bioRxiv Science⌕ Search

Biology subjects

Birgin, E.

Publications and source records attributed to Birgin, E..

4 recordsLinked to original sources

CD271 sorting for improved liver cell isolation: Semiautomated and simultaneous preparation of parenchymal and non-parenchymal cells from mouse and human livers

BackgroundA detailed understanding of the dynamic fate changes of hepatocytes, hepatic stellate cells (HSC), Kupffer cells (KC), and liver sinusoidal endothelial cells (LSEC) is critical for studying liver (patho)physiology during disease progression. Current isolation methods often focus on single cell types, limiting utility in comprehensive research. AimTo develop a novel, semi-automated protocol for the simultaneous isolation of hepatocytes and non-parenchymal cells (NPCs), including HSC, KC, and LSEC, from mouse and human, with high yield, purity, and viability from healthy and diseased livers. MethodThe protocol employs a two-step EGTA and collagenase II perfusion for tissue digestion. Hepatocytes were isolated by low-speed centrifugation and a Percoll gradient. Subsequently, magnetic-activated cell separation, using CD271 as a selective surface marker for HSC, CD11b for KC and CD146 for LSEC) was performed. Validation was achieved with immunofluorescence staining, flow cytometry, RT-PCR, and UV fluorescence, whereby yield, purity, and viability were assessed. ResultsWith our method, yield of hepatocytes, HSC, KC, and LSEC, is 33.4{+/-}5.5x10, 5.2{+/-}6.3x10, 12.4{+/-}4.8x10 and 18.2{+/-}8.9x10 cells per healthy mouse liver, respectively, with cell viabilities exceeding 89%, and purity surpassing 90%. CD271 was validated as an effective marker for purifying HSC in healthy and diseased human (n=4-6) and mouse livers. Compared to microfluidic and organ-on-a-chip approaches, with our protocol, we achieve higher yield and purity values while enabling the simultaneous isolation of multiple cell types from a single sample. ConclusionOur semi-automated protocol offers a scalable, reliable, and versatile solution for isolating main liver cell types with high yield, purity, and viability from both healthy and diseased tissues, advancing liver research and facilitating downstream investigations. Impact and implicationsO_LIBroad applicability: The CD271-based method efficiently isolates key liver cell types (Hepatocyte, HSC, KC, LSEC) simultaneously. C_LIO_LIVersatility in disease models: Effective for studying healthy, fibrotic, and damaged liver tissues. C_LIO_LIRobust across variability: Works reliably across different mouse strains, age groups, and conditions. C_LIO_LIHuman research potential: Scalable for high-purity isolation from human liver tissue, enabling translational studies. C_LIO_LIHigh-quality results: Ensures >85% viability and >90% purity, supporting reproducible liver research applications. C_LI

cell biology↗

Plectin-mediated cytoskeletal crosstalk as a target for inhibition of hepatocellular carcinoma growth and metastasis.

The most common primary malignancy of the liver, hepatocellular carcinoma (HCC), is a heterogeneous tumor entity with high metastatic potential and complex pathophysiology. Increasing evidence suggests that tissue mechanics plays a critical role in tumor onset and progression. Here we show that plectin, a major cytoskeletal crosslinker protein, plays a crucial role in mechanical homeostasis and mechanosensitive oncogenic signaling that drives hepatocarcinogenesis. Our expression analyses revealed elevated plectin levels in liver tumors, which correlated with poor prognosis for HCC patients. Using autochthonous and orthotopic mouse models we demonstrated that genetic and pharmacological inactivation of plectin potently suppressed the initiation and growth of HCC. Moreover, plectin targeting potently inhibited the invasion potential of human HCC cells and reduced their metastatic outgrowth in the lung. Proteomic and phosphoproteomic profiling linked plectin-dependent disruption of cytoskeletal networks to attenuation of oncogenic FAK, MAPK/Erk, and PI3K/AKT signatures. Importantly, by combining cell line-based and murine HCC models, we show that plectin inhibitor plecstatin-1 (PST) is well-tolerated and potently inhibits HCC progression. In conclusion, our study demonstrates that plectin-controlled cytoarchitecture is a key determinant of HCC development and suggests that pharmacologically induced disruption of mechanical homeostasis may represent a new therapeutic strategy for HCC treatment.

cancer biology↗

Spatial omics imaging of fresh-frozen tissue and routine FFPE histopathology on a single cancer needle core biopsy: freezing device and multimodal workflow

Complex molecular alterations underlying cancer pathophysiology are intensely studied with omics methods using bulk tissue extracts. For spatially resolved tissue diagnostics using needle biopsy cores, however, histopathological analysis using stained FFPE tissue and immuno-histochemistry (IHC) of few marker proteins is currently the main clinical focus. Today, spatial omics imaging using MSI or IRI are emerging diagnostic technologies for identification and classification of various cancer types. However, to conserve tissue-specific metabolomic states, fast, reliable and precise methods for preparation of fresh-frozen (FF) tissue sections are crucial. Such methods are often incompatible with clinical practice, since spatial metabolomics and routine histopathology of needle biopsies currently require two biopsies for FF and FFPE sampling, respectively. Therefore, we developed a device and corresponding laboratory and computational workflows for multimodal spatial omics analysis of fresh-frozen, longitudinally sectioned needle biopsies to accompany standard FFPE histopathology on the same biopsy core. As proof-of-concept, we analyzed surgical human liver cancer specimen by IRI and MSI with precise co-registration and, following FFPE processing, by sequential clinical pathology analysis on the same biopsy core. This workflow allowed spatial comparison between different spectral profiles and alterations in tissue histology, as well as direct comparison to histological diagnosis without the need of an extra biopsy. SIMPLE SUMMARYRoutine clinical approaches for cancer diagnosis demand fast, cost-efficient, and reliable methods, and their implementation within clinical settings. Currently, histopathology is the golden standard for tissue-based clinical diagnosis. Recently, spatially resolved molecular profiling techniques like mass spectrometry imaging (MSI) or infrared spectroscopy imaging (IRI) have increasingly contributed to clinical research, e.g., by differentiation of cancer subtypes using molecular fingerprints. However, adoption of the corresponding workflows in clinical routine remains challenging, especially for fresh-frozen tissue specimen. Here, we present a novel device based on 3D-printing technology, which facilitates sample preparation of needle biopsies for correlated clinical tissue analysis. It enables combination of MSI and IRI on fresh-frozen clinical samples with histopathological examination of the same needle core after formalin-fixation and paraffin-embedding (FFPE). This device and workflow can pave the way for a more profound understanding of biomolecular processes in cancer and, thus, aid more accurate diagnosis. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=180 SRC="FIGDIR/small/528125v1_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@1da99aborg.highwire.dtl.DTLVardef@9ee706org.highwire.dtl.DTLVardef@5153daorg.highwire.dtl.DTLVardef@1581594_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

Comparison of extraction methods for intracellular metabolomics

Measurements of metabolic compounds inside cells or tissues are of high informative potential since they represent the endpoint of biological information flow and a snapshot of the integration of many regulatory processes. However, it requires careful extraction to quantify their abundance. Here we present a comprehensive study using ten extraction protocols on four human sample types (liver tissue, bone marrow, HL60 and HEK cells) targeting 630 metabolites of different chemical classes. We show that the extraction efficiency and stability is highly variable across protocols and tissues by using different quality metrics including the limit of detection and variability between replicates as well as the sum of concentration as a global estimate of extraction stability. The profile of extracted metabolites depends on the used solvents - an observation which has implications for measurements of different sample types and metabolic compounds of interest. To identify the optimal extraction method for future metabolomics studies, the benchmark dataset was implemented in an easy-to-use, interactive and flexible online resource (R/shiny app MetaboExtract).

biochemistry↗