Superresolution imaging of human cytomegalovirus vMIA localization in sub-mitochondrial compartments

The human cytomegalovirus (HCMV) viral mitochondria-localized inhibitor of apoptosis (vMIA) protein, traffics to mitochondria-associated membranes (MAM), where the endoplasmic reticulum (ER) contacts the outer mitochondrial membrane (OMM). vMIA association with the MAM has not been visualized by imaging. Here, we have visualized this by using a combination of confocal and superresolution imaging. Deconvolution of confocal microscopy images shows vMIA localizes away from mitochondrial matrix at the Mitochondria-ER interface. By gated stimulated emission depletion (GSTED) imaging, we show that along this interface vMIA is distributed in clusters. Through multicolor, multifocal structured illumination microscopy (MSIM), we find vMIA clusters localize away from MitoTracker Red, indicating its OMM localization. GSTED and MSIM imaging show vMIA exists in clusters of ~100–150 nm, which is consistent with the cluster size determined by Photoactivated Localization Microscopy (PALM). With these diverse superresolution approaches, we have imaged the clustered distribution of vMIA at the OMM adjacent to the ER. Our findings directly compare the relative advantages of each of these superresolution imaging modalities for imaging components of the MAM and sub-mitochondrial compartments. These studies establish the ability of superresolution imaging to provide valuable insight into viral protein location, particularly in the sub-mitochondrial compartments, and into their clustered organization

Congo Basin peatlands: threats and conservation priorities

The recent publication of the first spatially explicit map of peatlands in the Cuvette Centrale, central Congo Basin, reveals it to be the most extensive tropical peatland complex, at ca. 145,500 km2. With an estimated 30.6 Pg of carbon stored in these peatlands, there are now questions about whether these carbon stocks are under threat and, if so, what can be done to protect them. Here, we analyse the potential threats to Congo Basin peat carbon stocks and identify knowledge gaps in relation to these threats, and to how the peatland systems might respond. Climate change emerges as a particularly pressing concern, given its potential to destabilise carbon stocks across the whole area. Socio-economic developments are increasing across central Africa and, whilst much of the peatland area is protected on paper by some form of conservation designation, the potential exists for hydrocarbon exploration, logging, plantations and other forms of disturbance to significantly damage the peatland ecosystems. The low level of human intervention at present suggests that the opportunity still exists to protect the peatlands in a largely intact state, possibly drawing on climate change mitigation funding, which can be used not only to protect the peat carbon pool but also to improve the livelihoods of people living in and around these peatlands

Current strategies for protein production and purification enabling membrane protein structural biology.

Membrane proteins are still heavily underrepresented in the protein data bank (PDB) due to multiple bottlenecks. The typical low abundance of membrane proteins in their natural hosts makes it necessary to overexpress these proteins either in heterologous systems or through in vitro translation/cell-free expression. Heterologous expression of proteins, in turn, leads to multiple obstacles due to the unpredictability of compatibility of the target protein for expression in a given host. The highly hydrophobic and/or amphipathic nature of membrane proteins also leads to challenges in producing a homogeneous, stable, and pure sample for structural studies. Circumventing these hurdles has become possible through introduction of novel protein production protocols; efficient protein isolation and sample preparation methods; and, improvement in hardware and software for structural characterization. Combined, these advances have made the past 10-15 years very exciting and eventful for the field of membrane protein structural biology, with an exponential growth in the number of solved membrane protein structures. In this review, we focus on both the advances and diversity of protein production and purification methods that have allowed this growth in structural knowledge of membrane proteins through X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, and cryo-electron microscopy (cryo-EM).The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Superresolution Imaging Identifies That Conventional Trafficking Pathways Are Not Essential for Endoplasmic Reticulum to Outer Mitochondrial Membrane Protein Transport.

Most nuclear-encoded mitochondrial proteins traffic from the cytosol to mitochondria. Some of these proteins localize at mitochondria-associated membranes (MAM), where mitochondria are closely apposed with the endoplasmic reticulum (ER). We have previously shown that the human cytomegalovirus signal-anchored protein known as viral mitochondria-localized inhibitor of apoptosis (vMIA) traffics from the ER to mitochondria and clusters at the outer mitochondrial membrane (OMM). Here, we have examined the host pathways by which vMIA traffics from the ER to mitochondria and clusters at the OMM. By disruption of phosphofurin acidic cluster sorting protein 2 (PACS-2), mitofusins (Mfn1/2), and dynamin related protein 1 (Drp1), we find these conventional pathways for ER to the mitochondria trafficking are dispensable for vMIA trafficking to OMM. Instead, mutations in vMIA that change its hydrophobicity alter its trafficking to mitochondria. Superresolution imaging showed that PACS-2- and Mfn-mediated membrane apposition or hydrophobic interactions alter vMIA\u27s ability to organize in nanoscale clusters at the OMM. This shows that signal-anchored MAM proteins can make use of hydrophobic interactions independently of conventional ER-mitochondria pathways to traffic from the ER to mitochondria. Further, vMIA hydrophobic interactions and ER-mitochondria contacts facilitate proper organization of vMIA on the OMM

Superresolution Imaging of Human Cytomegalovirus vMIA Localization in Sub-Mitochondrial Compartments

The human cytomegalovirus (HCMV) viral mitochondria-localized inhibitor of apoptosis (vMIA) protein, traffics to mitochondria-associated membranes (MAM), where the endoplasmic reticulum (ER) contacts the outer mitochondrial membrane (OMM). vMIA association with the MAM has not been visualized by imaging. Here, we have visualized this by using a combination of confocal and superresolution imaging. Deconvolution of confocal microscopy images shows vMIA localizes away from mitochondrial matrix at the Mitochondria-ER interface. By gated stimulated emission depletion (GSTED) imaging, we show that along this interface vMIA is distributed in clusters. Through multicolor, multifocal structured illumination microscopy (MSIM), we find vMIA clusters localize away from MitoTracker Red, indicating its OMM localization. GSTED and MSIM imaging show vMIA exists in clusters of ~100–150 nm, which is consistent with the cluster size determined by Photoactivated Localization Microscopy (PALM). With these diverse superresolution approaches, we have imaged the clustered distribution of vMIA at the OMM adjacent to the ER. Our findings directly compare the relative advantages of each of these superresolution imaging modalities for imaging components of the MAM and sub-mitochondrial compartments. These studies establish the ability of superresolution imaging to provide valuable insight into viral protein location, particularly in the sub-mitochondrial compartments, and into their clustered organization

LipidMatch: an automated workflow for rule-based lipid identification using untargeted high-resolution tandem mass spectrometry data

Abstract Background Lipids are ubiquitous and serve numerous biological functions; thus lipids have been shown to have great potential as candidates for elucidating biomarkers and pathway perturbations associated with disease. Methods expanding coverage of the lipidome increase the likelihood of biomarker discovery and could lead to more comprehensive understanding of disease etiology. Results We introduce LipidMatch, an R-based tool for lipid identification for liquid chromatography tandem mass spectrometry workflows. LipidMatch currently has over 250,000 lipid species spanning 56 lipid types contained in in silico fragmentation libraries. Unique fragmentation libraries, compared to other open source software, include oxidized lipids, bile acids, sphingosines, and previously uncharacterized adducts, including ammoniated cardiolipins. LipidMatch uses rule-based identification. For each lipid type, the user can select which fragments must be observed for identification. Rule-based identification allows for correct annotation of lipids based on the fragments observed, unlike typical identification based solely on spectral similarity scores, where over-reporting structural details that are not conferred by fragmentation data is common. Another unique feature of LipidMatch is ranking lipid identifications for a given feature by the sum of fragment intensities. For each lipid candidate, the intensities of experimental fragments with exact mass matches to expected in silico fragments are summed. The lipid identifications with the greatest summed intensity using this ranking algorithm were comparable to other lipid identification software annotations, MS-DIAL and Greazy. For example, for features with identifications from all 3 software, 92% of LipidMatch identifications by fatty acyl constituents were corroborated by at least one other software in positive mode and 98% in negative ion mode. Conclusions LipidMatch allows users to annotate lipids across a wide range of high resolution tandem mass spectrometry experiments, including imaging experiments, direct infusion experiments, and experiments employing liquid chromatography. LipidMatch leverages the most extensive in silico fragmentation libraries of freely available software. When integrated into a larger lipidomics workflow, LipidMatch may increase the probability of finding lipid-based biomarkers and determining etiology of disease by covering a greater portion of the lipidome and using annotation which does not over-report biologically relevant structural details of identified lipid molecules

Additional file 2: of LipidMatch: an automated workflow for rule-based lipid identification using untargeted high-resolution tandem mass spectrometry data

Supplemental Figures and Tables. Contains Figure S1 through Figure S5, and Table S1 through Table S3. (PPTX 593 kb