Efficient unfolding pattern recognition in single molecule force spectroscopy data

BackgroundSingle-molecule force spectroscopy (SMFS) is a technique that measures the force necessary to unfold a protein. SMFS experiments generate Force-Distance (F-D) curves. A statistical analysis of a set of F-D curves reveals different unfolding pathways. Information on protein structure, conformation, functional states, and inter- and intra-molecular interactions can be derived.ResultsIn the present work, we propose a pattern recognition algorithm and apply our algorithm to datasets from SMFS experiments on the membrane protein bacterioRhodopsin (bR). We discuss the unfolding pathways found in bR, which are characterised by main peaks and side peaks. A main peak is the result of the pairwise unfolding of the transmembrane helices. In contrast, a side peak is an unfolding event in the alpha-helix or other secondary structural element. The algorithm is capable of detecting side peaks along with main peaks.Therefore, we can detect the individual unfolding pathway as the sequence of events labeled with their occurrences and co-occurrences special to bR\u27s unfolding pathway. We find that side peaks do not co-occur with one another in curves as frequently as main peaks do, which may imply a synergistic effect occurring between helices. While main peaks co-occur as pairs in at least 50% of curves, the side peaks co-occur with one another in less than 10% of curves. Moreover, the algorithm runtime scales well as the dataset size increases.ConclusionsOur algorithm satisfies the requirements of an automated methodology that combines high accuracy with efficiency in analyzing SMFS datasets. The algorithm tackles the force spectroscopy analysis bottleneck leading to more consistent and reproducible results

Up-regulated expression of LAMP2 and autophagy activity during neuroendocrine differentiation of prostate cancer LNCaP cells

Neuroendocrine (NE) prostate cancer (PCa) is a highly aggressive subtype of prostate cancer associated with resistance to androgen ablation therapy. In this study, we used LNCaP prostate cancer cells cultured in a serum-free medium for 6 days as a NE model of prostate cancer. Serum deprivation increased the expression of NE markers such as neuron-specific enolase (NSE) and βIII tubulin (βIII tub) and decreased the expression of the androgen receptor protein in LNCaP cells. Using cDNA microarrays, we compared gene expression profiles of NE cells and non-differentiated LNCaP cells. We identified up-regulation of 155 genes, among them LAMP2, a lysosomal membrane protein involved in lysosomal stability and autophagy. We then confirmed up-regulation of LAMP2 in NE cells by qRT-PCR, Western blot and confocal microscopy assays, showing that mRNA up-regulation correlated with increased levels of LAMP2 protein. Subsequently, we determined autophagy activity in NE cells by assessing the protein levels of SQSTM/p62 and LC3 by Western blot and LC3 and Atg5 mRNAs content by qRT-PCR. The decreased levels of SQSTM/p62 was accompanied by an enhanced expression of LC3 and ATG5, suggesting activation of autophagy in NE cells. Blockage of autophagy with 1μM AKT inhibitor IV, or by silencing Beclin 1 and Atg5, prevented NE cell differentiation, as revealed by decreased levels of the NE markers. In addition, AKT inhibitor IV as well as Beclin1 and Atg5 kwockdown attenuated LAMP2 expression in NE cells. On the other hand, LAMP2 knockdown by siRNA led to a marked blockage of autophagy, prevention of NE differentiation and decrease of cell survival. Taken together, these results suggest that LAMP2 overexpression assists NE differentiation of LNCaP cells induced by serum deprivation and facilitates autophagy activity in order to attain the NE phenotype and cell survival. LAMP2 could thus be a potential biomarker and potential target for NE prostate cancer

Comparative Study of Tumor Targeting and Biodistribution of pH (Low) Insertion Peptides (pHLIP® Peptides) Conjugated with Different Fluorescent Dyes

Purpose Acidification of extracellular space promotes tumor development, progression, and invasiveness. pH (low) insertion peptides (pHLIP® peptides) belong to the class of pH-sensitive membrane peptides, which target acidic tumors and deliver imaging and/or therapeutic agents to cancer cells within tumors. Procedures Ex vivo fluorescent imaging of tissue and organs collected at various time points after administration of different pHLIP® variants conjugated with fluorescent dyes of various polarity was performed. Methods of multivariate statistical analyses were employed to establish classification between fluorescently labeled pHLIP® variants in multidimensional space of spectral parameters. Results The fluorescently labeled pHLIP® variants were classified based on their biodistribution profile and ability of targeting of primary tumors. Also, submillimeter-sized metastatic lesions in lungs were identified by ex vivo imaging after intravenous administration of fluorescent pHLIP® peptide. Conclusions Different cargo molecules conjugated with pHLIP® peptides can alter biodistribution and tumor targeting. The obtained knowledge is essential for the design of novel pHLIP®-based diagnostic and therapeutic agents targeting primary tumors and metastatic lesions

Mechanistic studies of the biogenesis and folding of outer membrane proteins in vitro and in vivo: what have we learned to date?

Research into the mechanisms by which proteins fold into their native structures has been on-going since the work of Anfinsen in the 1960s. Since that time, the folding mechanisms of small, water-soluble proteins have been well characterised. By contrast, progress in understanding the biogenesis and folding mechanisms of integral membrane proteins has lagged significantly because of the need to create a membrane mimetic environment for folding studies in vitro and the difficulties in finding suitable conditions in which reversible folding can be achieved. Improved knowledge of the factors that promote membrane protein folding and disfavour aggregation now allows studies of folding into lipid bilayers in vitro to be performed. Consequently, mechanistic details and structural information about membrane protein folding are now emerging at an ever increasing pace. Using the panoply of methods developed for studies of the folding of water-soluble proteins. This review summarises current knowledge of the mechanisms of outer membrane protein biogenesis and folding into lipid bilayers in vivo and in vitro and discusses the experimental techniques utilised to gain this information. The emerging knowledge is beginning to allow comparisons to be made between the folding of membrane proteins with current understanding of the mechanisms of folding of water-soluble proteins

The α-ketoglutarate dehydrogenase complex in cancer metabolic plasticity

Deregulated metabolism is a well-established hallmark of cancer. At the hub of various metabolic pathways deeply integrated within mitochondrial functions, the α-ketoglutarate dehydrogenase complex represents a major modulator of electron transport chain activity and tricarboxylic acid cycle (TCA) flux, and is a pivotal enzyme in the metabolic reprogramming following a cancer cell’s change in bioenergetic requirements. By contributing to the control of α-ketoglutarate levels, dynamics, and oxidation state, the α-ketoglutarate dehydrogenase is also essential in modulating the epigenetic landscape of cancer cells. In this review, we will discuss the manifold roles that this TCA enzyme and its substrate play in cancer

Classifying the evolutionary and ecological features of neoplasms

The consensus conference was supported by Wellcome Genome Campus Advanced Courses and Scientific Conferences. C.C.M. is supported in part by US NIH grants P01 CA91955, R01 CA149566, R01 CA170595, R01 CA185138 and R01 CA140657 as well as CDMRP Breast Cancer Research Program Award BC132057. M.J. is supported by NIH grant K99CA201606. K.S.A. is supported by NCI 5R21 CA196460. K. Polyak is supported by R35 CA197623, U01 CA195469, U54 CA193461, and the Breast Cancer Research Foundation. K.J.P. is supported by NIH grants CA143803, CA163124, CA093900 and CA143055. D.P. is supported by the European Research Council (ERC-617457- PHYLOCANCER), the Spanish Ministry of Economy and Competitiveness (BFU2015-63774-P) and the Education, Culture and University Development Department of the Galician Government. K.S.A. is supported in part by the Breast Cancer Research Foundation and NCI R21CA196460. C.S. is supported by the Royal Society, Cancer Research UK (FC001169), the UK Medical Research Council (FC001169), and the Wellcome Trust (FC001169), NovoNordisk Foundation (ID 16584), the Breast Cancer Research Foundation (BCRF), the European Research Council (THESEUS) and Marie Curie Network PloidyNet. T.A.G. is a Cancer Research UK fellow and a Wellcome Trust funded Investigator. E.S.H. is supported by R01 CA185138-01 and W81XWH-14-1-0473. M.Gerlinger is supported by Cancer Research UK and The Royal Marsden/ICR National Institute of Health Research Biomedical Research Centre. M.Ge., M.Gr., Y.Y., and A.So. were also supported in part by the Wellcome Trust [105104/Z/14/Z]. J.D.S. holds the Edward B. Clark, MD Chair in Pediatric Research, and is supported by the Primary Children's Hospital (PCH) Pediatric Cancer Research Program, funded by the Intermountain Healthcare Foundation and the PCH Foundation. A.S. is supported by the Chris Rokos Fellowship in Evolution and Cancer. Y.Y. is a Cancer Research UK fellow and supported by The Royal Marsden/ICR National Institute of Health Research Biomedical Research Centre. E.S.H. was supported in part by PCORI grants 1505–30497 and 1503–29572, NIH grants R01 CA185138, T32 CA093245, and U10 CA180857, CDMRP Breast Cancer Research Program Award BC132057, a CRUK Grand Challenge grant, and the Breast Cancer Research Foundation. A.R.A.A. was funded in part by NIH grant U01CA151924. A.R.A.A., R.G. and J.S.B. were funded in part by NIH grant U54CA193489

One β Hairpin Follows the Other: Exploring Refolding Pathways and Kinetics of the Transmembrane β-Barrel Protein OmpG

The β-barrel-forming outer-membrane protein G (OmpG) from E. coli can be folded into the native lipid membrane by using single-molecule force spectroscopy. Surprisingly, single β strands do not refold individually but as β hairpins that refold consecutively until the entire β-barrel membrane protein is refolded. This mechanism significantly advances the understanding of current folding models of β-barrel proteins

Local contact inhibition leads to universal principles of cell population growth

Cancer cell population dynamics often exhibit remarkably replicable, universal laws despite their underlying heterogeneity. Mechanistic explanations of universal cell population growth remain partly unresolved to this day, whereby population feedback between the microscopic and mesoscopic configurations can lead to macroscopic growth laws. We here present a unification under density-dependent birth events via contact inhibition. We consider five classical tumor growth laws: exponential, generalized logistic, Gompertz, radial growth, and fractal growth, which can be seen as manifestations of a single microscopic model. Our theory is substantiated by agent based simulations and can explain growth curve differences in experimental data from in vitro cancer cell population growth. Thus, our framework offers a possible explanation for the large number of mean-field laws that can adequately capture seemingly unrelated cancer or microbial growth dynamics

Mix and match: phenotypic coexistence as a key facilitator of cancer invasion

Invasion of healthy tissue is a defining feature of malignant tumours. Traditionally, invasion is thought to be driven by cells that have acquired all the necessary traits to overcome the range of biological and physical defences employed by the body. However, in light of the ever-increasing evidence for geno- and phenotypic intra-tumour heterogeneity, an alternative hypothesis presents itself: could invasion be driven by a collection of cells with distinct traits that together facilitate the invasion process? In this paper, we use a mathematical model to assess the feasibility of this hypothesis in the context of acid-mediated invasion. We assume tumour expansion is obstructed by stroma which inhibits growth and extra-cellular matrix (ECM) which blocks cancer cell movement. Further, we assume that there are two types of cancer cells: (i) a glycolytic phenotype which produces acid that kills stromal cells and (ii) a matrix-degrading phenotype that locally remodels the ECM. We extend the Gatenby–Gawlinski reaction–diffusion model to derive a system of five coupled reaction–diffusion equations to describe the resulting invasion process. We characterise the spatially homogeneous steady states and carry out a simulation study in one spatial dimension to determine how the tumour develops as we vary the strength of competition between the two phenotypes. We find that overall tumour growth is most extensive when both cell types can stably coexist, since this allows the cells to locally mix and benefit most from the combination of traits. In contrast, when inter-species competition exceeds intra-species competition the populations spatially separate and invasion arrests either: (i) rapidly (matrix-degraders dominate) or (ii) slowly (acid-producers dominate). Overall, our work demonstrates that the spatial and ecological relationship between a heterogeneous population of tumour cells is a key factor in determining their ability to cooperate. Specifically, we predict that tumours in which different phenotypes coexist stably are more invasive than tumours in which phenotypes are spatially separated

Evolvability of cancer-associated genes under APOBEC3A/B selection

Summary: Evolvability is an emergent hallmark of cancer that depends on intra-tumor heterogeneity and genetic variation. Mutations generated by APOBEC3 contribute to genetic variation and tumor evolvability. However, the influence of APOBEC3 on the evolvability of the genome and its differential impact on cancer genes versus non-cancer genes remains unclear. Analyzing over 40,000 human protein-coding transcripts, we identified distinct distribution patterns of APOBEC3A/B TC motifs between cancer and non-cancer genes, suggesting unique associations with cancer. Studying a bat species with numerous APOBEC3 genes, we found distinct motif patterns in orthologs of cancer genes compared to non-cancer genes, as in humans, suggesting APOBEC3 evolution to reduce impacts on the genome rather than the converse. Simulations confirmed that APOBEC3-induced heterogeneity enhances cancer evolution through bimodal patterns of mutations in certain classes of genes. Our results suggest the bimodal distribution of APOBEC-induced mutations can significantly increase cancer heterogeneity