LocSigDB: a database of protein localization signals

Characterization of a novel cytosolic sesquiterpene synthase MpTPS4 from Mentha ×piperita as a bioresource for the enrichment of invaluable viridiflorol in mentha essential oil

Our research addresses the challenge of low concentrations of viridiflorol, a unique and highly valuable sesquiterpene found in various Mentha species. We employed biotechnological strategies to enhance viridiflorol production, which could significantly boost export revenue. Mentha piperita L. sesquiterpene synthase (MpTPS4) was the focus of our study because it is a key enzyme in the biosynthesis of viridiflorol. Through biochemical characterization, we confirmed that MpTPS4 exclusively synthesizes viridiflorol. By overexpressing MpTPS4 in M. ×piperita L. using a glandular trichome-specific promoter, we achieved a notable increase (9-25 %) in viridiflorol content. Additionally, we explored the practical application of viridiflorol as a deterrent against the herbivore Helicoverpa armigera. The RNAi-mediated knockdown of MpTPS4 resulted in a significant reduction in viridiflorol levels in the essential oil. More importantly, these results show how relevant MpTPS4 is for making viridiflorol and how biotechnology could be used to increase biosynthesis. Our research provides valuable insights into enhancing the production of this commercially important sesquiterpene, offering promising opportunities for the mentha industry.

PE_PGRS45 (Rv2615c) protein of Mycobacterium tuberculosis perturbs mitochondria of macrophages

The PE_PGRS proteins have coevolved with the antigenic ESX-V secretory system and are abundant in pathogenic Mycobacterium. Only a few PE_PGRS proteins have been characterized, and research suggests their role in organelle targeting, cell death pathways, calcium (Ca2+ ) homeostasis and disease pathogenesis. The PE_PGRS45 (Rv2615c) protein was predicted to contain mitochondria targeting sequences by in silico evaluation. Therefore, we investigated the targeting of the Rv2615c protein to host mitochondria and its effect on mitochondrial functions. In vitro experiments showed the Rv2615c protein colocalized with the mitochondria and led to morphological mitochondrial perturbations. Recombinant Rv2615c was observed to cause increased levels of intracellular reactive oxygen species and the adenosine diphosphate-to-adenosine triphosphate ratio. The Rv2615c protein also induced mitochondrial membrane depolarization and the generation of mitochondrial superoxide. We observed the release of cytochrome C into the cytoplasm and increased expression of proapoptotic genes Bax and Bim with no significant change in anti-apoptotic Bcl2 in Rv2615c-stimulated THP1 macrophages. Ca2+ is a key signaling molecule in tuberculosis pathogenesis, modulating host cell responses. As reported for other PE_PGRS proteins, Rv2615c also has Ca2+ -binding motifs and thus can modulate calcium homeostasis in the host. We also observed a high level of Ca2+ influx in THP1 macrophages stimulated with Rv2615c. Based on these findings, we suggest that Rv2615c may be an effector protein that could contribute to disease pathogenesis by targeting host mitochondria.

FungiProteomeDB: a database for the molecular weight and isoelectric points of the fungal proteomes

Proteins' molecular weight (MW) and isoelectric point (pI) are crucial for their subcellular localization and subsequent function. These are also useful in 2D gel electrophoresis, liquid chromatography-mass spectrometry and X-ray protein crystallography. Moreover, visualizations like a virtual 2D proteome map of pI vs. MW are worthwhile to discuss the proteome diversity among different species. Although the genome sequence data of the fungi kingdom improved enormously, the proteomic details have been poorly elaborated. Therefore, we have calculated the MW and pI of the fungi proteins and reported them in, FungiProteomeDB, an online database (DB) https://vision4research.com/fungidb/. We analyzed the proteome of 685 fungal species that contain 7 127 141 protein sequences. The DB provides an easy-to-use and efficient interface for various search options, summary statistics and virtual 2D proteome map visualizations. The MW and pI of a protein can be obtained by searching the name of a protein, a keyword or a list of accession numbers. It also allows querying protein sequences. The DB will be helpful in hypothesis formulation and in various biotechnological applications. Database URL https://vision4research.com/fungidb/.

Transcytosis and trans-synaptic retention by postsynaptic ErbB4 underlie axonal accumulation of NRG3

Neuregulins (NRGs) are EGF-like ligands associated with cognitive disorders. Unprocessed proNRG3 is cleaved by BACE1 to generate the mature membrane-bound NRG3 ligand, but the subcellular site of proNRG3 cleavage, mechanisms underlying its transport into axons, and presynaptic accumulation remain unknown. Using an optogenetic proNRG3 cleavage reporter (LA143-NRG3), we investigate the spatial-temporal dynamics of NRG3 processing and sorting in neurons. In dark conditions, unprocessed LA143-NRG3 is retained in the trans-Golgi network but, upon photoactivation, is cleaved by BACE1 and released from the TGN. Mature NRG3 then emerges on the somatodendritic plasma membrane from where it is re-endocytosed and anterogradely transported on Rab4+ vesicles into axons via transcytosis. By contrast, the BACE1 substrate APP is sorted into axons on Rab11+ vesicles. Lastly, by a mechanism we denote "trans-synaptic retention," NRG3 accumulates at presynaptic terminals by stable interaction with its receptor ErbB4 on postsynaptic GABAergic interneurons. We propose that trans-synaptic retention may account for polarized expression of other neuronal transmembrane ligands and receptors.

PlantMWpIDB: a database for the molecular weight and isoelectric points of the plant proteomes

The molecular weight and isoelectric point of the proteins are very important parameters that control their subcellular localization and subsequent function. Although the genome sequence data of the plant kingdom improved enormously, the proteomic details have been poorly elaborated. Therefore, we have calculated the molecular weight and isoelectric point of the plant proteins and reported them in this database. A database, PlantMWpIDB, containing protein data from 342 plant proteomes was created to provide information on plant proteomes for hypothesis formulation in basic research and for biotechnological applications. The Molecular weight and isoelectric point (pI) are important molecular parameters of proteins that are useful when conducting protein studies involving 2D gel electrophoresis, liquid chromatography-mass spectrometry, and X-ray protein crystallography. PlantMWpIDB provides an easy-to-use and efficient interface for search options and generates a summary of basic protein parameters. The database represents a virtual 2D proteome map of plants, and the molecular weight and pI of a protein can be obtained by searching on the name of a protein, a keyword, or by a list of accession numbers. The PlantMWpIDB database also allows one to query protein sequences. The database can be found in the following link https://plantmwpidb.com/ . The individual 2D virtual proteome map of the plant kingdom will enable us to understand the proteome diversity between different species. Further, the molecular weight and isoelectric point of individual proteins can enable us to understand their functional significance in different species.

Affinity Purification-Mass Spectrometry Identifies a Novel Interaction between a Polerovirus and a Conserved Innate Immunity Aphid Protein that Regulates Transmission Efficiency

The vast majority of plant viruses are transmitted by insect vectors, with many crucial aspects of the transmission process being mediated by key protein-protein interactions. Still, very few vector proteins interacting with viruses have been identified and functionally characterized. Potato leafroll virus (PLRV) is transmitted most efficiently by Myzus persicae, the green peach aphid, in a circulative, non-propagative manner. Using affinity purification coupled to high-resolution mass spectrometry (AP-MS), we identified 11 proteins from M. persicaedisplaying a high probability of interaction with PLRV and an additional 23 vector proteins with medium confidence interaction scores. Three of these aphid proteins were confirmed to directly interact with the structural proteins of PLRV and other luteovirid species via yeast two-hybrid. Immunolocalization of one of these direct PLRV-interacting proteins, an orthologue of the human innate immunity protein complement component 1 Q subcomponent-binding protein (C1QBP), shows that MpC1QBP partially co-localizes with PLRV in cytoplasmic puncta and along the periphery of aphid gut epithelial cells. Artificial diet delivery to aphids of a chemical inhibitor of C1QBP leads to increased PLRV acquisition by aphids and subsequently increased titer in inoculated plants, supporting a role for C1QBP in the acquisition and transmission efficiency of PLRV by M. persicae. This study presents the first use of AP-MS for the in vivo isolation of a functionally relevant insect vector-virus protein complex. MS data are available from ProteomeXchange.org using the project identifier PXD022167.

Computational Biology and Machine Learning Approaches to Understand Mechanistic Microbiome-Host Interactions

The microbiome, by virtue of its interactions with the host, is implicated in various host functions including its influence on nutrition and homeostasis. Many chronic diseases such as diabetes, cancer, inflammatory bowel diseases are characterized by a disruption of microbial communities in at least one biological niche/organ system. Various molecular mechanisms between microbial and host components such as proteins, RNAs, metabolites have recently been identified, thus filling many gaps in our understanding of how the microbiome modulates host processes. Concurrently, high-throughput technologies have enabled the profiling of heterogeneous datasets capturing community level changes in the microbiome as well as the host responses. However, due to limitations in parallel sampling and analytical procedures, big gaps still exist in terms of how the microbiome mechanistically influences host functions at a system and community level. In the past decade, computational biology and machine learning methodologies have been developed with the aim of filling the existing gaps. Due to the agnostic nature of the tools, they have been applied in diverse disease contexts to analyze and infer the interactions between the microbiome and host molecular components. Some of these approaches allow the identification and analysis of affected downstream host processes. Most of the tools statistically or mechanistically integrate different types of -omic and meta -omic datasets followed by functional/biological interpretation. In this review, we provide an overview of the landscape of computational approaches for investigating mechanistic interactions between individual microbes/microbiome and the host and the opportunities for basic and clinical research. These could include but are not limited to the development of activity- and mechanism-based biomarkers, uncovering mechanisms for therapeutic interventions and generating integrated signatures to stratify patients.

Phenotypic characterization of Adig null mice suggests roles for adipogenin in the regulation of fat mass accrual and leptin secretion

Adipogenin (Adig) is an adipocyte-enriched transmembrane protein. Its expression is induced during adipogenesis in rodent cells, and a recent genome-wide association study associated body mass index (BMI)-adjusted leptin levels with the ADIG locus. In order to begin to understand the biological function of Adig, we studied adipogenesis in Adig-deficient cultured adipocytes and phenotyped Adig null (Adig^-/-) mice. Data from Adig-deficient cells suggest that Adig is required for adipogenesis. In vivo, Adig^-/- mice are leaner than wild-type mice when fed a high-fat diet and when crossed with Ob/Ob hyperphagic mice. In addition to the impact on fat mass accrual, Adig deficiency also reduces fat-mass-adjusted plasma leptin levels and impairs leptin secretion from adipose explants, suggesting an additional impact on the regulation of leptin secretion.

A platform for post-translational spatiotemporal control of cellular proteins

Mammalian cells process information through coordinated spatiotemporal regulation of proteins. Engineering cellular networks thus relies on efficient tools for regulating protein levels in specific subcellular compartments. To address the need to manipulate the extent and dynamics of protein localization, we developed a platform technology for the target-specific control of protein destination. This platform is based on bifunctional molecules comprising a target-specific nanobody and universal sequences determining target subcellular localization or degradation rate. We demonstrate that nanobody-mediated localization depends on the expression level of the target and the nanobody, and the extent of target subcellular localization can be regulated by combining multiple target-specific nanobodies with distinct localization or degradation sequences. We also show that this platform for nanobody-mediated target localization and degradation can be regulated transcriptionally and integrated within orthogonal genetic circuits to achieve the desired temporal control over spatial regulation of target proteins. The platform reported in this study provides an innovative tool to control protein subcellular localization, which will be useful to investigate protein function and regulate large synthetic gene circuits.

Synthetic Monopartite Peptide That Enables the Nuclear Import of Genes Delivered by the Neurotensin-Polyplex Vector

Neurotensin (NTS)-polyplex is a multicomponent nonviral vector that enables gene delivery via internalization of the neurotensin type 1 receptor (NTSR1) to dopaminergic neurons and cancer cells. An approach to improving its therapeutic safety is replacing the viral karyophilic component (peptide KPSV40; MAPTKRKGSCPGAAPNKPK), which performs the nuclear import activity, by a shorter synthetic peptide (KPRa; KMAPKKRK). We explored this issue and the mechanism of plasmid DNA translocation through the expression of the green fluorescent protein or red fluorescent protein fused with KPRa and internalization assays and whole-cell patch-clamp configuration experiments in a single cell together with importin α/β pathway blockers. We showed that KPRa electrostatically bound to plasmid DNA increased the transgene expression compared with KPSV40 and enabled nuclear translocation of KPRa-fused red fluorescent proteins and plasmid DNA. Such translocation was blocked with ivermectin or mifepristone, suggesting importin α/β pathway mediation. KPRa also enabled NTS-polyplex-mediated expression of reporter or physiological genes such as human mesencephalic-derived neurotrophic factor (hMANF) in dopaminergic neurons in vivo. KPRa is a synthetic monopartite peptide that showed nuclear import activity in NTS-polyplex vector-mediated gene delivery. KPRa could also improve the transfection of other nonviral vectors used in gene therapy.

Construction and expression of recombinant uricase‑expressing genetically engineered bacteria and its application in rat model of hyperuricemia

At present, the treatment of hyperuricemia is designed primarily to decrease the production of uric acid using xanthine oxidase inhibitors; however, the therapeutic effect is not satisfactory. Therefore, the key to the successful treatment of hyperuricemia is to increase the excretion of uric acid. The aim of present study was to construct uricase-expressing genetically engineered bacteria and analyze the effects of these engineered bacteria on the lowering of uric acid levels in a rat model of hyperuricemia. The uricase expression vector was constructed by gene recombination technology and transfected into Escherichia coli. The expression and activity of uricase were analyzed by SDS-PAGE analysis and Bradford assay. The water consumption, food intake, body weight, eosinophil count and intestinal histology, in addition to the levels of serum uric acid (SUA) and allantoin in the feces of the rats, were assessed. The intestinal contents of the rats were analyzed by 16S rDNA sequencing technology. The results demonstrated that uricase-expressing genetically engineered bacteria secreted active uricase. All rats exhibited a natural growth trend during the entire experiment, and the SUA of hyperuricemic rats treated with uricase-expressing engineered bacteria was significantly decreased. In conclusion, these results indicate that uricase secreted by recombinant uricase-expressing genetically engineered bacteria served an important role in decreasing SUA levels in a rat model of hyperuricemia.

Show me your secret(ed) weapons: a multifaceted approach reveals a wide arsenal of type III-secreted effectors in the cucurbit pathogenic bacterium Acidovorax citrulli and novel effectors in the Acidovorax genus

The cucurbit pathogenic bacterium Acidovorax citrulli requires a functional type III secretion system (T3SS) for pathogenicity. In this bacterium, as with Xanthomonas and Ralstonia spp., an AraC-type transcriptional regulator, HrpX, regulates expression of genes encoding T3SS components and type III-secreted effectors (T3Es). The annotation of a sequenced A. citrulli strain revealed 11 T3E genes. Assuming that this could be an underestimation, we aimed to uncover the T3E arsenal of the A. citrulli model strain, M6. Thorough sequence analysis revealed 51 M6 genes whose products are similar to known T3Es. Furthermore, we combined machine learning and transcriptomics to identify novel T3Es. The machine-learning approach ranked all A. citrulli M6 genes according to their propensity to encode T3Es. RNA-Seq revealed differential gene expression between wild-type M6 and a mutant defective in HrpX: 159 and 28 genes showed significantly reduced and increased expression in the mutant relative to wild-type M6, respectively. Data combined from these approaches led to the identification of seven novel T3E candidates that were further validated using a T3SS-dependent translocation assay. These T3E genes encode hypothetical proteins that seem to be restricted to plant pathogenic Acidovorax species. Transient expression in Nicotiana benthamiana revealed that two of these T3Es localize to the cell nucleus and one interacts with the endoplasmic reticulum. This study places A. citrulli among the 'richest' bacterial pathogens in terms of T3E cargo. It also revealed novel T3Es that appear to be involved in the pathoadaptive evolution of plant pathogenic Acidovorax species.

Peptide Bond Cleavage by Ni(II) Ions within the Nuclear Localization Signal Sequence

Nickel is harmful to humans, being both carcinogenic and allergenic. However, the mechanisms of this toxicity are still unresolved. We propose that Ni(II) ions disintegrate proteins by hydrolysis of peptide bonds preceding the Ser/Thr-Xaa-His sequences. Such sequences occur in nuclear localization signals (NLSs) of human phospholipid scramblase 1, Sam68-like mammalian protein 2, and CLK3 kinase. We performed spectroscopic experiments showing that model nonapeptides derived from these NLSs bind Ni(II) at physiological pH. We also proved that these sequences are prone to Ni(II) hydrolysis. Thus, the aforementioned NLSs may be targets for nickel toxicity. This implies that Ni(II) ions disrupt the transport of some proteins from cytoplasm to cell nucleus.

Arabidopsis TRM5 encodes a nuclear-localised bifunctional tRNA guanine and inosine-N1-methyltransferase that is important for growth

Modified nucleosides in tRNAs are critical for protein translation. N1-methylguanosine-37 and N1-methylinosine-37 in tRNAs, both located at the 3'-adjacent to the anticodon, are formed by Trm5. Here we describe Arabidopsis thaliana AtTRM5 (At3g56120) as a Trm5 ortholog. Attrm5 mutant plants have overall slower growth as observed by slower leaf initiation rate, delayed flowering and reduced primary root length. In Attrm5 mutants, mRNAs of flowering time genes are less abundant and correlated with delayed flowering. We show that AtTRM5 complements the yeast trm5 mutant, and in vitro methylates tRNA guanosine-37 to produce N1-methylguanosine (m1G). We also show in vitro that AtTRM5 methylates tRNA inosine-37 to produce N1-methylinosine (m1I) and in Attrm5 mutant plants, we show a reduction of both N1-methylguanosine and N1-methylinosine. We also show that AtTRM5 is localized to the nucleus in plant cells. Proteomics data showed that photosynthetic protein abundance is affected in Attrm5 mutant plants. Finally, we show tRNA-Ala aminoacylation is not affected in Attrm5 mutants. However the abundance of tRNA-Ala and tRNA-Asp 5' half cleavage products are deduced. Our findings highlight the bifunctionality of AtTRM5 and the importance of the post-transcriptional tRNA modifications m1G and m1I at tRNA position 37 in general plant growth and development.

The transportome of the malaria parasite

Membrane transport proteins, also known as transporters, control the movement of ions, nutrients, metabolites, and waste products across the membranes of a cell and are central to its biology. Proteins of this type also serve as drug targets and are key players in the phenomenon of drug resistance. The malaria parasite has a relatively reduced transportome, with only approximately 2.5% of its genes encoding transporters. Even so, assigning functions and physiological roles to these proteins, and ascertaining their contributions to drug action and drug resistance, has been very challenging. This review presents a detailed critique and synthesis of the disruption phenotypes, protein subcellular localisations, protein functions (observed or predicted), and links to antimalarial drug resistance for each of the parasite's transporter genes. The breadth and depth of the gene disruption data are particularly impressive, with at least one phenotype determined in the parasite's asexual blood stage for each transporter gene, and multiple phenotypes available for 76% of the genes. Analysis of the curated data set revealed there to be relatively little redundancy in the Plasmodium transportome; almost two-thirds of the parasite's transporter genes are essential or required for normal growth in the asexual blood stage of the parasite, and this proportion increased to 78% when the disruption phenotypes available for the other parasite life stages were included in the analysis. These observations, together with the finding that 22% of the transportome is implicated in the parasite's resistance to existing antimalarials and/or drugs within the development pipeline, indicate that transporters are likely to serve, or are already serving, as drug targets. Integration of the different biological and bioinformatic data sets also enabled the selection of candidates for transport processes known to be essential for parasite survival, but for which the underlying proteins have thus far remained undiscovered. These include potential transporters of pantothenate, isoleucine, or isopentenyl diphosphate, as well as putative anion-selective channels that may serve as the pore component of the parasite's 'new permeation pathways'. Other novel insights into the parasite's biology included the identification of transporters for the potential development of antimalarial treatments, transmission-blocking drugs, prophylactics, and genetically attenuated vaccines. The syntheses presented herein set a foundation for elucidating the functions and physiological roles of key members of the Plasmodium transportome and, ultimately, to explore and realise their potential as therapeutic targets.

UNIPred-Web: a web tool for the integration and visualization of biomolecular networks for protein function prediction

Background

One of the main issues in the automated protein function prediction (AFP) problem is the integration of multiple networked data sources. The UNIPred algorithm was thereby proposed to efficiently integrate —in a function-specific fashion— the protein networks by taking into account the imbalance that characterizes protein annotations, and to subsequently predict novel hypotheses about unannotated proteins. UNIPred is publicly available as R code, which might result of limited usage for non-expert users. Moreover, its application requires efforts in the acquisition and preparation of the networks to be integrated. Finally, the UNIPred source code does not handle the visualization of the resulting consensus network, whereas suitable views of the network topology are necessary to explore and interpret existing protein relationships.

Results

We address the aforementioned issues by proposing UNIPred-Web, a user-friendly Web tool for the application of the UNIPred algorithm to a variety of biomolecular networks, already supplied by the system, and for the visualization and exploration of protein networks. We support different organisms and different types of networks —e.g., co-expression, shared domains and physical interaction networks. Users are supported in the different phases of the process, ranging from the selection of the networks and the protein function to be predicted, to the navigation of the integrated network. The system also supports the upload of user-defined protein networks. The vertex-centric and the highly interactive approach of UNIPred-Web allow a narrow exploration of specific proteins, and an interactive analysis of large sub-networks with only a few mouse clicks.

Conclusions

UNIPred-Web offers a practical and intuitive (visual) guidance to biologists interested in gaining insights into protein biomolecular functions. UNIPred-Web provides facilities for the integration of networks, and supplies a framework for the imbalance-aware protein network integration of nine organisms, the prediction of thousands of GO protein functions, and a easy-to-use graphical interface for the visual analysis, navigation and interpretation of the integrated networks and of the functional predictions.

Genome-wide functional association networks: background, data & state-of-the-art resources

The vast amount of experimental data from recent advances in the field of high-throughput biology begs for integration into more complex data structures such as genome-wide functional association networks. Such networks have been used for elucidation of the interplay of intra-cellular molecules to make advances ranging from the basic science understanding of evolutionary processes to the more translational field of precision medicine. The allure of the field has resulted in rapid growth of the number of available network resources, each with unique attributes exploitable to answer different biological questions. Unfortunately, the high volume of network resources makes it impossible for the intended user to select an appropriate tool for their particular research question. The aim of this paper is to provide an overview of the underlying data and representative network resources as well as to mention methods of integration, allowing a customized approach to resource selection. Additionally, this report will provide a primer for researchers venturing into the field of network integration.

Comparative analysis of homologous aminopeptidase PepN from pathogenic and non-pathogenic mycobacteria reveals divergent traits

Mycobacterium tuberculosis (Mtb) secretes proteases and peptidases to subjugate its host. Out of its sixty plus proteases, atleast three are reported to reach host macrophages. In this study, we show that Mtb also delivers a lysyl alanine aminopeptidase, PepN (Rv2467) into host macrophage cytosol. Our comparative in silico analysis shows PepNMtb highly conserved across all pathogenic mycobacteria. Non-pathogenic mycobacteria including M. smegmatis (Msm) also encode pepN. PepN protein levels in both Mtb (pathogenic) and Msm (non-pathogenic) remain uniform across all in vitro growth phases. Despite such tight maintenance of PepNs' steady state levels, upon supplementation, Mtb alone allows accumulation of any excessive PepN. In contrast, Msm does not. It not only proteolyzes, but also secretes out the excessive PepN, be it native or foreign. Interestingly, while PepNMtb is required for modulating virulence in vivo, PepNMsm is essential for Msm growth in vitro. Despite such essentiality difference, both PepNMtb and PepNMsm harbor almost identical N-terminal M1-type peptidase domains that significantly align in their amino acid sequences and overlap in their secondary structures. Their C-terminal ERAP1_C-like domains however align much more moderately. Our in vitro macrophage-based infection experiments with MtbΔpepN-expressing pepNMsm reveals PepNMsm also retaining the ability to reach host cytosol. Lastly, but notably, we determined the PepNMtb and PepNMsm interactomes and found them to barely coincide. While PepNMtb chiefly interacts with Mtb's secreted proteins, PepNMsm primarily coimmunoprecipitates with Msm's housekeeping proteins. Thus, despite high sequence homology and several common properties, our comparative analytical study reveals host-centric traits of pathogenic and bacterial-centric traits of non-pathogenic PepNs.

Bardet-Biedl syndrome obesity: BBS4 regulates cellular ER stress in early adipogenesis

BACKGROUND

Bardet-Biedl syndrome (BBS) is an autosomal recessive ciliopathy, presenting with early obesity onset. The etiology of BBS obesity involves both central and peripheral defects, through mechanisms mostly yet to be deciphered. We previously showed BBS4 expression in adipogenesis, peaking at day 3 of differentiation. Obesity is characterized by cellular stress which promotes pathological consequences.

AIMS

We set out to test a possible role of BBS4 in adipocyte endoplasmic reticulum (ER) stress-induced unfolding protein response (UPR).

METHODS

BBS4 silenced (SiBBS4) and overexpressing (OEBBS4) pre-adipocyte murine cell lines were subjected to ER-stress induction (Tunicamycin, TM) during adipogenesis. ER-stress UPR was analyzed at the transcript, protein and biochemical levels (microscopy, immunocytochemistry, western blotting, quantitative RT-PCR and X-box binding protein 1 (XBP-1) splicing).

RESULTS

In silico analysis showed that BBS4 harbors an ER localization sequences indicative of ER localization. We verified BBS4's ER localization in adipocytes by immunocytochemistry and cellular protein fractionation. Furthermore, we demonstrated that BBS4 expression is significantly up-regulated by ER-stress, as indicated by protein and transcript levels. SiBBS4 adipocytes exhibited swollen ER typical to ER-stress and significant XBP-1 down-regulation at day 3 of differentiation. Following ER-stress, SiBBS4 adipocytes exhibited XBP-1 ER retention, failure to translocate to the nucleus and depletion of the nuclear active cleaved ATF6α. BBS4 did not alter ATF6α processing by S1P and S2P in the Golgi. Notably, SiBBS4 cells demonstrated significant reduction in the downstream activated phospho-IRE1α, independent of ER-stress.

CONCLUSIONS

At day 3 of adipogenesis, coinciding with the timing of its peak expression, BBS4 is localized to the ER and is involved in the ER stress response and trafficking. BBS4 depletion results in swollen ER with impaired intracellular nucleus translocation of XBP-1 and ATF6α. Thus, BBS4 affects the ER stress response in early adipogenesis, altering ER stress responsiveness and the adipocyte ER phenotype.

Genome-wide identification of the SPL gene family in Dichanthelium oligosanthes

SQUAMOSA promoter-binding protein-like (SPL) transcription factors play vital roles in various plant physiological processes. Although, the identification of the SPL gene family has been done in C4 grass plants, including rice and maize, the same has not been characterized in the C3 grass species Dichanthelium oligosanthes. In this study, 14 SPL genes were identified in the genome of D. oligosanthes. Gene structure analysis of the identified DoSPLs revealed the similarity and redundancy in their exon/intron organizations. Sequence comparisons within the DoSPLs and along with rice SPLs revealed the putative paralogs and orthologs in D. oligosanthes SPL genes. Phylogenetic analysis clustered the DoSPLs into eight groups along with other plant SPLs. Identification of the conserved SBP motifs in all 14 DoSPLs suggested them to be putative SPLs. In addition, the prediction of sub-cellular localization and associated functions for DoSPLs further supported to be SPL genes. The outcome of this study can serve as a framework for the isolation and functional validation of SPL genes in D. oligosanthes.

An exact test for comparing a fixed quantitative property between gene sets

Motivation

A significant difference in the distribution of a feature between two gene sets can provide insight into function or regulation. This statistical setting differs from much of hypothesis testing theory because the genome is often considered to be effectively fixed, finite and entirely known in commonly studied organisms, such as human. The Mann-Whitney U test is commonly employed in this scenario despite the assumptions of the test not being met, leading to unreliable and generally underpowered results. Permutation tests are also commonly employed for this purpose, but are computationally burdensome and are not tractable for obtaining small P values or for multiple comparisons.

Results

We present an exact test for the null hypothesis that gene set membership is independent of the quantitative gene feature of interest. We derive an analytic expression for the randomization distribution of the median of the quantitative feature under the null hypothesis. Efficient implementation permits calculation of precise P values of arbitrary magnitude and makes thousands of simultaneous tests of transcriptome-sized gene sets computationally tractable. The flexibility of the hypothesis testing framework presented permits extension to a variety of related tests commonly found in genomics. The exact test is used to identify signatures of translation control and protein function in the human genome.

Availability and implementation

The exact test presented here is implemented in R in the package kpmt available on CRAN.

Contact

map2085@med.cornell.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

HIP1R targets PD-L1 to lysosomal degradation to alter T cell-mediated cytotoxicity

Expression of programmed cell death 1 (PD-1) ligand 1 (PD-L1) protects tumor cells from T cell-mediated immune surveillance, and immune checkpoint blockade (ICB) therapies targeting PD-1 and PD-L1 have exhibited significant clinical benefits. However, the relatively low response rate and observed ICB resistance highlight the need to understand the molecular regulation of PD-L1. Here we show that HIP1R targets PD-L1 to lysosomal degradation to alter T cell-mediated cytotoxicity. HIP1R physically interacts with PD-L1 and delivers PD-L1 to the lysosome through a lysosomal targeting signal. Depletion of HIP1R in tumor cells caused PD-L1 accumulation and suppressed T cell-mediated cytotoxicity. A rationally designed peptide (PD-LYSO) incorporating the lysosome-sorting signal and the PD-L1-binding sequence of HIP1R successfully depleted PD-L1 expression in tumor cells. Our results identify the molecular machineries governing the lysosomal degradation of PD-L1 and exemplify the development of a chimeric peptide for targeted degradation of PD-L1 as a crucial anticancer target.

The PGRS Domain of Mycobacterium tuberculosis PE_PGRS Protein Rv0297 Is Involved in Endoplasmic Reticulum Stress-Mediated Apoptosis through Toll-Like Receptor 4

The genome of Mycobacterium tuberculosis, the causal organism of tuberculosis (TB), encodes a unique protein family known as the PE/PPE/PGRS family, present exclusively in the genus Mycobacterium and nowhere else in the living kingdom, with largely unexplored functions. We describe the functional significance of the PGRS domain of Rv0297, a member of this family. In silico analyses revealed the presence of intrinsically disordered stretches and putative endoplasmic reticulum (ER) localization signals in the PGRS domain of Rv0297 (Rv0297PGRS). The PGRS domain aids in ER localization, which was shown by infecting macrophage cells with M. tuberculosis and by overexpressing the protein by transfection in macrophage cells followed by activation of the unfolded protein response, as evident from increased expression of GRP78/GRP94 and CHOP/ATF4, leading to disruption of intracellular Ca²⁺ homeostasis and increased nitric oxide (NO) and reactive oxygen species (ROS) production. The consequent activation of the effector caspase-8 resulted in apoptosis of macrophages, which was Toll-like receptor 4 (TLR4) dependent. Administration of recombinant Rv0297PGRS (rRv0297PGRS) also exhibited similar effects. These results implicate a hitherto-unknown role of the PGRS domain of the PE_PGRS protein family in ER stress-mediated cell death through TLR4. Since this protein is already known to be present at later stages of infection in human granulomas it points to the possibility of it being employed by M. tuberculosis for its dissemination via an apoptotic mechanism.

Apoptosis is generally thought to be a defense mechanism in protecting the host against Mycobacterium tuberculosis in early stages of infection. However, apoptosis during later stages in lung granulomas may favor the bacterium in disseminating the disease. ER stress has been found to induce apoptosis in TB granulomas, in zones where apoptotic macrophages accumulate in mice and humans. In this study, we report ER stress-mediated apoptosis of host cells by the Rv0297-encoded PE_PGRS5 protein of M. tuberculosis exceptionally present in the pathogenic Mycobacterium genus. The PGRS domain of Rv0297 aids the protein in localizing to the ER and induces the unfolded protein response followed by apoptosis of macrophages. The effect of the Rv0297PGRS domain was found to be TLR4 dependent. This study presents novel insights on the strategies employed by M. tuberculosis to disseminate the disease.

Consistent prediction of GO protein localization

The GO-Cellular Component (GO-CC) ontology provides a controlled vocabulary for the consistent description of the subcellular compartments or macromolecular complexes where proteins may act. Current machine learning-based methods used for the automated GO-CC annotation of proteins suffer from the inconsistency of individual GO-CC term predictions. Here, we present FGGA-CC⁺, a class of hierarchical graph-based classifiers for the consistent GO-CC annotation of protein coding genes at the subcellular compartment or macromolecular complex levels. Aiming to boost the accuracy of GO-CC predictions, we make use of the protein localization knowledge in the GO-Biological Process (GO-BP) annotations to boost the accuracy of GO-CC prediction. As a result, FGGA-CC⁺ classifiers are built from annotation data in both the GO-CC and GO-BP ontologies. Due to their graph-based design, FGGA-CC⁺ classifiers are fully interpretable and their predictions amenable to expert analysis. Promising results on protein annotation data from five model organisms were obtained. Additionally, successful validation results in the annotation of a challenging subset of tandem duplicated genes in the tomato non-model organism were accomplished. Overall, these results suggest that FGGA-CC⁺ classifiers can indeed be useful for satisfying the huge demand of GO-CC annotation arising from ubiquitous high throughout sequencing and proteomic projects.

Identifying metabolic pathways for production of extracellular polymeric substances by the diatom Fragilariopsis cylindrus inhabiting sea ice

Diatoms are significant primary producers in sea ice, an ephemeral habitat with steep vertical gradients of temperature and salinity characterizing the ice matrix environment. To cope with the variable and challenging conditions, sea ice diatoms produce polysaccharide-rich extracellular polymeric substances (EPS) that play important roles in adhesion, cell protection, ligand binding and as organic carbon sources. Significant differences in EPS concentrations and chemical composition corresponding to temperature and salinity gradients were present in sea ice from the Weddell Sea and Eastern Antarctic regions of the Southern Ocean. To reconstruct the first metabolic pathway for EPS production in diatoms, we exposed Fragilariopsis cylindrus, a key bi-polar diatom species, to simulated sea ice formation. Transcriptome profiling under varying conditions of EPS production identified a significant number of genes and divergent alleles. Their complex differential expression patterns under simulated sea ice formation was aligned with physiological and biochemical properties of the cells, and with field measurements of sea ice EPS characteristics. Thus, the molecular complexity of the EPS pathway suggests metabolic plasticity in F. cylindrus is required to cope with the challenging conditions of the highly variable and extreme sea ice habitat.

Optogenetic Tools for Subcellular Applications in Neuroscience

The ability to study cellular physiology using photosensitive, genetically encoded molecules has profoundly transformed neuroscience. The modern optogenetic toolbox includes fluorescent sensors to visualize signaling events in living cells and optogenetic actuators enabling manipulation of numerous cellular activities. Most optogenetic tools are not targeted to specific subcellular compartments but are localized with limited discrimination throughout the cell. Therefore, optogenetic activation often does not reflect context-dependent effects of highly localized intracellular signaling events. Subcellular targeting is required to achieve more specific optogenetic readouts and photomanipulation. Here we first provide a detailed overview of the available optogenetic tools with a focus on optogenetic actuators. Second, we review established strategies for targeting these tools to specific subcellular compartments. Finally, we discuss useful tools and targeting strategies that are currently missing from the optogenetics repertoire and provide suggestions for novel subcellular optogenetic applications.

Biomolecular engineering for nanobio/bionanotechnology

Biomolecular engineering can be used to purposefully manipulate biomolecules, such as peptides, proteins, nucleic acids and lipids, within the framework of the relations among their structures, functions and properties, as well as their applicability to such areas as developing novel biomaterials, biosensing, bioimaging, and clinical diagnostics and therapeutics. Nanotechnology can also be used to design and tune the sizes, shapes, properties and functionality of nanomaterials. As such, there are considerable overlaps between nanotechnology and biomolecular engineering, in that both are concerned with the structure and behavior of materials on the nanometer scale or smaller. Therefore, in combination with nanotechnology, biomolecular engineering is expected to open up new fields of nanobio/bionanotechnology and to contribute to the development of novel nanobiomaterials, nanobiodevices and nanobiosystems. This review highlights recent studies using engineered biological molecules (e.g., oligonucleotides, peptides, proteins, enzymes, polysaccharides, lipids, biological cofactors and ligands) combined with functional nanomaterials in nanobio/bionanotechnology applications, including therapeutics, diagnostics, biosensing, bioanalysis and biocatalysts. Furthermore, this review focuses on five areas of recent advances in biomolecular engineering: (a) nucleic acid engineering, (b) gene engineering, (c) protein engineering, (d) chemical and enzymatic conjugation technologies, and (e) linker engineering. Precisely engineered nanobiomaterials, nanobiodevices and nanobiosystems are anticipated to emerge as next-generation platforms for bioelectronics, biosensors, biocatalysts, molecular imaging modalities, biological actuators, and biomedical applications.

Extent of pre-translational regulation for the control of nucleocytoplasmic protein localization

Background

Appropriate protein subcellular localization is essential for proper cellular function. Central to the regulation of protein localization are protein targeting motifs, stretches of amino acids serving as guides for protein entry in a specific cellular compartment. While the use of protein targeting motifs is modulated in a post-translational manner, mainly by protein conformational changes and post-translational modifications, the presence of these motifs in proteins can also be regulated in a pre-translational manner. Here, we investigate the extent of pre-translational regulation of the main signals controlling nucleo-cytoplasmic traffic: the nuclear localization signal (NLS) and the nuclear export signal (NES).

Results

Motif databases and manual curation of the literature allowed the identification of 175 experimentally validated NLSs and 120 experimentally validated NESs in human. Following mapping onto annotated transcripts, these motifs were found to be modular, most (73 % for NLS and 88 % for NES) being encoded entirely in only one exon. The presence of a majority of these motifs is regulated in an alternative manner at the transcript level (61 % for NLS and 72 % for NES) while the remaining motifs are present in all coding isoforms of their encoding gene. NLSs and NESs are pre-translationally regulated using four main mechanisms: alternative transcription/translation initiation, alternative translation termination, alternative splicing of the exon encoding the motif and frameshift, the first two being by far the most prevalent mechanisms. Quantitative analysis of the presence of these motifs using RNA-seq data indicates that inclusion of these motifs can be regulated in a tissue-specific and a combinatorial manner, can be altered in disease states in a directed way and that alternative inclusion of these motifs is often used by proteins with diverse interactors and roles in diverse pathways, such as kinases.

Conclusions

The pre-translational regulation of the inclusion of protein targeting motifs is a prominent and tightly-regulated mechanism that adds another layer in the control of protein subcellular localization.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2854-4) contains supplementary material, which is available to authorized users.

Mislocalization-related disease gene discovery using gene expression based computational protein localization prediction

Protein sorting is an important mechanism for transporting proteins to their target subcellular locations after their synthesis. Mutations on genes may disrupt the well regulated protein sorting process, leading to a variety of mislocation related diseases. This paper proposes a methodology to discover such disease genes based on gene expression data and computational protein localization prediction. A kernel logistic regression based algorithm is used to successfully identify several candidate cancer genes which may cause cancers due to their mislocation within the cell. Our results also showed that compared to the gene co-expression network defined on Pearson correlation coefficients, the nonlinear Maximum Correlation Coefficients (MIC) based co-expression network give better results for subcellular localization prediction.