Cover Image,Volume 88, Issue 6

Hsp16.3, a molecular chaperone, plays a vital role in the growth and survival of Mycobacterium tuberculosis inside the host. We previously reported that deletion of three amino acid residues (¹⁴²STN¹⁴⁴) from C-terminal extension (CTE) of Hsp16.3 triggers its structural perturbation and increases its chaperone activity, which reaches its apex upon the deletion of its entire CTE (¹⁴¹RSTN¹⁴⁴). Thus, we hypothesized that Arg141 (R141) and Ser142 (S142) in the CTE of Hsp16.3 possibly hold the key in maintaining its native-like structure and chaperone activity. To test this hypothesis, we generated two deletion mutants in which R141 and S142 were deleted individually (Hsp16.3ΔR141 and Hsp16.3ΔS142) and three substitution mutants in which R141 was replaced by lysine (Hsp16.3R141K), alanine (Hsp16.3R141A), and glutamic acid (Hsp16.3R141E), respectively. Hsp16.3ΔS142 or Hsp16.3R141K mutant has native-like structure and chaperone activity. Deletion of R141 from the CTE (Hsp16.3ΔR141) perturbs the secondary and tertiary structure, lowers the subunit exchange dynamics and decreases the chaperone activity of Hsp16.3. But, the substitution of R141 with alanine (Hsp16.3R141A) or glutamic acid (Hsp16.3R141E) perturbs its secondary and tertiary structure. Surprisingly, such charge tampering of R141 enhances the subunit exchange dynamics and chaperone activity of Hsp16.3. Interestingly, neither the deletion of R141/S142 nor the substitution of R141 with lysine, alanine and glutamic acid affects the oligomeric mass/size of Hsp16.3. Overall, our study suggests that R141 (especially the positive charge on R141) plays a crucial role in maintaining the native-like structure as well as in regulating subunit exchange dynamics and chaperone activity of Hsp16.3.     

Bayesian data integration and variable selection for pan-cancer survival prediction using protein expression data

Accurate prognostic prediction using molecular information is a challenging area of research, which is essential to develop precision medicine. In this paper, we develop translational models to identify major actionable proteins that are associated with clinical outcomes, like the survival time of patients. There are considerable statistical and computational challenges due to the large dimension of the problems. Furthermore, data are available for different tumor types; hence data integration for various tumors is desirable. Having censored survival outcomes escalates one more level of complexity in the inferential procedure. We develop Bayesian hierarchical survival models, which accommodate all the challenges mentioned here. We use the hierarchical Bayesian accelerated failure time model for survival regression. Furthermore, we assume sparse horseshoe prior distribution for the regression coefficients to identify the major proteomic drivers. We borrow strength across tumor groups by introducing a correlation structure among the prior distributions. The proposed methods have been used to analyze data from the recently curated “The Cancer Proteome Atlas” (TCPA), which contains reverse-phase protein arrays–based high-quality protein expression data as well as detailed clinical annotation, including survival times. Our simulation and the TCPA data analysis illustrate the efficacy of the proposed integrative model, which links different tumors with the correlated prior structures.     

Improved protein A resin for antibody capture in a continuous countercurrent tangential chromatography system

Continuous countercurrent tangential chromatography (CCTC) enables steady-state continuous bioprocessing with low-pressure operation and high productivity. CCTC has been applied to initial capture of monoclonal antibodies (mAb) from clarified cell culture harvest and postcapture polishing of mAb; however, these studies were performed with commercial chromatography resins designed for conventional column chromatography. In this study, a small particle size prototype agarose resin (20–25 µm) with lower cross-linking was co-developed with industrial partner Purolite and tested with CCTC. Due to increased binding capacity and faster kinetics, the resulting CCTC process showed more than a 2X increase in productivity, and a 2X reduction in buffer consumption over commercial protein A resins used in previous CCTC studies, as well as more than a 10X productivity increase versus conventional column operation. Single-pass tangential flow filtration was integrated with the CCTC system, enabling simple control of eluate concentration. A scale-up exercise was conducted to provide a quantitative comparison of CCTC and batch column chromatography. These results clearly demonstrate opportunities for using otherwise unpackable soft small particle size resins with CCTC as the core of a continuous bioprocessing platform.     

Reduction of nuclear Y654-p-β-catenin expression through SH3GL2-meditated downregulation of EGFR in chemotolerance TNBC: Clinical and prognostic importance

Triple negative breast cancer (TNBC) originates from a less differentiated ductal cell of breast, which is less sensitive to chemotherapy. The chemotolerance mechanism of TNBC has not yet been studied in detail. For this reason, molecular profiles (expression/genetic/epigenetic) of Y654-p-β-catenin (active) and its kinase epidermal growth factor receptor (EGFR) along with SH3GL2 (regulator of EGFR homeostasis) were compared between neoadjuvant chemotherapy treated (NACT) and pretherapeutic TNBC samples. Reduced nuclear expression of Y654-p-β-catenin protein with low proliferation index and CD44 prevalence showed concordance with reduced expression of EGFR/Y1045-p-EGFR proteins in the NACT samples than the pretherapeutic TNBC samples. Infrequent messenger RNA expression, gene amplification (10–32.5%), and mutation (1%) of EGFR were seen in the TNBC samples irrespective of therapy, suggesting the importance of EGFR protein stabilization in this tumor. The upregulation of SH3GL2 seen in the NACT samples in contrast to the pretherapeutic samples might be due to its promoter hypomethylation, as seen in the quantitative methylation assay. A similar trend of upregulation of SH3GL2 and downregulation of EGFR, Y1045-p-EGFR, Y654-p-β-catenin were seen in the MDA-MB-231 cell line using antharacycline antitumor drugs (doxorubicin/nogalamycin). The NACT patients with reduced expression of Y654-p-β-catenin and/or EGFR and high expression of SH3GL2 showed comparatively better prognosis than the pretherapeutic patients. Thus, our study showed that reduced nuclear expression of Y654-p-β-catenin in NACT samples due to downregulation of EGFR protein through promoter hypomethylation-mediated upregulation of SH3GL2, resulting in low proliferation index/CD44 prevalence with better prognosis of the NACT patients, might have an important role in the chemotolerance of TNBC.     

Effect of nitric oxide signaling in bacterial-treated soybean plant under salt stress

To understand protective roles of nitric oxide against salt stress, the effects of exogenous sodium nitroprusside on activities of lipoxygenase, peroxidase, phenylalanine ammonialyase, catalase, superoxide dismutase enzymes, proline accumulation, and distribution of sodium in soybean plants under salt were determined. Application of sodium nitroprusside + bacterium enhanced plant growth-promotion characteristics, activities of different enzymes, and proline accumulation in the presence of sodium nitroprusside under salt stress. Treatment with NaCl at 200 mM and sodium nitroprusside (0.1 mM) reduced Na⁺ levels but increased K⁺ levels in leaves in comparison with the NaCl-treated plants. Correspondingly, the plants treated with exogenous sodium nitroprusside and NaCl maintained a lower ratio of [Na⁺]/[K⁺] in NaCl-stressed plants.     

In silico investigation of novel biological pathways: The role of CD200 in regulation of T cell priming in experimental autoimmune encephalomyelitis

The use of simulation to investigate biological domains will inevitably lead to the need to extend existing simulations as new areas of these domains become more fully understood. Such simulation extensions can entail the incorporation of additional cell types, molecules or molecular pathways, all of which can exert a profound influence on the simulation behaviour. Where the biological domain is not well characterised, a structured development methodology must be employed to ensure that the extended simulation is well aligned with its predecessor. We develop and discuss such a methodology, relying on iterative simulation development and sensitivity analysis. The utility of this methodology is demonstrated using a case study simulation of experimental autoimmune encephalomyelitis (EAE), a murine T cell-mediated autoimmune disease model of multiple sclerosis, where it is used to investigate the activity of an additional regulatory pathway. We discuss how application of this methodology guards against creating inappropriate simulation representations of the biology when investigating poorly characterised biological mechanisms.     

Meander: visually exploring the structural variome using space-filling curves

The introduction of next generation sequencing methods in genome studies has made it possible to shift research from a gene-centric approach to a genome wide view. Although methods and tools to detect single nucleotide polymorphisms are becoming more mature, methods to identify and visualize structural variation (SV) are still in their infancy. Most genome browsers can only compare a given sequence to a reference genome; therefore, direct comparison of multiple individuals still remains a challenge. Therefore, the implementation of efficient approaches to explore and visualize SVs and directly compare two or more individuals is desirable. In this article, we present a visualization approach that uses space-filling Hilbert curves to explore SVs based on both read-depth and pair-end information. An interactive open-source Java application, called Meander, implements the proposed methodology, and its functionality is demonstrated using two cases. With Meander, users can explore variations at different levels of resolution and simultaneously compare up to four different individuals against a common reference. The application was developed using Java version 1.6 and Processing.org and can be run on any platform. It can be found at http://homes.esat.kuleuven.be/~bioiuser/meander.     

Binding of the plant alkaloid aristololactam-β-d-glucoside and antitumor antibiotic daunomycin to single stranded polyribonucleotides

Background

Interaction of the plant alkaloid aristololactam-β-d-glucoside and the antitumor drug daunomycin with single stranded RNAs poly(G), poly(I), poly(C) and poly(U) has been investigated.

Methods

Biophysical techniques of absorption, fluorescence, competition dialysis, circular dichroism, and microcalorimetry have been used.

Results

Absorption and fluorescence studies have revealed noncooperative binding of ADG and DAN to the single stranded RNAs. The binding affinity of ADG varied as poly(G) > poly(I) > > poly(C) > poly(U). The affinity of DAN was one order higher than that of ADG and varied as poly(G) > poly(I) > poly(U) > poly(C). This binding preference was further confirmed by competition dialysis assay. The thermodynamics of the binding was characterised to be favourable entropy and enthalpic terms but their contributions were different for different systems. The major non-polyelectrolytic contribution to the binding revealed from salt dependent data appears to be arising mostly from stacking of DAN and ADG molecules with the bases leading to partial intercalation to single stranded RNA structures. Small negative heat capacity values have been observed in all the four cases.

Conclusions

This study presents the comparative structural and thermodynamic profiles of the binding of aristololactam-β-d-glucoside and daunomycin to single stranded polyribonucleotides.

General significance

These results suggest strong, specific but differential binding of these drug molecules to the single stranded RNAs and highlight the role of their structural differences in the interaction profile.