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Buchauer, L.

Publications and source records attributed to Buchauer, L..

3 recordsLinked to original sources

Q4ddPCR (May the Fourth Be Precise): A Flexible, 4-Target Assay for High-Resolution HIV Reservoir Profiling

Precise and scalable quantification of the genetically intact HIV reservoir is critical for advancing curative strategies. However, current HIV reservoir assays such as the intact proviral DNA assay (IPDA) are limited by quantification failures or misclassification of defective proviral genomes due to HIV sequence heterogeneity. Q4ddPCR is a modular, droplet digital PCR assay that simultaneously targets four conserved regions in the HIV genome to improve specificity, reduce quantification gaps, and provide multi-layered readouts. We benchmarked Q4ddPCR against 3,650 near full-length proviral sequences from 13 virally suppressed people with HIV (PWH) generated by Q4PCR using the same primer/probe sets. Q4ddPCR enabled intact reservoir quantification in 95% of samples from three independent cohorts and closely matched sequence-confirmed Q4PCR reservoir measurements. In addition, multi-probe readouts revealed clonal intact reservoir dynamics that are not detectable by IPDA. In longitudinal samples from 42 participants over the first 4.5 years on antiretroviral therapy (ART), Q4ddPCR reported lower proviral frequencies and a steeper decline in intact proviral DNA compared to IPDA. Collectively, our findings confirm key predictions from mathematical modeling, demonstrating that multi-target assays provide greater specificity and more accurately capture the dynamics of the intact HIV reservoir.

immunology↗

A spatiotemporally resolved single cell atlas of the Plasmodium liver stage

Malaria infection involves an obligatory, yet clinically silent liver stage1,2. Hepatocytes operate in repeating units termed lobules, exhibiting heterogeneous gene expression patterns along the lobule axis3, but the effects of hepatocyte zonation on parasite development have not been molecularly explored. Here, we combine single-cell RNA sequencing4 and single-molecule transcript imaging5 to characterize the hosts and parasites temporal expression programs in a zonally-controlled manner for the rodent malaria parasite Plasmodium berghei ANKA. We identify differences in parasite gene expression in distinct zones, and a sub-population of periportally-biased hepatocytes that harbor abortive infections associated with parasitophorous vacuole breakdown. These abortive hepatocytes up-regulate immune recruitment and key signaling programs. They exhibit reduced levels of Plasmodium transcripts, perturbed parasite mRNA localization, and may give rise to progressively lower abundance of periportal infections. Our study provides a resource for understanding the liver stage of Plasmodium infection at high spatial resolution and highlights heterogeneous behavior of both the parasite and the host hepatocyte.

genomics↗

Exponential Growth of Glioblastoma In Vivo Driven by Rapidly Dividing and Outwardly Migrating Cancer Stem Cells

How overall tumor growth emerges from the properties of functionally heterogeneous tumor cell subpopulations is a fundamental question of cancer biology. Here we combined lineage tracing, continuous monitoring of tumor mass, proliferation assays and transcriptomics with mathematical modeling and statistical inference to dissect the growth of glioblastoma in mice. We found that tumors grow exponentially at the rate of symmetric divisions of brain tumor stem cells (BTSCs). Spatial modeling predicts, and data show, that BTSCs accumulate at the tumor rim rather than in the core. The physiological differentiation hierarchy downstream of BTSCs is preserved in mice and humans: transit amplifying progenitors give rise to terminally differentiated cells. Consistent with our quantification of the mechanisms underlying tumor growth, molecular data show elevated expression of cell cycle-and migration-related genes in BTSCs. Our systematic approach reveals fundamental properties of glioblastoma and may be transferable to the study of other animal models of cancer.

cancer biology↗