Europan Molecular Indicators of Life Investigation (EMILI) for a Future Europa Lander Mission

The Europan Molecular Indicators of Life Investigation (EMILI) is an instrument concept being developed for the Europa Lander mission currently under study. EMILI will meet and exceed the scientific and technical/resource requirements of the organic composition analyzer identified as a core instrument on the Lander. EMILI tightly couples two complementary analytical techniques, based on 1) liquid extraction and processing with capillary electrophoresis and 2) thermal and chemical extraction with gas chromatography, to robustly detect, structurally characterize, and quantify the broadest range of organics and other Europan chemicals over widely-varying concentrations. Dual processing and analysis paths enable EMILI to perform a thorough characterization of potential molecular biosignatures and contextual compounds in collected surface samples. Here we present a summary of the requirements, design, and development status of EMILI with projected scientific opportunities on the Europa Lander as well as on other potential life detection missions seeking potential molecular biosignatures in situ.

The Potential of Molecular Indicators of Plant Virus Infection: Are Plants Able to Tell Us They Are Infected?

To our knowledge, there are no reports that demonstrate the use of host molecular markers for the purpose of detecting generic plant virus infection. Two approaches involving molecular indicators of virus infection in the model plant Arabidopsis thaliana were examined: the accumulation of small RNAs (sRNAs) using a microfluidics-based method (Bioanalyzer); and the transcript accumulation of virus-response related host plant genes, suppressor of gene silencing 3 (AtSGS3) and calcium-dependent protein kinase 3 (AtCPK3) by reverse transcriptase-quantitative PCR (RT-qPCR). The microfluidics approach using sRNA chips has previously demonstrated good linearity and good reproducibility, both within and between chips. Good limits of detection have been demonstrated from two-fold 10-point serial dilution regression to 0.1 ng of RNA. The ratio of small RNA (sRNA) to ribosomal RNA (rRNA), as a proportion of averaged mock-inoculation, correlated with known virus infection to a high degree of certainty. AtSGS3 transcript decreased between 14- and 28-days post inoculation (dpi) for all viruses investigated, while AtCPK3 transcript increased between 14 and 28 dpi for all viruses. A combination of these two molecular approaches may be useful for assessment of virus-infection of samples without the need for diagnosis of specific virus infection.

Does the Urinary Proteome Reflect ccRCC Stage and Grade Progression?

Due its ability to provide a global snapshot of kidney physiology, urine has emerged as a highly promising, non-invasive source in the search for new molecular indicators of disease diagnosis, prognosis, and surveillance. In particular, proteomics represents an ideal strategy for the identification of urinary protein markers; thus, a urinomic approach could also represent a powerful tool in the investigation of the most common kidney cancer, which is clear cell Renal Cell Carcinoma (ccRCC). Currently, these tumors are classified after surgical removal using the TNM and nuclear grading systems and prognosis is usually predicted based upon staging. However, the aggressiveness and clinical outcomes of ccRCC remain heterogeneous within each stratified group, highlighting the need for novel molecular indicators that can predict the progression of these tumors. In our study, we explored the association between the urinary proteome and the ccRCC staging and grading classification. The urine proteome of 44 ccRCC patients with lesions of varying severity was analyzed via label-free proteomics. MS data revealed several proteins with altered abundance according to clinicopathological stratification. Specifically, we determined a panel of dysregulated proteins strictly related to stage and grade, suggesting the potential utility of MS-based urinomics as a complementary tool in the staging process of ccRCC.

Using Transcript Levels of Nitrate Transporter 2 as Molecular Indicators to Estimate the Potentials of Nitrate Transport in Symbiodinium, Cladocopium, and Durusdinium of the Fluted Giant Clam, Tridacna squamosa

Giant clams are important ecosystem engineers of coral reefs because they harbor large quantities of phototrophic Symbiodiniaceae dinoflagellates of mainly genera Symbiodinium, Cladocopium, and Durusdinium. The coccoid dinoflagellates donate photosynthate and amino acids to the clam host, which in return needs to supply inorganic carbon and nitrogen to them. The host can conduct light-enhanced absorption of nitrate (NO3–), which can only be metabolized by the symbionts. This study aimed to clone nitrate transporter 2 (NRT2) from the symbionts of the fluted giant clam, Tridacna squamosa. Here, we report three major sequences of NRT2 derived from Symbiodinium (Symb-NRT2), Cladocopium (Clad-NRT2) and Durusdinium (Duru-NRT2). Phenogramic analysis and molecular characterization confirmed that these three sequences were NRT2s derived from dinoflagellates. Immunofluorescence microscopy localized NRT2 at the plasma membrane and cytoplasmic vesicles of the symbiotic dinoflagellates, indicating that it could partake in the uptake and transport of NO3–. Therefore, the transcript levels of Symb-NRT2, Clad-NRT2, and Duru-NRT2 could be used as molecular indicators to estimate the potential of NO3– transport in five organs of 13 T. squamosa individuals. The transcript levels of form II ribulose-1, 5-bisphosphate carboxylase/oxygenase (rbcII) of Symbiodinium (Symb-rbcII), Cladocopium (Clad-rbcII) and Durusdinium (Duru-rbcII) were also determined in order to calculate the transcript ratios of Symb-NRT2/Symb-rbcII, Clad-NRT2/Clad-rbcII, and Duru-NRT2/Duru-rbcII. These ratios expressed the potentials of NO3– transport with reference to the phototrophic potentials in a certain genus of coccoid dinoflagellate independent of its quantity. Results obtained indicate that Symbiodinium generally had a higher potential of NO3– transport than Cladocopium and Durusdinium at the genus level. Furthermore, some phylotypes (species) of Symbiodinium, particularly those in the colorful outer mantle, had very high Symb-NRT2/Symb-rbcII ratio (7–13), indicating that they specialized in NO3– uptake and nitrogen metabolism. Overall, our results indicate for the first time that different phylotypes of Symbiodiniaceae dinoflagellates could have dissimilar abilities to absorb and assimilate NO3–, alluding to their functional diversity at the genus and species levels.

Molecular Indicators of Biomaterials Osteoinductivity - Cell Migration, BMP Production and Signalling Turns a Key

In this work we dissected the osteoinductive properties of selected, PLGA-based scaffolds enriched with gel-derived bioactive glasses (SBGs) of either binary SiO2-CaO or ternary SiO2-CaO-P2O5 system, differing in CaO/SiO2 ratio (i.e. high -or low-calcium SBGs). To assess the inherent ability of the scaffolds to induce osteogenesis of human bone marrow stromal cells (BMSC), the study was designed to avoid any osteogenic stimuli beyond the putative osteogenic SBG component of the studied scaffolds. The bioactivity and porosity of scaffolds were confirmed by SBF test and porosimetry. Condition media (CM) from BMSC-loaded scaffolds exhibited increased Ca and decreased P content corresponding to SBGs CaO/SiO2 ratio, whereas Si content was relatively stable and overall lower in CM from scaffolds containing binary SBGs. CM from cell-loaded scaffolds containing high-calcium, binary SBGs promoted migration of BMSC and BMP-response in reporter osteoblast cell line. BMSC culture on these scaffolds or the ones containing ternary, low-calcium SBGs resulted in the activation of BMP-related signaling and expression of several osteogenic markers. Ectopic bone formation was induced by scaffolds containing binary SBGs, but high-calcium ones produced significantly more osteoid. Scaffolds containing ternary SBGs negatively influenced the expression of osteogenic transcription factors and Cx43, involved in cell-cell interactions. High-calcium scaffolds stimulated overall higher Cx43 expression. We believe the initial cell-cell communication may be crucial to induce and maintain osteogenesis and high BMP signaling on the studied scaffolds. The presented scaffolds’ biological properties may also constitute new helpful markers to predict osteoinductive potential of other bioactive implant materials. Graphical Abstract

Cancer Growth Inhibition Using Predictive Mathematical Models of Signaling Pathways

Cancer cells develop several hallmark changes over the progress of the tumor process. Cell assistance in multicellular organisms is regulated by the division of cell coordination by aggressive growth modulation. In this perspective, the use of molecular indicators triggering cell division is a mystery, because a cancer cell can manipulate any molecule that induces and helps growth, disturbing cellular assistance. An effective alteration proceeding to tumors must develop to be competitive, allowing a cancer cell to pass a signal resulting in better selection chances. The subjective simulation of physiological systems has become increasingly valuable in recent years, and there is now a wide range of mathematical models of signalling pathways that have contributed to some groundbreaking discoveries and hypotheses as to how this system works. Here we discuss various modeling methods and their application to the physiology of medical systems, focusing on the identification of parameters in ordinary differential equation models and their significance for forecasting cellular decisions in network modeling. In situations of global and local cell-to-cell rivalry, we quantify how this mechanism impacts a mutated cell's fixing chance of producing such a signal, and consider that this process will play a vital role in reducing cancer.

Molecular Indicators of Biomaterials Osteoinductivity - Cell Migration, BMP Production and Signalling Turns a Key

In this work we dissect the osteoinductive properties of selected bioactive materials obtained in a 3D form, and based on PLGA matrix and 2 types of gel-derived bioactive glasses (SBGs) of SiO2-CaO system, each with and without P2O5. The study is designed to avoid any osteogenic stimuli beyond the putative osteogenic bioactive glass compound of the studied materials. Previously we found that, when used as growth surfaces (i.e. material sheets), some of these materials were capable to support osteogenesis of bone marrow stromal cells (BMSC) without the need for any additional osteogenic cell treatment. In this work we explore further the role of BMP production and signaling upon BMSC culture on selected, SBG/PLGA 3D scaffolds as well as BMSC migration toward the condition media obtained from such cell-loaded materials. Our results show that BMP signaling of osteoprogenitor cells as well as their migration rate may present important indicators of materials osteoinductivity.

Population validation of reproductive gene mutation loci and association with the litter size in Nubian goat

Litter size is an important component trait of doe reproduction. By improving it, production efficiency and economic benefits can be significantly provided. Genetic marker-assisted selection (MAS) based on proven molecular indicators could enhance the efficacy of goat selection, as well as litter size trait. Many molecular markers have been identified that they can be used to improve litter size in different goat breeds. However, the presence and value of these markers vary among goat breeds. In the present study, we used the reported loci on other breeds of goat as candidate loci to detect whether these loci appear in this Nubian goat population; then we proceed to genotype and detect surrounding loci (50 bp) by multiplex PCR and sequencing technology. As a result, 69 mutations (59 SNPs and 10 indels) were screened out from 23 candidate genes in Nubian goat population, 12 loci were significantly associated with the litter size of first-parity individuals; 5 loci were significantly associated with the litter size of second-parity individuals; 3 loci were significantly associated with the litter size of third-parity individuals. In addition, five loci were significantly associated with the average litter size. The additive effect value of KITLG: g.18047318 G>A in first parity, KITLG: g.18152042G>A in third parity, KISS-1: g.1341674 C>G in first parity, and GHR: g.32134187G>A in second parity exceed more than 0.40, and the preponderant alleles are G, C, A and G, respectively. Further, linkage disequilibrium analysis of 21 mutation loci shows that 3 haplotype blocks are formed, and the litter size of combination type AACC in KISS-1 gene and AAGG in KITLG gene are significantly lower than that of other combinations genotype in first parity (P<0.05). These findings can provide effective candidate DNA markers for selecting superior individuals in Nubian goat breeding.

Combining Clinicopathological Parameters and Molecular Indicators to Predict Lymph Node Metastasis in Endometrioid Type Endometrial Adenocarcinoma

BackgroundLymph node metastasis (LNM) is a critical unfavorable prognostic factor in endometrial cancer (EC). At present, models involving molecular indicators that accurately predict LNM are still uncommon. We addressed this gap by developing nomograms to individualize the risk of LNM in EC and to identify a low-risk group for LNM.MethodsIn all, 776 patients who underwent comprehensive surgical staging with pelvic lymphadenectomy at the First Affiliated Hospital of Chongqing Medical University were divided into a training cohort (used for building the model) and a validation cohort (used for validating the model) according to a predefined ratio of 7:3. Logistics regression analysis was used in the training cohort to screen out predictors related to LNM, after which a nomogram was developed to predict LNM in patients with EC. A calibration curve and consistency index (C-index) were used to estimate the performance of the model. A receiver operating characteristic (ROC) curve and Youden index were used to determine the optimal threshold of the risk probability of LNM predicted by the model proposed in this study. Then, the prediction performance of different models and their discrimination abilities for identifying low-risk patients were compared.ResultLNM occurred in 87 and 42 patients in the training and validation cohorts, respectively. Multivariate logistic regression analysis showed that histological grade (P=0.022), myometrial invasion (P=0.002), lymphovascular space invasion (LVSI) (P=0.001), serum CA125 (P=0.008), Ki67 (P=0.012), estrogen receptor (ER) (0.009), and P53 (P=0.003) were associated with LNM; a nomogram was then successfully established on this basis. The internal and external calibration curves showed that the model fits well, and the C-index showed that the prediction accuracy of the model proposed in this study was better than that of the other models (the C-index of the training and validation cohorts was 0.90 and 0.91, respectively). The optimal threshold of the risk probability of LNM predicted by the model was 0.18. Based on this threshold, the model showed good discrimination for identifying low-risk patients.ConclusionCombining molecular indicators based on classical clinical parameters can predict LNM of patients with EC more accurately. The nomogram proposed in this study showed good discrimination for identifying low-risk patients with LNM.

Divining Deamidation and Isomerization in Therapeutic Proteins: Effect of Neighboring Residue

Deamidation of asparagine (ASN) and isomerization of aspartic acid (ASP) residues are among the most commonly observed spontaneous post-translational modifications (PTMs) in proteins. Understanding and predicting a protein sequence's propensity for such PTMs can help expedite protein therapeutic discovery and development. In this study, we utilized proton-affinity calculations with semi-empirical quantum mechanics (QM) and microsecond long equilibrium molecular dynamics (MD) simulations to investigate mechanistic roles of structure and chemical environment in dictating spontaneous degradation of asparagine and aspartic acid residues in 131 clinical-stage therapeutic antibodies. Backbone secondary structure, side-chain rotamer conformation and solvent accessibility were found as three key molecular indicators of ASP isomerization and ASN deamidation. Comparative analysis of backbone dihedral angles along with N-H proton affinity calculations provides a mechanistic explanation for the strong influence of the identity of the n+1 residue on the rate of ASP/ASN degradation. With these findings, we propose a minimalistic physics-based classification model that can be leveraged to predict deamidation and isomerization propensity of therapeutic proteins.