On a Model of Pattern Regeneration Based on Cell Memory

We present here a new model of the cellular dynamics that enable regeneration of complex biological morphologies. Biological cell structures are considered as an ensemble of mathematical points on the plane. Each cell produces a signal which propagates in space and is received by other cells. The total signal received by each cell forms a signal distribution defined on the cell structure. This distribution characterizes the geometry of the cell structure. If a part of this structure is removed, the remaining cells have two signals. They keep the value of the signal which they had before the amputation (memory), and they receive a new signal produced after the amputation. Regeneration of the cell structure is stimulated by the difference between the old and the new signals. It is stopped when the two signals coincide. The algorithm of regeneration contains certain rules which are essential for its functioning, being the first quantitative model of cellular memory that implements regeneration of complex patterns to a specific target morphology. Correct regeneration depends on the form and the size of the cell structure, as well as on some parameters of regeneration.     

Parameters Influencing Baseline HIV-1 Genotypic Tropism Testing Related to Clinical Outcome in Patients on Maraviroc

ObjectivesWe analysed the impact of different parameters on genotypic tropism testing related to clinical outcome prediction in 108 patients on maraviroc (MVC) treatment.Methods87 RNA and 60 DNA samples were used. The viral tropism was predicted using the geno2pheno_[coreceptor] and T-CUP tools with FPR cut-offs ranging from 1%-20%. Additionally, 27 RNA and 28 DNA samples were analysed in triplicate, 43 samples with the ESTA assay and 45 with next-generation sequencing. The influence of the genotypic susceptibility score (GSS) and 16 MVC-resistance mutations on clinical outcome was also studied.ResultsConcordance between single-amplification testing compared to ESTA and to NGS was in the order of 80%. Concordance with NGS was higher at lower FPR cut-offs. Detection of baseline R5 viruses in RNA and DNA samples by all methods significantly correlated with treatment success, even with FPR cut-offs of 3.75%-7.5%. Triple amplification did not improve the prediction value but reduced the number of patients eligible for MVC. No influence of the GSS or MVC-resistance mutations but adherence to treatment, on the clinical outcome was detected.ConclusionsProviral DNA is valid to select candidates for MVC treatment. FPR cut-offs of 5%-7.5% and single amplification from RNA or DNA would assure a safe administration of MVC without excluding many patients who could benefit from this drug. In addition, the new prediction system T-CUP produced reliable results.     

Autophagy and mitochondrial remodelling in mouse mesenchymal stromal cells challenged with Staphylococcus epidermidis

The bone marrow stroma constitutes the marrow‐blood barrier, which sustains immunochemical homoeostasis and protection of the haematopoietic tissue in sequelae of systemic bacterial infections. Under these conditions, the bone marrow stromal cells affected by circulating bacterial pathogens shall elicit the adaptive stress‐response mechanisms to maintain integrity of the barrier. The objective of this communication was to demonstrate (i) that in vitro challenge of mesenchymal stromal cells, i.e. colony‐forming unit fibroblasts (CFU‐F), with Staphylococcus epidermidis can activate the autophagy pathway to execute antibacterial defence response, and (ii) that homoeostatic shift because of the bacteria‐induced stress includes the mitochondrial remodelling and sequestration of compromised organelles via mitophagy. Implication of Drp1 and PINK1–PARK2‐dependent mechanisms in the mitophagy turnover of the aberrant mitochondria in mesenchymal stromal cells is investigated and discussed.     

The Genome Sequence of the Crenarchaeon Acidilobus saccharovorans Supports a New Order,Acidilobales, and Suggests an Important Ecological Role in Terrestrial Acidic Hot Springs

Acidilobus saccharovorans is an anaerobic, organotrophic, thermoacidophilic crenarchaeon isolated from a terrestrial hot spring. We report the complete genome sequence of A. saccharovorans, which has permitted the prediction of genes for Embden-Meyerhof and Entner-Doudoroff pathways and genes associated with the oxidative tricarboxylic acid cycle. The electron transfer chain is branched with two sites of proton translocation and is linked to the reduction of elemental sulfur and thiosulfate. The genomic data suggest an important role of the order Acidilobales in thermoacidophilic ecosystems whereby its members can perform a complete oxidation of organic substrates, closing the anaerobic carbon cycle.Acidophilic microorganisms are widely dispersed in natural acidic environments, including volcanic hot springs, and are, in the majority, aerobes (14). However, such anoxic, high-temperature, acidic environments are inhabited by metabolically versatile anaerobic thermoacidophiles of the archaeal phylum Crenarchaeota. Lithoautotrophic thermoacidophiles oxidize molecular hydrogen in the course of elemental sulfur (S⁰) respiration. Organotrophs couple the oxidation of organic substrates to the reduction of S⁰ or thiosulfate. They all belong to the genus Acidilobus in the family Acidilobaceae and to the genus Caldisphaera in the family Caldisphaeraceae (4, 13, 22, 24). Acidilobaceae and Caldisphaeraceae form the crenarchaeal order Acidilobales (24). Acidilobus saccharovorans was isolated from an acidic hot spring of Uzon Caldera, Kamchatka, Russia (24). It is an obligately anaerobic acidophile with a range of growth from pH 2.5 to 5.8 (optimum at pH 3.5 to 4) and a temperature range from 60 to 90°C (optimum at 80 to 85°C). It utilizes a wide range of proteinaceous and carbohydrate substrates and cannot grow lithoautotrophically on H₂ and CO₂ (24). S⁰ and thiosulfate stimulate growth and are reduced to H₂S. Protons cannot serve as electron acceptors, since no H₂ is produced during growth in the absence of S⁰ (24). Genomic sequences of aerobic, thermoacidophilic euryarchaea Thermoplasma acidophilum (26) and Picrophilus torridus (8) give an insight into the thermoacidophilic survival strategy. However, no genomes of obligately anaerobic, thermoacidophilic archaea were available until now. Here we present the genome of A. saccharovorans and show that it encodes numerous hydrolytic enzymes and metabolic pathways necessary for the utilization and complete mineralization of organic substrates in its natural habitat, acidic hot springs.     

A plausible mechanism for auxin patterning along the developing root

Background

Recent experimental work has uncovered some of the genetic components required to maintain the Arabidopsis thaliana root stem cell niche (SCN) and its structure. Two main pathways are involved. One pathway depends on the genes SHORTROOT and SCARECROW and the other depends on the PLETHORA genes, which have been proposed to constitute the auxin readouts. Recent evidence suggests that a regulatory circuit, composed of WOX5 and CLE40, also contributes to the SCN maintenance. Yet, we still do not understand how the niche is dynamically maintained and patterned or if the uncovered molecular components are sufficient to recover the observed gene expression configurations that characterize the cell types within the root SCN. Mathematical and computational tools have proven useful in understanding the dynamics of cell differentiation. Hence, to further explore root SCN patterning, we integrated available experimental data into dynamic Gene Regulatory Network (GRN) models and addressed if these are sufficient to attain observed gene expression configurations in the root SCN in a robust and autonomous manner.

Results

We found that an SCN GRN model based only on experimental data did not reproduce the configurations observed within the root SCN. We developed several alternative GRN models that recover these expected stable gene configurations. Such models incorporate a few additional components and interactions in addition to those that have been uncovered. The recovered configurations are stable to perturbations, and the models are able to recover the observed gene expression profiles of almost all the mutants described so far. However, the robustness of the postulated GRNs is not as high as that of other previously studied networks.

Conclusions

These models are the first published approximations for a dynamic mechanism of the A. thaliana root SCN cellular pattering. Our model is useful to formally show that the data now available are not sufficient to fully reproduce root SCN organization and genetic profiles. We then highlight some experimental holes that remain to be studied and postulate some novel gene interactions. Finally, we suggest the existence of a generic dynamical motif that can be involved in both plant and animal SCN maintenance.     

The Generating Function of CID,ETD, and CID/ETD Pairs of Tandem Mass Spectra: Applications to Database Search

Recent emergence of new mass spectrometry techniques (e.g. electron transfer dissociation, ETD) and improved availability of additional proteases (e.g. Lys-N) for protein digestion in high-throughput experiments raised the challenge of designing new algorithms for interpreting the resulting new types of tandem mass (MS/MS) spectra. Traditional MS/MS database search algorithms such as SEQUEST and Mascot were originally designed for collision induced dissociation (CID) of tryptic peptides and are largely based on expert knowledge about fragmentation of tryptic peptides (rather than machine learning techniques) to design CID-specific scoring functions. As a result, the performance of these algorithms is suboptimal for new mass spectrometry technologies or nontryptic peptides. We recently proposed the generating function approach (MS-GF) for CID spectra of tryptic peptides. In this study, we extend MS-GF to automatically derive scoring parameters from a set of annotated MS/MS spectra of any type (e.g. CID, ETD, etc.), and present a new database search tool MS-GFDB based on MS-GF. We show that MS-GFDB outperforms Mascot for ETD spectra or peptides digested with Lys-N. For example, in the case of ETD spectra, the number of tryptic and Lys-N peptides identified by MS-GFDB increased by a factor of 2.7 and 2.6 as compared with Mascot. Moreover, even following a decade of Mascot developments for analyzing CID spectra of tryptic peptides, MS-GFDB (that is not particularly tailored for CID spectra or tryptic peptides) resulted in 28% increase over Mascot in the number of peptide identifications. Finally, we propose a statistical framework for analyzing multiple spectra from the same precursor (e.g. CID/ETD spectral pairs) and assigning p values to peptide-spectrum-spectrum matches.Since the introduction of electron capture dissociation (ECD)1 in 1998 (1), electron-based peptide dissociation technologies have played an important role in analyzing intact proteins and post-translational modifications (2). However, until recently, this research-grade technology was available only to a small number of laboratories because it was commercially unavailable, required experience for operation, and could be implemented only with expensive FT-ICR instruments. The discovery of electron-transfer dissociation (ETD) (3) enabled an ECD-like technology to be implemented in (relatively cheap) ion-trap instruments. Nowadays, many researchers are employing the ETD technology for tandem mass spectra generation (4–9).Although the hardware technologies to generate ETD spectra are maturing rapidly, software technologies to analyze ETD spectra are still in infancy. There are two major approaches to analyzing tandem mass spectra: de novo sequencing and database search. Both approaches find the best-scoring peptide either among all possible peptides (de novo sequencing) or among all peptides in a protein database (database search). Although de novo sequencing is emerging as an alternative to database search, database search remains a more accurate (and thus preferred) method of spectral interpretation, so here we focus on the database search approach.Numerous database search engines are currently available, including SEQUEST (10), Mascot (11), OMSSA (12), X!Tandem (13), and InsPecT (14). However, most of them are inadequate for the analysis of ETD spectra because they are optimized for collision induced dissociation (CID) spectra that show different fragmentation propensities than those of ETD spectra. Additionally, the existing tandem mass spectrometry (MS/MS) tools are biased toward the analysis of tryptic peptides because trypsin is usually used for CID, and thus not suitable for the analysis of nontryptic peptides that are common for ETD. Therefore, even though some database search engines support the analysis of ETD spectra (e.g. SEQUEST, Mascot, and OMSSA), their performance remains suboptimal when it comes to analyzing ETD spectra. Recently, an ETD-specific database search tool (Z-Core) was developed; however it does not significantly improve over OMSSA (15).We present a new database search tool (MS-GFDB) that significantly outperforms existing database search engines in the analysis of ETD spectra, and performs equally well on nontryptic peptides. MS-GFDB employs the generating function approach (MS-GF) that computes rigorous p values of peptide-spectrum matches (PSMs) based on the spectrum-specific score histogram of all peptides (16).² MS-GF p values are dependent only on the PSM (and not on the database), thus can be used as an alternative scoring function for the database search.Computing p values requires a scoring model evaluating qualities of PSMs. MS-GF adopts a probabilistic scoring model (MS-Dictionary scoring model) described in Kim et al., 2009 (17), considering multiple features including product ion types, peak intensities and mass errors. To define the parameters of this scoring model, MS-GF only needs a set of training PSMs.³ This set of PSMs can be obtained in a variety of ways: for example, one can generate CID/ETD pairs and use peptides identified by CID to form PSMs for ETD. Alternatively, one can generate spectra from a purified protein (when PSMs can be inferred from the accurate parent mass alone) or use a previously developed (not necessary optimal) tool to generate training PSMs. From these training PSMs, MS-GF automatically derives scoring parameters without assuming any prior knowledge about the specifics of a particular peptide fragmentation method (e.g. ETD, CID, etc.) and/or proteolytic origin of the peptides. MS-GF was originally designed for the analysis of CID spectra, but now it has been extended to other types of spectra generated by various fragmentation techniques and/or various enzymes. We show that MS-GF can be successfully applied to novel types of spectra (e.g. ETD of Lys-N peptides (18, 19)) by simply retraining scoring parameters without any modification. Note that although the same scoring model is used for different types of spectra, the parameters derived to score different types of spectra are dissimilar.We compared the performance of MS-GFDB with Mascot on a large ETD data set and found that it generated many more peptide identifications for the same false discovery rates (FDR). For example, at 1% peptide level FDR, MS-GFDB identified 9450 unique peptides from 81,864 ETD spectra of Lys-N peptides whereas Mascot only identified 3672 unique peptides, ≈160% increase in the number of peptide identifications (a similar improvement is observed for ETD spectra of tryptic peptides).⁴ MS-GFDB also showed a significant 28% improvement in the number of identified peptides from CID spectra of tryptic peptides (16,203 peptides as compared with 12,658 peptides identified by Mascot).The ETD technology complements rather than replaces CID because both technologies have some advantages: CID for smaller peptides with small charges, ETD for larger and multiply charged peptides (20, 21). An alternative way to utilize ETD is to use it in conjunction with CID because CID and ETD generate complementary sequence information (20, 22, 23). ETD-enabled instruments often support generating both CID and ETD spectra (CID/ETD pairs) for the same peptide. Although the CID/ETD pairs promise a great improvement in peptide identification, the full potential of such pairs has not been fully realized yet. In the case of de novo sequencing, de novo sequencing tools utilizing CID/ETD pairs indeed result in more accurate de novo peptide sequencing than traditional CID-based algorithms (23, 24, 25). However, in the case of database search, the argument that the use of CID/ETD pairs improves peptide identifications remains poorly substantiated. A few tools are developed to use CID/ETD (or CID/ECD) pairs for the database search but they are limited to preprocessing/postprocessing of the spectral data before or following running a traditional database search tool (26, 27). Nielsen et al., 2005 (22) pioneered the combined use of CID and ECD for the database search. Given a CID/ECD pair, they generated a combined spectrum comprised only of complementary pairs of peaks, and searched it with Mascot.⁵ However, this approach is hard to generalize to less accurate CID/ETD pairs generated by ion-trap instruments because there is a higher chance that the identified complementary pairs of peaks are spurious. More importantly, using traditional MS/MS tools (such as Mascot) for the database search of the combined spectrum is inappropriate, because they are not optimized for analyzing such combined spectra; a better approach would be to develop a new database search tool tailored for the combined spectrum. Recently, Molina et al., 2008 (26) studied database search of CID/ETD pairs using Spectrum Mill (Agilent Technologies, Santa Clara, CA) and came to a counterintuitive conclusion that using only CID spectra identifies 12% more unique peptides than using CID/ETD pairs. We believe that it is an acknowledgment of limitations of the traditional MS/MS database search tools for the analysis of multiple spectra generated from a single peptide.In this paper, we modify the generating function approach for interpreting CID/ETD pairs and further apply it to improve the database search with CID/ETD pairs. In contrast to previous approaches, our scoring is specially designed to interpret CID/ETD pairs and can be generalized to analyzing any type of multiple spectra generated from a single peptide. When CID/ETD pairs from trypsin digests are used, MS-GFDB identified 13% and 27% more peptides compared with the case when only CID spectra and only ETD spectra are used, respectively. The difference was even more prominent when CID/ETD pairs from Lys-N digests were used, with 41% and 33% improvement over CID only and ETD only, respectively.Assigning a p value to a PSM greatly helped researchers to evaluate the quality of peptide identifications. We now turn to the problem of assigning a p value to a peptide-spectrum-spectrum match (PS²M) when two spectra in PS²M are generated by different fragmentation technologies (e.g. ETD and CID). We argue that assigning statistical significance to a PS²M (or even PSⁿM) is a prerequisite for rigorous CID/ETD analyses. To our knowledge, MS-GFDB is the first tool to generate statistically rigorous p values of PSⁿMs.The MS-GFDB executable and source code is available at the website of Center for Computational Mass Spectrometry at UCSD (http://proteomics.ucsd.edu). It takes a set of spectra (CID, ETD, or CID/ETD pairs) and a protein database as an input and outputs peptide matches. If the input is a set of CID/ETD pairs, it outputs the best scoring peptide matches and their p values (1) using only CID spectra, (2) using only ETD spectra, and (3) using combined spectra of CID/ETD pairs.     

Innate-Like Control of Human iNKT Cell Autoreactivity via the Hypervariable CDR3β Loop

Invariant Natural Killer T cells (iNKT) are a versatile lymphocyte subset with important roles in both host defense and immunological tolerance. They express a highly conserved TCR which mediates recognition of the non-polymorphic, lipid-binding molecule CD1d. The structure of human iNKT TCRs is unique in that only one of the six complementarity determining region (CDR) loops, CDR3β, is hypervariable. The role of this loop for iNKT biology has been controversial, and it is unresolved whether it contributes to iNKT TCR:CD1d binding or antigen selectivity. On the one hand, the CDR3β loop is dispensable for iNKT TCR binding to CD1d molecules presenting the xenobiotic alpha-galactosylceramide ligand KRN7000, which elicits a strong functional response from mouse and human iNKT cells. However, a role for CDR3β in the recognition of CD1d molecules presenting less potent ligands, such as self-lipids, is suggested by the clonal distribution of iNKT autoreactivity. We demonstrate that the human iNKT repertoire comprises subsets of greatly differing TCR affinity to CD1d, and that these differences relate to their autoreactive functions. These functionally different iNKT subsets segregate in their ability to bind CD1d-tetramers loaded with the partial agonist α-linked glycolipid antigen OCH and structurally different endogenous β-glycosylceramides. Using surface plasmon resonance with recombinant iNKT TCRs and different ligand-CD1d complexes, we demonstrate that the CDR3β sequence strongly impacts on the iNKT TCR affinity to CD1d, independent of the loaded CD1d ligand. Collectively our data reveal a crucial role for CDR3β for the function of human iNKT cells by tuning the overall affinity of the iNKT TCR to CD1d. This mechanism is relatively independent of the bound CD1d ligand and thus forms the basis of an inherent, CDR3β dependent functional hierarchy of human iNKT cells.