Biology subjects

Mohamed, A.

Publications and source records attributed to Mohamed, A..

44 records · Page 3Linked to original sources

bioRxiv2019

Concurrent lipidomics and proteomics on malignant plasma cells from multiple myeloma patients: Probing the lipid metabolome

BackgroundMultiple myeloma (MM) is a hematological malignancy characterized by the clonal expansion of malignant plasma cells. Though durable remissions are possible, MM is considered incurable, with relapse occurring in almost all patients. There has been limited data reported on the lipid metabolism changes in plasma cells during MM progression. Here, we evaluated the feasibility of concurrent lipidomics and proteomics analyses from patient plasma cells, and report these data on a limited number of patient samples, demonstrating the feasibility of the method, and establishing hypotheses to be evaluated in the future. MethodsPlasma cells were purified from fresh bone marrow aspirates using CD138 microbeads. Proteins and lipids were extracted using a bi-phasic solvent system with methanol, methyl tert-butyl ether, and water. Untargeted proteomics, untargeted and targeted lipidomics were performed on 7 patient samples using liquid chromatography-mass spectrometry. Two comparisons were conducted: high versus low risk; relapse versus newly diagnosed. Proteins and pathways enriched in the relapsed group was compared to a public transcriptomic dataset from Multiple Myeloma Research Consortium reference collection (n=222) at gene and pathways level. ResultsFrom one million purified plasma cells, we were able to extract material and complete untargeted ([~]6000 and [~]3600 features in positive and negative mode respectively) and targeted lipidomics (313 lipids), as well as untargeted proteomics analysis ([~]4100 reviewed proteins). Comparative analyses revealed limited differences between high and low risk groups (according to the standard clinical criteria), hence we focused on drawing comparisons between the relapsed and newly diagnosed patients. Untargeted and targeted lipidomics indicated significant down-regulation of phosphatidylcholines (PCs) in relapsed MM. Although there was limited overlap of the differential proteins/transcripts, 76 significantly enriched pathways in relapsed MM were common between proteomics and transcriptomics data. Further evaluation of transcriptomics data for lipid metabolism network revealed enriched correlation of PC, ceramide, cardiolipin, arachidonic acid and cholesterol metabolism pathways to be exclusively correlated among relapsed but not in newly-diagnosed patients. ConclusionsThis study establishes the feasibility and workflow to conduct integrated lipidomics and proteomics analyses on patient-derived plasma cells. Potential lipid metabolism changes associated with MM relapse warrant further investigation.

systems biology↗

bioRxiv2019

Transcriptomic insights into the establishment of coral-algal symbioses from the symbiont perspective

Despite the ecological significance of the mutualistic relationship between Symbiodiniaceae and reef-building corals, the molecular machinery underpinning the establishment of this relationship is not well understood. This is especially true of the symbiont side, as previous attempts to understand the interaction between coral larvae and Symbiodiniaceae have focused nearly exclusively on the host. In the current study, Acropora tenuis planula larvae were exposed to a compatible strain of Symbiodiniaceae (Cladocopium) and the transcriptomic landscape of the symbiont profiled at 3, 12, 48 and 72 h post-exposure using RNA-Seq. The transcriptomic response of Cladocopium to the symbiotic state was complex, the most obvious feature being an extensive and generalised downregulation of gene expression. Included in this \"symbiosis-derived transcriptional repression\" were a range of stress response and immune-related genes. In contrast, genes implicated in metabolism were upregulated in the symbiotic state. Consistent with previous ecological studies, this transcriptomic response of Cladocopium implied that active translocation of metabolites to the host occurred, and thus that the mutualistic relationship can be established at the larval stage. This study provides novel insights into the transcriptomic remodelling that occurs in Symbiodiniaceae, with important implications for understanding the establishment of symbiosis between corals and their dinoflagellate partners.

genomics↗

bioRxiv2019

Genetic Polymorphisms and Molecular Mechanisms Mediating Oncolytic Potency of Reovirus Strains

The Dearing strain of Mammalian orthoreovirus (T3D) is undergoing clinical trials as an oncolytic virotherapeutic agent. In this study, a comprehensive phenotypic and genetic comparison of T3D virus stocks from various laboratories and commercial sources revealed that T3D laboratory strains differ substantially in their oncolytic activities in vitro and in vivo. Superior replication of the most-oncolytic T3D lab strain was attributed to several mechanistic advantages: virus-cell binding, viral RNA transcriptase activity, viral inclusion morphology, and differential activation of RIG-I versus NF{kappa}B-dependent signalling pathways. Viral S4, M1 and L3 gene segments were each independently associated with a distinct mechanistic advantage. Furthermore, the specific missense polymorphisms that governed replication potency were identified, and utilized to generate a hybrid of T3D laboratory strains with further-augmented replication in tumor cells. Together, the results depict an elaborate balance between reovirus replication and host-cell signaling to achieve optimal oncolytic reovirus efficacy.

microbiology↗

bioRxiv2018

Habitat-Net: Segmentation of habitat images using deep learning

Understanding environmental factors that influence forest health, as well as the occurrence and abundance of wildlife, is a central topic in forestry and ecology. However, the manual processing of field habitat data is time-consuming and months are often needed to progress from data collection to data interpretation. Computer-assisted tools, such as deep-learning applications can significantly shortening the time to process the data while maintaining a high level of accuracy. Here, we propose Habitat-Net: a novel method based on Convolutional Neural Networks (CNN) to segment habitat images of tropical rainforests. Habitat-Net takes color images as input and after multiple layers of convolution and deconvolution, produces a binary segmentation of the input image. We worked on two different types of habitat datasets that are widely used in ecological studies to characterize the forest conditions: canopy closure and understory vegetation. We trained the model with 800 canopy images and 700 understory images separately and then used 149 canopy and 172 understory images to test the performance of Habitat-Net. We compared the performance of Habitat-Net with a simple threshold based method, a manual processing by a second researcher and a CNN approach called U-Net upon which Habitat-Net is based. Habitat-Net, U-Net and simple thresholding reduced total processing time to milliseconds per image, compared to 45 seconds per image for manual processing. However, the higher mean Dice coefficient of Habitat-Net (0.94 for canopy and 0.95 for understory) indicates that accuracy of Habitat-Net is higher than that of both the simple thresholding (0.64, 0.83) and U-Net (0.89, 0.94). Habitat-Net will be of great relevance for ecologists and foresters, who need to monitor changes in their forest structures. The automated workflow not only reduces the time, it also standardizes the analytical pipeline and, thus, reduces the degree of uncertainty that would be introduced by manual processing of images by different people (either over time or between study sites). Furthermore, it provides the opportunity to collect and process more images from the field, which might increase the accuracy of the method. Although datasets from other habitats might need an annotated dataset to first train the model, the overall time required to process habitat photos will be reduced, particularly for large projects.

ecology↗

bioRxiv2018

Shifting up a gear with iDNA: from mammal detection events to standardized surveys

O_LIInvertebrate-derived DNA (iDNA), in combination with high throughput sequencing, has been proposed as a cost-efficient and powerful tool to survey vertebrate species. Previous studies, however, have only provided evidence that vertebrates can be detected using iDNA, but have not taken the next step of placing these detection events within a statistical framework that allows for robust biodiversity assessments.\nC_LIO_LIHere, we compare concurrent iDNA and camera-trap surveys. Leeches were repeatedly collected in close vicinity to 64 camera-trap stations in Sabah, Malaysian Borneo. We analyze iDNA-derived mammalian detection events in a modern occupancy model that accounts for imperfect detection and compare the results with those from occupancy models parameterized with camera-trap-derived detection events. We also combine leech-iDNA and camera-trap data in a single occupancy model.\nC_LIO_LIWe found consistent estimates of occupancy probabilities produced by our camera-trap and leech datasets. This indicates that the metabarcoding of leech-iDNA method provides reasonable estimates of occupancy and can be a suitable method for studying and monitoring mammal species in tropical rainforests. However, we also show that a more extensive collection of leeches would be needed to assess mammal biodiversity with a similar robustness as with camera traps. As certain taxa were only detected in leeches, we see great potential in complementing camera-trap studies with the iDNA approach, as long as the collection of leeches follows a similar robust and standardized sampling scheme.\nC_LIO_LISynthesis and applications. The approach we describe here is not restricted to the processing of leech samples, but can be used for the analysis of other iDNA and environmental DNA (eDNA) data. Our study is the first step to shift the application of e/iDNA studies from opportunistic ad-hoc collections to systematic surveys required for long-term wildlife populations and biodiversity monitoring programs.\nC_LI

ecology↗

bioRxiv2018

Design of an epitope-based peptide vaccine against Cryptococcus neoformans

IntroductionThis study aimed to design an immunogenic epitope for Cryptococcus neoformans the etiological agent of cryptococcosis using in silico simulations, for epitope prediction, we selected the mannoprotein antigen MP88 which its known to induce protective immunity.\n\nMaterial & methodA total of 39 sequences of MP88 protein with length 378 amino acids were retrieved from the National Center for Biotechnology Information database (NCBI) in the FASTA format were used to predict antigenic B-cell and T cell epitopes via different bioinformatics tools at Immune Epitope Database and Analysis Resource (IEDB). The tertiary structure prediction of MP88 was created in RaptorX, and visualized by UCSF Chimera software.\n\nResultA Conserved B-cell epitopes AYSTPA, AYSTPAS, PASSNCK, and DSAYPP have displayed the most promising B cell epitopes. While the YMAADQFCL, VSYEEWMNY and FQQRYTGTF they represent the best candidates T-cell conserved epitopes, the 9-mer epitope YMAADQFCL display the greater interact with 9 MHC-I alleles and HLA-A*02:01 alleles have the best interaction with an epitope. The VSYEEWMNY and FQQRYTGTF they are non-allergen while YMAADQFCL was an allergen. For MHC class II peptide binding prediction, the YARLLSLNA, ISYGTAMAV and INQTSYARL represent the most Three highly binding affinity core epitopes. The core epitope INQTSYARL was found to interact with 14 MHC-II. The allergenicity prediction reveals ISYGTAMAV, INQTSYARL were non-allergen and YARLLSLNA was an allergen. Regarding population coverage the YMAADQFCL exhibit, a higher percentage among the world (69.75%) and the average population coverage was 93.01%. In MHC-II, ISYGTAMAV epitope reveal a higher percentage (74.39%) and the average population coverage was (81.94%). This successfully designed a peptide vaccine against Cryptococcus neoformans open up a new horizon in Cryptococcus neoformans research; the results require validation by in vitro and in vivo experiments.

bioinformatics↗

bioRxiv2018

RaftProt V2: understanding membrane microdomain function through lipid raft proteomes

Cellular membranes feature dynamic submicrometer-scale lateral membrane domainsvariously referred to as lipid rafts, membrane rafts or glycosphingolipid-enriched microdomains (GEM). In order to understand the molecular functions of lipid rafts, numerous studies have utilized various biochemical methods to isolate and examine the protein composition of membrane rafts. However, interpretation of individual raft proteomics studies are confounded by the limitations of isolation methods and the dynamic nature of rafts. Knowledge-based approaches can facilitate biological data interpretation by integrating experimental evidence from existing studies. To this end, we previously developed RaftProt (http://lipid-raft-database.di.uq.edu.au/), a searchable database of mammalian lipid raft-associated proteins. Despite being a valuable and highly used resource, improvements in search capabilities and visualisation were still needed. Here, we present RaftProt V2 (http://raftprot.org), an improved update of RaftProt, enabling interrogation and integration of datasets at the cell/tissue type and UniRef/Gene level. Besides the addition of new datasets and re-mapping of all entries to both UniProt and UniRef IDs, we have annotated the level of experimental evidence for each protein entry. The search engine now allows for multiple protein or experiment searches where correlations, interactions or overlaps can be investigated. The web-interface has been completely re-designed and offers new interactive tools for data and subset selection, correlation analysis and network visualization. Overall, RaftProt aims to advance our understanding of lipid raft function by revealing the proteomes and pathways that are associated with membrane microdomains in diverse tissue and conditions.\n\nDatabase URL: http://raftprot.org

bioinformatics↗

bioRxiv2016

UNC-5 (UNC5) Regulates the Length and Number of Processes that Caenorhabditis elegans Neurons Can Develop

Neurons extend processes that vary in number, length, and direction of outgrowth. Extracellular cues help determine outgrowth patterns. In Caenorhabditis elegans, neurons respond to the extracellular UNC-6 (netrin) cue via UNC-40 (DCC) and UNC-5 (UNC5) receptors. Previously we presented evidence that UNC-40 asymmetric localization at the plasma membrane is self-organizing and that UNC-40 can localize and mediate outgrowth at randomly selected sites. We also postulate that the process is statistically dependent, i.e. if the probability of outgrowth at one site changes then the probability at another site(s) must also change. Over time, the direction of outgrowth activity fluctuates across the membrane. A probability distribution describes the likelihood of outgrowth in each direction. Random walk modeling predicts that the degree to which the direction of outgrowth fluctuations affects the outward displacement of the membrane. We predict that extracellular cues create patterns of outgrowth by differentially affecting the degree to which the direction of outgrowth activity fluctuates along the membrane. This produces different rates of outgrowth along the surface and creates patterns of extension. Here we present evidence that UNC-5 (UNC5) receptor activity regulates UNC-40 asymmetric localization and the patterning of outgrowth. We show that unc-5 mutations alter UNC-40 asymmetric localization and the patterns of outgrowth that neurons develop. Genetic interactions suggest UNC-5 acts through the UNC-53 (NAV2) cytoplasmic protein to regulate UNC-40 asymmetric localization in response to both the UNC-6 and EGL-20 (wnt) extracellular cues.

neuroscience↗