Predominantly Pro-Inflammatory Phenotype with Mixed M1/M2 Polarization of Peripheral Blood Classical Monocytes and Monocyte-Derived Macrophages among Patients with Excessive Ethanol Intake

Excessive alcohol consumption impairs the immune system, induces oxidative stress, and triggers the activation of peripheral blood (PB) monocytes, thereby contributing to alcoholic liver disease (ALD). We analyzed the M1/M2 phenotypes of circulating classical monocytes and macrophage-derived monocytes (MDMs) in excessive alcohol drinkers (EADs). PB samples from 20 EADs and 22 healthy controls were collected for isolation of CD14+ monocytes and short-term culture with LPS/IFNγ, IL4/IL13, or without stimulation. These conditions were also used to polarize MDMs into M1, M2, or M0 phenotypes. Cytokine production was assessed in the blood and culture supernatants. M1/M2-related markers were analyzed using mRNA expression and surface marker detection. Additionally, the miRNA profile of CD14+ monocytes was analyzed. PB samples from EADs exhibited increased levels of pro-inflammatory cytokines. Following short-term culture, unstimulated blood samples from EADs showed higher levels of soluble TNF-α and IL-8, whereas monocytes expressed increased levels of surface TNF-α and elevated mRNA expression of pro-inflammatory cytokines and inducible nitric oxide synthase. MDMs from EADs showed higher levels of TNF-α and CD206 surface markers and increased IL-10 production. LPS/IFNγ induced higher mRNA expression of Nrf2 only in the controls. miRNA analysis revealed a distinctive miRNA profile that is potentially associated with liver carcinogenesis and ALD through inflammation and oxidative stress. This study confirms the predominantly pro-inflammatory profile of PB monocytes among EADs and suggests immune exhaustion features in MDMs.

Scipion Flexibility Hub: an integrative framework for advanced analysis of conformational heterogeneity in cryoEM

Understanding how structure and function meet to drive biological processes is progressively shifting the cryoEM field towards a more advanced analysis of macromolecular flexibility. Thanks to techniques such as single-particle analysis and electron tomography, it is possible to image a macromolecule in different states, information that can subsequently be extracted through advanced image-processing methods to build a richer approximation of a conformational landscape. However, the interoperability of all of these algorithms remains a challenging task that is left to users, preventing them from defining a single flexible workflow in which conformational information can be addressed by different algorithms. Therefore, in this work, a new framework integrated into Scipion is proposed called the Flexibility Hub. This framework automatically handles intercommunication between different heterogeneity software, simplifying the task of combining the software into workflows in which the quality and the amount of information extracted from flexibility analysis is maximized.

Scipion3: A workflow engine for cryo-electron microscopy image processing and structural biology

Image-processing pipelines require the design of complex workflows combining many different steps that bring the raw acquired data to a final result with biological meaning. In the image-processing domain of cryo-electron microscopy single-particle analysis (cryo-EM SPA), hundreds of steps must be performed to obtain the three-dimensional structure of a biological macromolecule by integrating data spread over thousands of micrographs containing millions of copies of allegedly the same macromolecule. The execution of such complicated workflows demands a specific tool to keep track of all these steps performed. Additionally, due to the extremely low signal-to-noise ratio (SNR), the estimation of any image parameter is heavily affected by noise resulting in a significant fraction of incorrect estimates. Although low SNR and processing millions of images by hundreds of sequential steps requiring substantial computational resources are specific to cryo-EM, these characteristics may be shared by other biological imaging domains. Here, we present Scipion, a Python generic open-source workflow engine specifically adapted for image processing. Its main characteristics are: (a) interoperability, (b) smart object model, (c) gluing operations, (d) comparison operations, (e) wide set of domain-specific operations, (f) execution in streaming, (g) smooth integration in high-performance computing environments, (h) execution with and without graphical capabilities, (i) flexible visualization, (j) user authentication and private access to private data, (k) scripting capabilities, (l) high performance, (m) traceability, (n) reproducibility, (o) self-reporting, (p) reusability, (q) extensibility, (r) software updates, and (s) non-restrictive software licensing.

Deciphering the Role and Signaling Pathways of PKCα in Luminal A Breast Cancer Cells

Protein kinase C (PKC) comprises a family of highly related serine/threonine protein kinases involved in multiple signaling pathways, which control cell proliferation, survival, and differentiation. The role of PKCα in cancer has been studied for many years. However, it has been impossible to establish whether PKCα acts as an oncogene or a tumor suppressor. Here, we analyzed the importance of PKCα in cellular processes such as proliferation, migration, or apoptosis by inhibiting its gene expression in a luminal A breast cancer cell line (MCF-7). Differential expression analysis and phospho-kinase arrays of PKCα-KD vs. PKCα-WT MCF-7 cells identified an essential set of proteins and oncogenic kinases of the JAK/STAT and PI3K/AKT pathways that were down-regulated, whereas IGF1R, ERK1/2, and p53 were up-regulated. In addition, unexpected genes related to the interferon pathway appeared down-regulated, while PLC, ERBB4, or PDGFA displayed up-regulated. The integration of this information clearly showed us the usefulness of inhibiting a multifunctional kinase-like PKCα in the first step to control the tumor phenotype. Then allowing us to design a possible selection of specific inhibitors for the unexpected up-regulated pathways to further provide a second step of treatment to inhibit the proliferation and migration of MCF-7 cells. The results of this study suggest that PKCα plays an oncogenic role in this type of breast cancer model. In addition, it reveals the signaling mode of PKCα at both gene expression and kinase activation. In this way, a wide range of proteins can implement a new strategy to fine-tune the control of crucial functions in these cells and pave the way for designing targeted cancer therapies.

ScipionTomo: Towards cryo-electron tomography software integration, reproducibility, and validation

Image processing in cryogenic electron tomography (cryoET) is currently at a similar state as Single Particle Analysis (SPA) in cryogenic electron microscopy (cryoEM) was a few years ago. Its data processing workflows are far from being well defined and the user experience is still not smooth. Moreover, file formats of different software packages and their associated metadata are not standardized, mainly since different packages are developed by different groups, focusing on different steps of the data processing pipeline.

The Scipion framework, originally developed for SPA (de la Rosa-Trevín et al., 2016), has a generic python workflow engine that gives it the versatility to be extended to other fields, as demonstrated for model building (Martínez et al., 2020). In this article, we provide an extension of Scipion based on a set of tomography plugins (referred to as ScipionTomo hereafter), with a similar purpose: to allow users to be focused on the data processing and analysis instead of having to deal with multiple software installation issues and the inconvenience of switching from one to another, converting metadata files, managing possible incompatibilities, scripting (writing a simple program in a language that the computer must convert to machine language each time the program is run), etcetera. Additionally, having all the software available in an integrated platform allows comparing the results of different algorithms trying to solve the same problem. In this way, the commonalities and differences between estimated parameters shed light on which results can be more trusted than others. ScipionTomo is developed by a collaborative multidisciplinary team composed of Scipion team engineers, structural biologists, and in some cases, the developers whose software packages have been integrated. It is open to anyone in the field willing to contribute to this project.

The result is a framework extension that combines the acquired knowledge of Scipion developers in close collaboration with third-party developers, and the on-demand design of functionalities requested by beta testers applying this solution to actual biological problems.

Algorithmic robustness to preferred orientations in single particle analysis by CryoEM

The presence of preferred orientations in single particle analysis (SPA) by cryo-Electron Microscopy (cryoEM) is currently one of the hurdles preventing many structural analyses from yielding high-resolution structures. Although the existence of preferred orientations is mostly related to the grid preparation, in this technical note, we show that some image processing algorithms used for angular assignment and three-dimensional (3D) reconstruction are more robust than others to these detrimental conditions. We exemplify this argument with three different data sets in which the presence of preferred orientations hindered achieving a 3D reconstruction without artifacts or, even worse, a 3D reconstruction could never be achieved.

Hsp70 - a master regulator in protein degradation

Proteostasis, the controlled balance of protein synthesis, folding, assembly, trafficking and degradation, is a paramount necessity for cell homeostasis. Impaired proteostasis is a hallmark of ageing and of many human diseases. Molecular chaperones are essential for proteostasis in eukaryotic cells, and their function has traditionally been linked to protein folding, assembly and disaggregation. More recent findings suggest that chaperones also contribute to key steps in protein degradation. In particular, Hsp70 has an essential role in substrate degradation through the ubiquitin-proteasome system, as well as through different autophagy pathways. Accumulated knowledge suggests that the fate of an Hsp70 substrate is dictated by the combination of partners (cochaperones and other chaperones) that interact with Hsp70 in a given cell context.