Biology subjects

Mattila, P.

Publications and source records attributed to Mattila, P..

15 recordsLinked to original sources

bioRxiv2026

Extracellular vesicles from antigen-activated B cells stimulate oncogenic herpesvirus lytic gene expression

B cell-derived extracellular vesicles (B-EVs) have been associated with immunomodulatory functions like antigen presentation, cytokine signaling, and T cell activation. However, little is known about the general composition of B-EVs or how the state of the donor cells affects the B-EV composition or functions. We performed integrated proteomic, lipidomic, and transcriptomic analyses of EVs secreted by B cells in resting conditions or upon 30 min of B cell receptor (BCR) activation. Antigen-driven BCR stimulation led to acute remodeling of the protein and lipid composition, and RNA cargo of the B-EVs, which also translated into differential responses in recipient B cells. Remarkably, EVs from activated B cells stimulated lytic gene expression of latent oncogenic {gamma}-herpesviruses Epstein-Barr virus (EBV) and Kaposi sarcoma-associated herpesvirus (KSHV). These findings suggest a novel mechanism for the potentially oncogenic reactivation of these lifelong-persisting latent herpesviruses, residing in B cells. Our results support a mechanism in which, upon immune activation, B-EVs from antigen-specific B cells induce viral reactivation in bystander B cells in a paracrine manner, providing molecular insights that bridge immune activation and the pathogenesis of {gamma}-herpesvirus infections.

immunology↗

bioRxiv2025

Dynamic Micropatterning Reveals Spatial Dynamics of B Cell Receptor Signaling and Immune Synapse Formation

B cell activation by foreign antigens, recognized by the B cell receptor (BCR), is the key prerequisite for cell differentiation for antibody production. B cells typically encounter antigens bound to the surface of antigen presenting cells (APCs), leading to the formation of the immunological synapse (IS). To gain a deeper understanding of lymphocyte activation, we developed a dynamic micropatterning technique that enables the modeling of IS formation with exceptional spatial and temporal control. Using this method, we can image B cells before and after BCR engagement, in both fixed and live samples. We compared the activation of different BCR proximal signaling proteins in activatory and non-activatory areas of the synapse and found that the activated signaling proteins exhibited distinct spatial distributions. While pCD79A was strongly localized in the antigen-tethered area, surprisingly, pPLC{gamma}2 was enriched in regions lacking BCR ligands. We also visualized the formation of the IS in living cells using enhanced-resolution microscopy in 3D. We identified different cell behaviors during this process, including the repurposing of pre-existing actin-based protrusions as ready-made building blocks for the IS -- a feature uniquely detectable with this highly controllable system. Extending our approach to include a co-stimulatory B cell ligand, ICAM-1, and T cell system using CD3 and CD28 antibodies as ligands, we demonstrate the broader applicability of this method. Overall, our results highlight the power of dynamic micropatterning in elucidating the rapid and dynamic earliest steps of the IS formation with high spatial and temporal precision.

immunology↗

bioRxiv2025

GlycoAvatars: Bead-Coated Membrane Models for Studying the Cancer-Immune Cells Interactome

Immature O-glycosylation of plasma membrane proteins, characterized by the presence of glycosites with a single GalNAc residue (the Tn antigen) rather than more extended and complex glycans, is a prominent feature of many advanced solid tumors across different origins and aetiologies. This form of glycosylation has been strongly associated with poor prognosis and is known to play a crucial role in the progression of the disease. Notably, it has been directly implicated in the crosstalk with the immune system, inducing tolerogenic phenotypes in both innate and adaptive immune cells. Despite this, the specific receptors involved in these interactions remain largely unidentified. To address this gap, we propose a novel high-throughput proteomics assisted strategy for characterizing the glycan interactome using plasma membrane-derived glycoprotein coated magnetic beads. Glycoproteins were isolated from plasma membranes of glycoengineered cell models with immature glycosylation and were then cloaked on the surface of magnetic beads, creating simplified cell "GlycoAvatars." These GlycoAvatars were primarily employed to characterize the interactome between gastric and colorectal cancer cell lines and immune cells (dendritic cells and macrophages), providing a tool for identifying potentially relevant molecular nodes in glycan-mediated immune synapses, foreseeing their application in deciphering tumor-immune interactions.

biochemistry↗

bioRxiv2024

Comprehensive multi-omics profiling of a healthy human cohort

Multi-omics approaches can offer powerful insights into personalized biomarker profiles relevant for disease diagnosis, prognosis, and therapeutics. However, separating meaningful biological variability from technical noise remains a major challenge. The EATRIS-Plus consortium analyzed blood samples from 127 healthy adults across six omics layers using twelve platforms, resulting in one of the most comprehensive multi-omics profiling datasets of healthy individuals available to date. We applied reproducible workflows to analyze and integrate these data, revealing several key findings. Sex significantly influenced all omics layers, emphasizing the importance of sex-balanced study designs. Age could be accurately predicted using epigenetic clocks, achieving high performance with our high-resolution enzymatic methylation sequencing data (R2 = 0.90), whereas candidate aging biomarkers were identified across all omics layers. The resulting dataset provides reference ranges in healthy individuals for abundance and variability of omics features, enabling robust power analyses, sample size estimations, and benchmarking of multi-omics integration methods. This resource can guide future biomarker discovery and personalized health research and was made FAIR-compliant and publicly available via the ClinData Portal (https://clindata.imtm.cz) and a Zenodo repository (https://doi.org/10.5281/zenodo.17514796).

bioinformatics↗

bioRxiv2023

Proteomic profiling of isolated immune synapses from primary mouse B cells

The immune synapse (IS) is a cell-cell interaction platform critical in lymphocyte activation by specific antigens. Despite of B cells being able to also respond to soluble antigens, in particular the in vivo importance of the IS and surface-tethered antigen recognition has strongly emerged in the recent years. The IS serves as a dynamic hub for multiple cellular actions but the molecular details of these functions, especially beyond the B cell antigen receptor (BCR) signalling, remain poorly understood. Here, to address the lack in the systems level understanding of the IS, we setup methodology for comprehensive investigation of the composition of the primary mouse B cells IS at proteome level. Utilizing functionalized magnetic beads to mimic antigen presenting cells and trigger IS formation on them, we developed a method to specifically and robustly extract the cell adhesions on the beads, namely the IS or transferrin receptor mediated adhesion as a control. Our data revealed 661 proteins exclusively present in the IS at 15 minutes after BCR engagement, 13 exclusively in the control adhesions and 365 proteins shared between the samples. We got strong coverage of the known components of the IS as well as identified a plethora of unknown proteins and functional pathways with hitherto unknown roles in B cell IS. Thus, in this work, we validated the IS isolation method as a valuable tool to study early B cell activation by surface-bound antigens as well as unveil several novel proteins and pathways suggestive of new functional aspects in the IS.

immunology↗

bioRxiv2022

Quartet RNA reference materials and ratio-based reference datasets for reliable transcriptomic profiling

As an indispensable tool for transcriptome-wide analysis of differential gene expression, RNA sequencing (RNAseq) has demonstrated great potential in clinical applications. However, the lack of multi-group RNA reference materials of biological relevance and the corresponding reference datasets for assessing the reliability of RNAseq hampers its wide clinical applications wherein the underlying biological differences among study groups are often small. As part of the Quartet Project for quality control and data integration of multiomic profiling, we established four RNA reference materials derived from immortalized B-lymphoblastoid cell lines from four members of a monozygotic twin family. Additionally, we constructed ratio-based transcriptome-wide reference datasets using multi-batch RNAseq datasets, providing "ground truth" for benchmarking. Moreover, Quartet-sample-based quality metrics were developed for assessing reliability of RNAseq technology in terms of intra-batch proficiency and cross-batch reproducibility. The small intrinsic biological differences among the Quartet samples enable sensitive assessment of performance of transcriptomic measurements. The Quartet RNA reference materials combined with the reference datasets can be served as unique resources for assessing data quality and improving reliability of transcriptomic profiling.

genetics↗

bioRxiv2022

Loss of Rab8a in B cells leads to increased antibody responses and class-switch recombination

Rab8a is a small GTPase with a wide range of reported functions in different cell types, including vesicle recycling, vesicle traffic to cilia, cell ruffling, migration, neurite outgrowth, Toll-like receptor signalling and T cell receptor docking at the immune synapse. However, the role of Rab8a in B lymphocytes has not been described to date. Here, using a conditional B cell-specific Rab8a knockout mouse model, we investigate the role of Rab8a both in vivo and in vitro. Rab8a KO mice present enhanced antibody responses to both T-dependent and T-independent immunisations. Rab8a KO cells showed normal BCR trafficking and antigen processing and presentation but however, increased class-switch recombination. While the early BCR signalling responses, such as proximal kinase activation and calcium-flux, were normal, the signalling via AKT and ERK1/2 was decreased. We propose that the lack of Rab8a alters cellular signalling leading to enhanced antibody responses and increased class-switch recombination potentially via downmodulation of the PI3K/AKT/mTOR pathway.

immunology↗

bioRxiv2021

Analysis of human brain tissue derived from DBS surgery

BackgroundTranscriptomic and proteomic profiling of human brain tissue is hindered by availability of fresh samples from living patients. Postmortem samples usually represent the advanced disease stage of the patient. Furthermore, the postmortem interval affects the observed transcriptomic and proteomic profiles. Therefore, access to fresh brain tissue samples from living patients is valuable resource to obtain information on metabolically intact tissue. The implantation of deep brain stimulation (DBS) electrodes into the human brain is a neurosurgical treatment for, e.g., movement disorders. Here, we describe an improved approach to collect brain tissue from surgical instruments used in implantation of DBS device for transcriptomics and proteomics analyses. MethodsSamples were extracted from guide tubes and recording electrodes used in routine DBS implantation procedure that was carried out to treat patients with Parkinsons disease, genetic dystonia and tremor. RNA sequencing was carried out to tissue extracted from the recording microelectrodes and liquid chromatography-mass spectrometry was carried out to analyze tissue from guide tubes. To assess the performance of the current approach, obtained datasets were compared with previously published datasets representing brain tissue. ResultsIn RNA sequencing, altogether 32,034 transcripts representing unique Ensembl gene identifiers were detected from eight samples representing both hemispheres of four patients. By using liquid chromatography-mass spectrometry, we identified 734 unique proteins from 31 samples collected from 14 patients. Comparison with previously published brain derived data indicated that both of our datasets reflected the expected brain tissue specific features. The datasets are available via BioStudies database (accession number S-BSST667). ConclusionsSurgical instruments used in DBS installation retain enough brain material for protein and gene expression studies. Analysis of the datasets indicated that hemisphere-specific expression data can be obtained from individual patients without any sample pooling and without any modifications to the standard surgical protocol. Comparison with previously published datasets obtained with similar approach proved the robustness and reproducibility of the current improved protocol. This approach overcomes the issues that arise from using postmortem tissue, such as effect of postmortem interval, on proteomic and transcriptomic landscape of the brain and can be used for studying molecular aspects of DBS-treatable diseases.

neuroscience↗

bioRxiv2020

AutoCoEv: a high-throughput in silico pipeline for revealing novel protein-protein interactions

Protein-protein communications govern cellular processes via complex regulatory networks, that are still far from being understood. Thus, identifying novel interactions between proteins can significantly facilitate our comprehension of the mechanistic principles of protein functions. Co-evolution between proteins is a sign of functional communication and, as such, provides a powerful approach to search for novel direct or indirect molecular partners. However, evolutionary analysis of large arrays of proteins, in silico, is a highly time-consuming effort, which has limited the usage of this method to protein pairs or small protein groups. Here, we developed AutoCoEv, a user-friendly computational pipeline for the search of co-evolution between a large number of proteins. By driving 15 individual programs, culminating in CAPS2 as the software for detecting co-evolution, AutoCoEv achieves seamless automation and parallelization of the workflow. Importantly, we provide a patch to CAPS2 source code to strengthen its statistical output, allowing for multiple comparisons correction and enhanced analysis of the results. We apply the pipeline to inspect co-evolution among 324 proteins identified to locate at the vicinity of the lipid rafts of B lymphocytes. We successfully detected multiple strong coevolutionary relations between the proteins, predicting many novel partners and previously unidentified clusters of functionally related molecules. We conclude that AutoCoEv, available at https://github.com/mattilalab/autocoev, can be used to predict functional interactions from large datasets in a time and cost-efficient manner.

bioinformatics↗

bioRxiv2020

Patient-tailored design of AML cell subpopulation-selective drug combinations

The extensive primary and secondary drug resistance in acute myeloid leukemia (AML) requires rational approaches to design personalized combinatorial treatments that exploit patient-specific therapeutic vulnerabilities to optimally target disease-driving AML cell subpopulations. However, the large number of AML-relevant drug combinations makes the testing impossible in scarce primary patient cells. This combinatorial problem is further exacerbated by the translational challenge of how to design such personalized and selective drug combinations that do not only show synergistic effect in overall AML cell killing but also result in minimal toxic side effects on non-malignant cells. To solve these challenges, we implemented a systematic computational-experimental approach for identifying potential drug combinations that have a desired synergy-efficacy-toxicity balance. Our mechanism-agnostic approach combines single-cell RNA-sequencing (scRNA-seq) with ex vivo single-agent viability testing in primary patient cells. The data integration and predictive modelling are carried out at a single-cell resolution by means of a machine learning model that makes use of compound-target interaction networks to narrow down the massive search space of potentially effective drug combinations. When applied to two diagnostic and two refractory AML patient cases, each having a different genetic background, our integrated approach predicted a number of patient-specific combinations that were shown to result not only in synergistic cancer cell inhibition but were also capable of targeting specific AML cell subpopulations that emerge in differing stages of disease pathogenesis or treatment regimens. Overall, 53% of the 59 predicted combinations were experimentally confirmed to show synergy, and 83% were non-antagonistic, as validated with viability assays, which is a significant improvement over the success rate of randomly guessing a synergistic drug combination (5%). Importantly, 67% of the predicted combinations showed low toxicity to non-malignant cells, as validated with flow-based population assays, suggesting their selective killing of AML cell populations. Our data-driven approach provides an unbiased means for systematic prioritization of patient-specific drug combinations that selectively inhibit AML cells and avoid co-inhibition of non-malignant cells, thereby increasing their likelihood for clinical translation. The approach uses only a limited number of patient primary cells, and it is widely applicable to hematological cancers that are accessible for scRNA-seq profiling and ex vivo compound testing.

systems biology↗

bioRxiv2020

ZeroCostDL4Mic: an open platform to simplify access and use of Deep-Learning in Microscopy

The resources and expertise needed to use Deep Learning (DL) in bioimaging remain significant barriers for most laboratories. We present https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki, a platform simplifying access to DL by exploiting the free, cloud-based computational resources of Google Colab. https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki allows researchers to train, evaluate, and apply key DL networks to perform tasks including segmentation, detection, denoising, restoration, resolution enhancement and image-to-image translation. We demonstrate the application of the platform to study multiple biological processes.

bioinformatics↗

bioRxiv2019

Missing-In-Metastasis / Metastasis Suppressor 1 modulates B cell receptor signaling, B cell metabolic potential and T cell-independent immune responses.

Efficient generation of antibodies by B cells is one of the prerequisites of protective immunity. B cell activation by cognate antigens via B cell receptors (BCR), or pathogen-associated molecules through pattern-recognition receptors, such as Toll-like receptors (TLRs), leads to transcriptional and metabolic changes that ultimately transform B cells into antibody producing plasma cells or memory cells. BCR signaling and a number of steps downstream of it rely on coordinated action of cellular membranes and the actin cytoskeleton, tightly controlled by concerted action of multiple regulatory proteins, some of them exclusive to B cells. Here, we dissect the role of Missing-In-Metastasis (MIM), or Metastasis suppressor 1 (MTSS1), a cancer-associated membrane and actin cytoskeleton regulating protein, in B cell-mediated immunity by taking advantage of MIM knockout mouse strain. We show undisturbed B cell development and largely normal composition of B cell compartments in the periphery. Interestingly, we found that MIM-/- B cells are defected in BCR signaling in response to surface-bound antigens but, on the other hand, show increased metabolic activity after stimulation with LPS or CpG. In vivo, MIM knockout animals exhibit impaired IgM antibody responses to immunization with T cell-independent antigen. This study provides the first comprehensive characterization of MIM in B cells, demonstrates its regulatory role for B cell-mediated immunity, as well as proposes new functions for MIM in tuning receptor signaling and cellular metabolism, processes which may also contribute to the poorly understood functions of MIM in cancer.

immunology↗

bioRxiv2019

Fast targeting of antigen and surface-derived MHCII into degradative compartments implies endosomal prewiring for antigen presentation in B cells.

In order to mount high-affinity antibody responses, B cells internalise specific antigens and process them into peptides loaded onto MHCII for presentation to TO_SCPLOWHC_SCPLOW cells. While the biochemical principles of antigen processing and MHCII loading have been well dissected, how the endosomal vesicle system is wired to enable these specific functions remains much less studied. Here, we performed a systematic microscopy-based analysis of antigen trafficking in B cells to reveal its route to the MHCII peptide-loading compartment (MIIC). Surprisingly, we detected fast targeting of internalised antigen into peripheral acidic compartments that possessed the hallmarks of MIIC and also showed degradative capacity. In these vesicles, internalised antigen converged rapidly with membrane-derived MHCII and partially overlapped with Cathepsin-S and H2-M, both required for peptide loading. These early compartments appeared heterogenous and atypical as they contained a mixture of both early and late markers, indicating specialized endosomal route. Together, our data suggests that, in addition to previously-reported perinuclear late endosomal MIICs, antigen processing and peptide loading could start already in these specialized early peripheral acidic vesicles (eMIIC) to support fast peptide-MHCII presentation.

immunology↗

bioRxiv2018

FinDonor 10 000 study: A cohort to identify iron depletion and factors affecting it in Finnish blood donors

Background and ObjectivesThere is increasing evidence that frequent blood donation depletes the iron stores of some blood donors. The FinDonor 10 000 study was set up to study iron status and factors affecting iron stores in Finnish blood donors. In Finland, iron supplementation for at-risk groups has been in place since the 1980s. Material and Methods2584 blood donors (N= 8003 samples) were recruited into the study alongside the standard donation at three donation sites in the capital region of Finland between 5/2015 and 12/2017. All participants were asked to fill out a questionnaire about their health and lifestyle. Blood samples were collected from the sample pouch of whole blood collection set, kept in cool temperature and processed centrally. Whole blood count, CRP, ferritin and sTFR were measured from the samples and DNA was isolated for GWAS studies. ResultsParticipant demographics, albeit in general similar to the general blood donor population in Finland, indicated some bias toward older and more frequent donors. Participation in the study increased median donation frequency of the donors. Analysis of the effect of time lag from the sampling to the analysis and the time of day when sample was drawn revealed small but significant time-dependent changes. ConclusionThe FinDonor cohort now provides us with tools to identify potential donor groups at increased risk of iron deficiency as factors explaining this risk. The increase in donation frequency during the study suggests that scientific projects can be used to increase the commitment of blood donors.

epidemiology↗

bioRxiv2018

MITA couples with PI3K to regulate actin reorganization during BCR activation

As an adaptor protein, MITA has been extensively studied in innate immunity. However, its role in adaptive immunity as well as its underlying mechanism are not completely understood. We used MITA KO mice to study the effect of MITA deficiency on B cell development and differentiation, BCR signaling during BCR activation and humoral immune response. We found that MITA deficiency promotes the differentiation of marginal zone B cells, which is linked to the lupus-like autoimmune disease that develops in MITA KO mice. MITA is involved in BCR activation and negatively regulates the activation of CD19 and Btk and positively regulates the activation of SHIP. Interestingly, we found that the activation of WASP and accumulation of F-actin is enhanced in MITA KO B cells upon stimulation. Mechanistically, we found that MITA uses PI3K mediated by the CD19-Btk axis as a central hub to control the actin remodeling that, in turn, offers feedback to BCR signaling. Overall, our study has provided a new mechanism on how MITA regulates BCR signaling via feedback from actin reorganization, which may contribute to the effects of MITA on the humoral immune response.

immunology↗