-in confirms comparable RNA quality as compared to manual sample processing, the gold-standard used in our prior work. The semi-automated pipeline also shows striking improvement in sample throughput (+12x), time spent (-11x), cost (-3x), and biohazardous waste produced (-4x) as compared to its manual counterpart. In total, this protocol enables cfRNA extraction from 96 samples simultaneously in 4.5 hours; in practice, this dramatically improves time to results as demonstrated in our recent work [1] where it was used to process 404 samples in 27 hours. Importantly, any lab already has most of the parts required (manual pipette, corresponding tips and kits) to build a semi-automated sample processing pipeline of their own and would only need to purchase or 3D-print a few extra parts ($5.5K total). This pipeline is also generalizable for many nucleic acid extraction applications, thereby increasing the scale of studies, which can be performed in small research labs.

bioengineering↗

bioRxiv2017

A Noninvasive Molecular Clock for Fetal Development Predicts Gestational Age and Preterm Delivery

We performed a high time-resolution, longitudinal study of normal pregnancy development by measuring cell-free RNA (cfRNA) in blood from women during each week of pregnancy. Analysis of tissue-specific transcripts in these samples enabled us to follow fetal and placental development with high resolution and sensitivity, and also to detect gene-specific responses of the maternal immune system to pregnancy. We established a \"clock\" for normal pregnancy development and enabled a direct molecular approach to determine expected delivery dates with comparable accuracy to ultrasound, creating the basis for a portable, inexpensive fetal dating method. We also identified a related gene set that accurately discriminated women at risk for spontaneous preterm delivery up to two months in advance of labor, forming the basis of a potential screening test for risk of preterm delivery.

bioengineering↗