Single-Cell Genetic Analysis Using Automated Microfluidics to Resolve Somatic Mosaicism

Somatic mosaicism occurs throughout normal development and contributes to numerous disease etiologies, including tumorigenesis and neurological disorders. Intratumor genetic heterogeneity is inherent to many cancers, creating challenges for effective treatments. Unfortunately, analysis of bulk DNA masks subclonal phylogenetic architectures created by the acquisition and distribution of somatic mutations amongst cells. As a result, single-cell genetic analysis is becoming recognized as vital for accurately characterizing cancers. Despite this, methods for single-cell genetics are lacking. Here we present an automated microfluidic workflow enabling efficient cell capture, lysis, and whole genome amplification (WGA). We find that ~90% of the genome is accessible in single cells with improved uniformity relative to current single-cell WGA methods. Allelic dropout (ADO) rates were limited to 13.75% and variant false discovery rates (SNV FDR) were 4.11x10^-6, on average. Application to ER-/PR-/HER2+ breast cancer cells and matched normal controls identified novel mutations that arose in a subpopulation of cells and effectively resolved the segregation of known cancer-related mutations with single-cell resolution. Finally, we demonstrate effective cell classification using mutation profiles with 10X average exome coverage depth per cell. Our data demonstrate an efficient automated microfluidic platform for single-cell WGA that enables the resolution of somatic mutation patterns in single cells.     

Single-cell paired-end genome sequencing reveals structural variation per cell cycle

The nature and pace of genome mutation is largely unknown. Because standard methods sequence DNA from populations of cells, the genetic composition of individual cells is lost, de novo mutations in cells are concealed within the bulk signal and per cell cycle mutation rates and mechanisms remain elusive. Although single-cell genome analyses could resolve these problems, such analyses are error-prone because of whole-genome amplification (WGA) artefacts and are limited in the types of DNA mutation that can be discerned. We developed methods for paired-end sequence analysis of single-cell WGA products that enable (i) detecting multiple classes of DNA mutation, (ii) distinguishing DNA copy number changes from allelic WGA-amplification artefacts by the discovery of matching aberrantly mapping read pairs among the surfeit of paired-end WGA and mapping artefacts and (iii) delineating the break points and architecture of structural variants. By applying the methods, we capture DNA copy number changes acquired over one cell cycle in breast cancer cells and in blastomeres derived from a human zygote after in vitro fertilization. Furthermore, we were able to discover and fine-map a heritable inter-chromosomal rearrangement t(1;16)(p36;p12) by sequencing a single blastomere. The methods will expedite applications in basic genome research and provide a stepping stone to novel approaches for clinical genetic diagnosis.     

Confidence-based Somatic Mutation Evaluation and Prioritization

Next generation sequencing (NGS) has enabled high throughput discovery of somatic mutations. Detection depends on experimental design, lab platforms, parameters and analysis algorithms. However, NGS-based somatic mutation detection is prone to erroneous calls, with reported validation rates near 54% and congruence between algorithms less than 50%. Here, we developed an algorithm to assign a single statistic, a false discovery rate (FDR), to each somatic mutation identified by NGS. This FDR confidence value accurately discriminates true mutations from erroneous calls. Using sequencing data generated from triplicate exome profiling of C57BL/6 mice and B16-F10 melanoma cells, we used the existing algorithms GATK, SAMtools and SomaticSNiPer to identify somatic mutations. For each identified mutation, our algorithm assigned an FDR. We selected 139 mutations for validation, including 50 somatic mutations assigned a low FDR (high confidence) and 44 mutations assigned a high FDR (low confidence). All of the high confidence somatic mutations validated (50 of 50), none of the 44 low confidence somatic mutations validated, and 15 of 45 mutations with an intermediate FDR validated. Furthermore, the assignment of a single FDR to individual mutations enables statistical comparisons of lab and computation methodologies, including ROC curves and AUC metrics. Using the HiSeq 2000, single end 50 nt reads from replicates generate the highest confidence somatic mutation call set.     

One Bacterial Cell,One Complete Genome

While the bulk of the finished microbial genomes sequenced to date are derived from cultured bacterial and archaeal representatives, the vast majority of microorganisms elude current culturing attempts, severely limiting the ability to recover complete or even partial genomes from these environmental species. Single cell genomics is a novel culture-independent approach, which enables access to the genetic material of an individual cell. No single cell genome has to our knowledge been closed and finished to date. Here we report the completed genome from an uncultured single cell of Candidatus Sulcia muelleri DMIN. Digital PCR on single symbiont cells isolated from the bacteriome of the green sharpshooter Draeculacephala minerva bacteriome allowed us to assess that this bacteria is polyploid with genome copies ranging from approximately 200–900 per cell, making it a most suitable target for single cell finishing efforts. For single cell shotgun sequencing, an individual Sulcia cell was isolated and whole genome amplified by multiple displacement amplification (MDA). Sanger-based finishing methods allowed us to close the genome. To verify the correctness of our single cell genome and exclude MDA-derived artifacts, we independently shotgun sequenced and assembled the Sulcia genome from pooled bacteriomes using a metagenomic approach, yielding a nearly identical genome. Four variations we detected appear to be genuine biological differences between the two samples. Comparison of the single cell genome with bacteriome metagenomic sequence data detected two single nucleotide polymorphisms (SNPs), indicating extremely low genetic diversity within a Sulcia population. This study demonstrates the power of single cell genomics to generate a complete, high quality, non-composite reference genome within an environmental sample, which can be used for population genetic analyzes.     

Identification of Single Amino Acid Substitutions in Proteogenomics

An important aim of proteogenomics, which combines data of high throughput nucleic acid and protein analysis, is to reliably identify single amino acid substitutions representing a main type of coding genome variants. Exact knowledge of deviations from the consensus genome can be utilized in several biomedical fields, such as studies of expression of mutated proteins in cancer, deciphering heterozygosity mechanisms, identification of neoantigens in anticancer vaccine production, search for RNA editing sites at the level of the proteome, etc. Generation of this new knowledge requires processing of large data arrays from high–resolution mass spectrometry, where information on single–point protein variation is often difficult to extract. Accordingly, a significant problem in proteogenomic analysis is the presence of high levels of false positive results for variant–containing peptides in the produced results. Here we review recently suggested approaches of high quality proteomics data processing that may provide more reliable identification of single amino acid substitutions, especially contrary to residue modifications occurring in vitro and in vivo. Optimized methods for assessment of false discovery rate save instrumental and computational time spent for validation of interesting findings of amino acid polymorphism by orthogonal methods.     

A Simple Strategy for Reducing False Negatives in Calling Variants from Single-Cell Sequencing Data

Due to the growth of interest in single-cell genomics, computational methods for distinguishing true variants from artifacts are highly desirable. While special attention has been paid to false positives in variant or mutation calling from single-cell sequencing data, an equally important but often neglected issue is that of false negatives derived from allele dropout during the amplification of single cell genomes. In this paper, we propose a simple strategy to reduce the false negatives in single-cell sequencing data analysis. Simulation results show that this method is highly reliable, with an error rate of 4.94×10^-5, which is orders of magnitude lower than the expected false negative rate (~34%) estimated from a single-cell exome dataset, though the method is limited by the low SNP density in the human genome. We applied this method to analyze the exome data of a few dozen single tumor cells generated in previous studies, and extracted cell specific mutation information for a small set of sites. Interestingly, we found that there are difficulties in using the classical clonal model of tumor cell growth to explain the mutation patterns observed in some tumor cells.     

Exploration of Genetic Variations through Single‐cell Whole‐genome Sequencing in the Model Ciliate Tetrahymena thermophila

Ciliates are unicellular eukaryotes with separate germline and somatic genomes and diverse life cycles, which make them a unique model to improve our understanding of population genetics through the detection of genetic variations. However, traditional sequencing methods cannot be directly applied to ciliates because the majority are uncultivated. Single‐cell whole‐genome sequencing (WGS) is a powerful tool for studying genetic variation in microbes, but no studies have been performed in ciliates. We compared the use of single‐cell WGS and bulk DNA WGS to detect genetic variation, specifically single nucleotide polymorphisms (SNPs), in the model ciliate Tetrahymena thermophila. Our analyses showed that (i) single‐cell WGS has excellent performance regarding mapping rate and genome coverage but lower sequencing uniformity compared with bulk DNA WGS due to amplification bias (which was reproducible); (ii) false‐positive SNP sites detected by single‐cell WGS tend to occur in genomic regions with particularly high sequencing depth and high rate of C:G to T:A base changes; (iii) SNPs detected in three or more cells should be reliable (an detection efficiency of 83.4–97.4% was obtained for combined data from three cells). This analytical method could be adapted to measure genetic variation in other ciliates and broaden research into ciliate population genetics.     

“Ryanopathies” and RyR2 dysfunctions: can we further decipher them using in vitro human disease models?

The regulation of intracellular calcium (Ca²⁺) homeostasis is fundamental to maintain normal functions in many cell types. The ryanodine receptor (RyR), the largest intracellular calcium release channel located on the sarco/endoplasmic reticulum (SR/ER), plays a key role in the intracellular Ca²⁺ handling. Abnormal type 2 ryanodine receptor (RyR2) function, associated to mutations (ryanopathies) or pathological remodeling, has been reported, not only in cardiac diseases, but also in neuronal and pancreatic disorders. While animal models and in vitro studies provided valuable contributions to our knowledge on RyR2 dysfunctions, the human cell models derived from patients’ cells offer new hope for improving our understanding of human clinical diseases and enrich the development of great medical advances. We here discuss the current knowledge on RyR2 dysfunctions associated with mutations and post-translational remodeling. We then reviewed the novel human cellular technologies allowing the correlation of patient’s genome with their cellular environment and providing approaches for personalized RyR-targeted therapeutics.Subject terms: Ventricular tachycardia, Ventricular tachycardia     

Dominant-Negative Effects of Adult-Onset Huntingtin Mutations Alter the Division of Human Embryonic Stem Cells-Derived Neural Cells

Mutations of the huntingtin protein (HTT) gene underlie both adult-onset and juvenile forms of Huntington’s disease (HD). HTT modulates mitotic spindle orientation and cell fate in mouse cortical progenitors from the ventricular zone. Using human embryonic stem cells (hESC) characterized as carrying mutations associated with adult-onset disease during pre-implantation genetic diagnosis, we investigated the influence of human HTT and of an adult-onset HD mutation on mitotic spindle orientation in human neural stem cells (NSCs) derived from hESCs. The RNAi-mediated silencing of both HTT alleles in neural stem cells derived from hESCs disrupted spindle orientation and led to the mislocalization of dynein, the p150^Glued subunit of dynactin and the large nuclear mitotic apparatus (NuMA) protein. We also investigated the effect of the adult-onset HD mutation on the role of HTT during spindle orientation in NSCs derived from HD-hESCs. By combining SNP-targeting allele-specific silencing and gain-of-function approaches, we showed that a 46-glutamine expansion in human HTT was sufficient for a dominant-negative effect on spindle orientation and changes in the distribution within the spindle pole and the cell cortex of dynein, p150^Glued and NuMA in neural cells. Thus, neural derivatives of disease-specific human pluripotent stem cells constitute a relevant biological resource for exploring the impact of adult-onset HD mutations of the HTT gene on the division of neural progenitors, with potential applications in HD drug discovery targeting HTT-dynein-p150^Glued complex interactions.     

Integrative Analysis of Genome, 3D Genome,and Transcriptome Alterations of Clinical Lung Cancer Samples

Genomic studies of cancer cell alterations, such as mutations, copy number variations (CNVs), and translocations, greatly promote our understanding of the genesis and development of cancers. However, the 3D genome architecture of cancers remains less studied due to the complexity of cancer genomes and technical difficulties. To explore the 3D genome structure in clinical lung cancer, we performed Hi-C experiments using paired normal and tumor cells harvested from patients with lung cancer, combining with RNA sequenceing analysis. We demonstrated the feasibility of studying 3D genome of clinical lung cancer samples with a small number of cells (1 × 10⁴), compared the genome architecture between clinical samples and cell lines of lung cancer, and identified conserved and changed spatial chromatin structures between normal and cancer samples. We also showed that Hi-C data can be used to infer CNVs and point mutations in cancer. By integrating those different types of cancer alterations, we showed significant associations between CNVs, 3D genome, and gene expression. We propose that 3D genome mediates the effects of cancer genomic alterations on gene expression through altering regulatory chromatin structures. Our study highlights the importance of analyzing 3D genomes of clinical cancer samples in addition to cancer cell lines and provides an integrative genomic analysis pipeline for future larger-scale studies in lung cancer and other cancers.     

Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'

Whole genome amplification and sequencing of single microbial cells enables genomic characterization without the need of cultivation ^1-3. Viruses, which are ubiquitous and the most numerous entities on our planet ⁴ and important in all environments ⁵, have yet to be revealed via similar approaches. Here we describe an approach for isolating and characterizing the genomes of single virions called ''Single Virus Genomics'' (SVG). SVG utilizes flow cytometry to isolate individual viruses and whole genome amplification to obtain high molecular weight genomic DNA (gDNA) that can be used in subsequent sequencing reactions.     

A model for random genetic damage directing selection of diploid or aneuploid tumours

Objectives: To test whether genetic instability may determine whether tumours become aneuploid or diploid. Materials and methods: We have identified genes needed for cell survival or replication by combining Affymetrix gene expression array data from 12 experimental cell lines with in silico GEO+GNF and expO databases. Specific loss of heterozygosis (LOHs), chromosomal abnormalities (called derivative chromosomes) and numbers of normal homologues were identified by SNP and SKY analyses. Random gene losses were calculated under the assumption that bi‐allelic MMR gene inactivation causes a 20‐fold increase in rate of gene loss. Results: There were ～1.23 × 10⁴ genes widely dispersed throughout the genome and possibly expressed by all cells for survival or proliferation, many of these genes performed housekeeping functions. Conservation of the genes may explain the complete haploid genomes found for 15 different cell types and derivative chromosomes selectively retained in aneuploid cancer cell lines after LOH formations, and normal homologue losses. Loss of cell survival/replication genes was calculated to be higher in colon stem cells of carriers of MMR gene mutations than carriers of APC gene mutations. Conclusion: Random loss of cell survival/replication genes was calculated to be low enough for colon stem cells with APC gene mutations to ‘select’ LOH and derivative chromosome combinations favouring tumour cell proliferation. However, cell survival/replication gene loss was calculated to be too high for colonic stem cells lacking MMR genes to survive chromosomal instability, explaining why MMR mutations only produce tumours with diploid chromosome cells.     

Next‐generation sequencing (NGS)‐based identification of induced mutations in a doubly mutagenized tomato (Solanum lycopersicum) population

The identification of mutations in targeted genes has been significantly simplified by the advent of TILLING (Targeting Induced Local Lesions In Genomes), speeding up the functional genomic analysis of animals and plants. Next‐generation sequencing (NGS) is gradually replacing classical TILLING for mutation detection, as it allows the analysis of a large number of amplicons in short durations. The NGS approach was used to identify mutations in a population of Solanum lycopersicum (tomato) that was doubly mutagenized by ethylmethane sulphonate (EMS). Twenty‐five genes belonging to carotenoids and folate metabolism were PCR‐amplified and screened to identify potentially beneficial alleles. To augment efficiency, the 600‐bp amplicons were directly sequenced in a non‐overlapping manner in Illumina MiSeq, obviating the need for a fragmentation step before library preparation. A comparison of the different pooling depths revealed that heterozygous mutations could be identified up to 128‐fold pooling. An evaluation of six different software programs (camba , crisp , gatk unified genotyper , lofreq , snver and vipr ) revealed that no software program was robust enough to predict mutations with high fidelity. Among these, crisp and camba predicted mutations with lower false discovery rates. The false positives were largely eliminated by considering only mutations commonly predicted by two different software programs. The screening of 23.47 Mb of tomato genome yielded 75 predicted mutations, 64 of which were confirmed by Sanger sequencing with an average mutation density of 1/367 Kb. Our results indicate that NGS combined with multiple variant detection tools can reduce false positives and significantly speed up the mutation discovery rate.     

High efficiency,Site-specific Transfection of Adherent Cells with siRNA Using Microelectrode Arrays (MEA)

The discovery of RNAi pathway in eukaryotes and the subsequent development of RNAi agents, such as siRNA and shRNA, have achieved a potent method for silencing specific genes^1-8 for functional genomics and therapeutics. A major challenge involved in RNAi based studies is the delivery of RNAi agents to targeted cells. Traditional non-viral delivery techniques, such as bulk electroporation and chemical transfection methods often lack the necessary spatial control over delivery and afford poor transfection efficiencies^9-12. Recent advances in chemical transfection methods such as cationic lipids, cationic polymers and nanoparticles have resulted in highly enhanced transfection efficiencies¹³. However, these techniques still fail to offer precise spatial control over delivery that can immensely benefit miniaturized high-throughput technologies, single cell studies and investigation of cell-cell interactions. Recent technological advances in gene delivery have enabled high-throughput transfection of adherent cells^14-23, a majority of which use microscale electroporation. Microscale electroporation offers precise spatio-temporal control over delivery (up to single cells) and has been shown to achieve high efficiencies^{19, 24-26}. Additionally, electroporation based approaches do not require a prolonged period of incubation (typically 4 hours) with siRNA and DNA complexes as necessary in chemical based transfection methods and lead to direct entry of naked siRNA and DNA molecules into the cell cytoplasm. As a consequence gene expression can be achieved as early as six hours after transfection²⁷. Our lab has previously demonstrated the use of microelectrode arrays (MEA) for site-specific transfection in adherent mammalian cell cultures^17-19. In the MEA based approach, delivery of genetic payload is achieved via localized micro-scale electroporation of cells. An application of electric pulse to selected electrodes generates local electric field that leads to electroporation of cells present in the region of the stimulated electrodes. The independent control of the micro-electrodes provides spatial and temporal control over transfection and also enables multiple transfection based experiments to be performed on the same culture increasing the experimental throughput and reducing culture-to-culture variability. Here we describe the experimental setup and the protocol for targeted transfection of adherent HeLa cells with a fluorescently tagged scrambled sequence siRNA using electroporation. The same protocol can also be used for transfection of plasmid vectors. Additionally, the protocol described here can be easily extended to a variety of mammalian cell lines with minor modifications. Commercial availability of MEAs with both pre-defined and custom electrode patterns make this technique accessible to most research labs with basic cell culture equipment.     

Improving Indel Detection Specificity of the Ion Torrent PGM Benchtop Sequencer

The emergence of benchtop sequencers has made clinical genetic testing using next-generation sequencing more feasible. Ion Torrent''s PGM^TM is one such benchtop sequencer that shows clinical promise in detecting single nucleotide variations (SNVs) and microindel variations (indels). However, the large number of false positive indels caused by the high frequency of homopolymer sequencing errors has impeded PGM^TM''s usage for clinical genetic testing. An extensive analysis of PGM^TM data from the sequencing reads of the well-characterized genome of the Escherichia coli DH10B strain and sequences of the BRCA1 and BRCA2 genes from six germline samples was done. Three commonly used variant detection tools, SAMtools, Dindel, and GATK''s Unified Genotyper, all had substantial false positive rates for indels. By incorporating filters on two major measures we could dramatically improve false positive rates without sacrificing sensitivity. The two measures were: B-Allele Frequency (BAF) and VARiation of the Width of gaps and inserts (VARW) per indel position. A BAF threshold applied to indels detected by UnifiedGenotyper removed ∼99% of the indel errors detected in both the DH10B and BRCA sequences. The optimum BAF threshold for BRCA sequences was determined by requiring 100% detection sensitivity and minimum false discovery rate, using variants detected from Sanger sequencing as reference. This resulted in 15 indel errors remaining, of which 7 indel errors were removed by selecting a VARW threshold of zero. VARW specific errors increased in frequency with higher read depth in the BRCA datasets, suggesting that homopolymer-associated indel errors cannot be reduced by increasing the depth of coverage. Thus, using a VARW threshold is likely to be important in reducing indel errors from data with higher coverage. In conclusion, BAF and VARW thresholds provide simple and effective filtering criteria that can improve the specificity of indel detection in PGM^TM data without compromising sensitivity.     

Effects of salt concentrations and bending energy on the extent of ejection of phage genomes

Recent work has shown that pressures inside dsDNA phage capsids can be as high as many tens of atmospheres; it is this pressure that is responsible for initiation of the delivery of phage genomes to host cells. The forces driving ejection of the genome have been shown to decrease monotonically as ejection proceeds, and hence to be strongly dependent on the genome length. Here we investigate the effects of ambient salts on the pressures inside phage-λ, for the cases of mono-, di-, and tetravalent cations, and measure how the extent of ejection against a fixed osmotic pressure (mimicking the bacterial cytoplasm) varies with cation concentration. We find, for example, that the ejection fraction is halved in 30 mM Mg²⁺ and is decreased by a factor of 10 upon addition of 1 mM spermine. These effects are calculated from a simple model of genome packaging, using DNA-DNA repulsion energies as determined independently from x-ray diffraction measurements on bulk DNA solutions. By comparing the measured ejection fractions with values implied from the bulk DNA solution data, we predict that the bending energy makes the d-spacings inside the capsid larger than those for bulk DNA at the same osmotic pressure.     

A novel method for biodosimetry

Accurate methods for measuring the biological effects of radiation are critical for estimating an individual’s health risk from radiation exposure. We investigated the feasibility of using radiation-induced mutations in repetitive DNA sequences to measure genetic damage caused by radiation exposure. Most repetitive sequences are in non-coding regions of the genome and alterations in these loci are usually not deleterious. Thus, mutations in non-coding repetitive sequences might accumulate, providing a stable molecular record of DNA damage caused by all past exposures. To test this hypothesis, we screened repetitive DNA sequences to identify the loci most sensitive to radiation-induced mutations and then investigated whether these mutations were stable in vivo over time and after multiple exposures. Microsatellite repeat markers were identified that exhibited a linear dose response up to 1 Gy of 1 GeV/nucleon ⁵⁶Fe ions and ¹³⁷Cs gamma rays in mouse and human cells. Short tandem repeats on the Y chromosome and mononucleotide repeats on autosomal chromosomes exhibited significant increases in mutations at ≥ 0.5 Gy of ⁵⁶Fe ions with frequencies averaging 4.3–10.3 × 10⁻³ mutations/locus/Gy/cell, high enough for direct detection of mutations in irradiated cells. A significant increase in radiation-induced mutations in extended mononucleotide repeats was detectible in vivo in mouse blood and cheek samples 10 and 26 weeks after radiation exposure and these mutations were additive over multiple exposures. This study demonstrates the feasibility of a novel method for biodosimetry that is applicable to humans and other species. This new approach should complement existing methods of biodosimetry and might be useful for measuring radiation exposure in circumstances that are not amenable to current methods.     

Assaying the Kinase Activity of LRRK2 in vitro

Leucine Rich Repeat Kinase 2 (LRRK2) is a 2527 amino acid member of the ROCO family of proteins, possessing a complex, multidomain structure including a GTPase domain (termed ROC, for Ras of Complex proteins) and a kinase domain¹. The discovery in 2004 of mutations in LRRK2 that cause Parkinson''s disease (PD) resulted in LRRK2 being the focus of a huge volume of research into its normal function and how the protein goes awry in the disease state^2,3. Initial investigations into the function of LRRK2 focused on its enzymatic activities^4-6. Although a clear picture has yet to emerge of a consistent alteration in these due to mutations, data from a number of groups has highlighted the importance of the kinase activity of LRRK2 in cell death linked to mutations^7,8. Recent publications have reported inhibitors targeting the kinase activity of LRRK2, providing a key experimental tool^9-11. In light of these data, it is likely that the enzymatic properties of LRRK2 afford us an important window into the biology of this protein, although whether they are potential drug targets for Parkinson''s is open to debate.A number of different approaches have been used to assay the kinase activity of LRRK2. Initially, assays were carried out using epitope tagged protein overexpressed in mammalian cell lines and immunoprecipitated, with the assays carried out using this protein immobilised on agarose beads^4,5,7. Subsequently, purified recombinant fragments of LRRK2 in solution have also been used, for example a GST tagged fragment purified from insect cells containing residues 970 to 2527 of LRRK2¹². Recently, Daniëls et al. reported the isolation of full length LRRK2 in solution from human embryonic kidney cells, however this protein is not widely available¹³. In contrast, the GST fusion truncated form of LRRK2 is commercially available (from Invitrogen, see table 1 for details), and provides a convenient tool for demonstrating an assay for LRRK2 kinase activity. Several different outputs for LRRK2 kinase activity have been reported. Autophosphorylation of LRRK2 itself, phosphorylation of Myelin Basic Protein (MBP) as a generic kinase substrate and phosphorylation of an artificial substrate - dubbed LRRKtide, based upon phosphorylation of threonine 558 in Moesin - have all been used, as have a series of putative physiological substrates including α-synuclein, Moesin and 4-EBP^14-17. The status of these proteins as substrates for LRRK2 remains unclear, and as such the protocol described below will focus on using MBP as a generic substrate, noting the utility of this system to assay LRRK2 kinase activity directed against a range of potential substrates.     

A computational workflow for predicting cancer neo-antigens

Neo-antigens presented on cell surface play a pivotal role in the success of immunotherapies. Peptides derived from mutant proteins are thought to be the primary source of neo-antigens presented on the surface of cancer cells. Mutation data from cancer genome sequencing is often used to predict cancer neo-antigens. However, this strategy is associated with significant false positives as many coding mutations may not be expressed at the protein level. Hence, we describe a computational workflow to integrate genomic and proteomic data to predictpotential neo-antigens.