High-resolution genomic analysis: the tumor-immune interface comes into focus

A genomic analysis of heterogeneous colorectal tumor samples has uncovered interactions between immunophenotype and various aspects of tumor biology, with implications for informing the choice of immunotherapies for specific patients and guiding the design of personalized neoantigen-based vaccines.Please see related article: http://dx.doi.org/10.1186/s13059-015-0620-6Immunotherapy is a promising new approach for treating human malignancies. Approximately 20% of melanoma and lung cancer patients receiving immune checkpoint inhibitors show responses [1,2]. Current major challenges include identification of patients most likely to respond to specific therapies and elucidation of novel targets to treat those who do not. To address these problems, a detailed understanding of the dynamic interactions between tumors and the immune system is required. In a new study, Zlatko Trajanoski and colleagues [3] describe a powerful approach to dissecting these issues through high-resolution analysis of patient genomic data. This study represents a significant advance over previous work from this group, which defined 28 immune-cell-type gene expression signatures and identified specific cell types as prognostic indicators in colorectal cancer (CRC) patients [4]. Here, the authors [3] integrate genomic analyses of CRC tumor molecular phenotypes, predicted antigenicity (called the ‘antigenome’), and immune-cell infiltration derived from multiple independent cohorts to gain refined insights into tumor-immune system interactions.     

The NOTCH signaling pathway in normal and malignant blood cell production

The NOTCH pathway is an evolutionarily conserved signalling network, which is fundamental in regulating developmental processes in invertebrates and vertebrates (Gazave et al. in BMC Evol Biol 9:249, 2009). It regulates self-renewal (Butler et al. in Cell Stem Cell 6:251–264, 2010), differentiation (Auderset et al. in Curr Top Microbiol Immunol 360:115–134, 2012), proliferation (VanDussen et al. in Development 139:488–497, 2012) and apoptosis (Cao et al. in APMIS 120:441–450, 2012) of diverse cell types at various stages of their development. NOTCH signalling governs cell-cell interactions and the outcome of such responses is highly context specific. This makes it impossible to generalize about NOTCH functions as it stimulates survival and differentiation of certain cell types, whereas inhibiting these processes in others (Meier-Stiegen et al. in PLoS One 5:e11481, 2010). NOTCH was first identified in 1914 in Drosophila and was named after the indentations (notches) present in the wings of the mutant flies (Bigas et al. in Int J Dev Biol 54:1175–1188, 2010). Homologs of NOTCH in vertebrates were initially identified in Xenopus (Coffman et al. in Science 249:1438–1441, 1990) and in humans NOTCH was first identified in T-Acute Lymphoblastic Leukaemia (T-ALL) (Ellisen et al. in Cell 66:649–61, 1991). NOTCH signalling is integral in neurogenesis (Mead and Yutzey in Dev Dyn 241:376–389, 2012), myogenesis (Schuster-Gossler et al. in Proc Natl Acad Sci U S A 104:537–542, 2007), haematopoiesis (Bigas et al. in Int J Dev Biol 54:1175–1188, 2010), oogenesis (Xu and Gridley in Genet Res Int 2012:648207, 2012), differentiation of intestinal cells (Okamoto et al. in Am J Physiol Gastrointest Liver Physiol 296:G23–35, 2009) and pancreatic cells (Apelqvist et al. in Nature 400:877–881, 1999). The current review will focus on NOTCH signalling in normal and malignant blood cell production or haematopoiesis.     

Phospholamban phosphorylation,mutation, and structural dynamics: a biophysical approach to understanding and treating cardiomyopathy

We review the recent development of novel biochemical and spectroscopic methods to determine the site-specific phosphorylation, expression, mutation, and structural dynamics of phospholamban (PLB), in relation to its function (inhibition of the cardiac calcium pump, SERCA2a), with specific focus on cardiac physiology, pathology, and therapy. In the cardiomyocyte, SERCA2a actively transports Ca²⁺ into the sarcoplasmic reticulum (SR) during relaxation (diastole) to create the concentration gradient that drives the passive efflux of Ca²⁺ required for cardiac contraction (systole). Unphosphorylated PLB (U-PLB) inhibits SERCA2a, but phosphorylation at S16 and/or T17 (producing P-PLB) changes the structure of PLB to relieve SERCA2a inhibition. Because insufficient SERCA2a activity is a hallmark of heart failure, SERCA2a activation, by gene therapy (Andino et al. 2008; Fish et al. 2013; Hoshijima et al. 2002; Jessup et al. 2011) or drug therapy (Ferrandi et al. 2013; Huang 2013; Khan et al. 2009; Rocchetti et al. 2008; Zhang et al. 2012), is a widely sought goal for treatment of heart failure. This review describes rational approaches to this goal. Novel biophysical assays, using site-directed labeling and high-resolution spectroscopy, have been developed to resolve the structural states of SERCA2a-PLB complexes in vitro and in living cells. Novel biochemical assays, using synthetic standards and multidimensional immunofluorescence, have been developed to quantitate PLB expression and phosphorylation states in cells and human tissues. The biochemical and biophysical properties of U-PLB, P-PLB, and mutant PLB will ultimately resolve the mechanisms of loss of inhibition and gain of inhibition to guide therapeutic development. These assays will be powerful tools for investigating human tissue samples from the Sydney Heart Bank, for the purpose of analyzing and diagnosing specific disorders.     

Focus Issue on Roots: Functional Soil Microbiome: Belowground Solutions to an Aboveground Problem

There is considerable evidence in the literature that beneficial rhizospheric microbes can alter plant morphology, enhance plant growth, and increase mineral content. Of late, there is a surge to understand the impact of the microbiome on plant health. Recent research shows the utilization of novel sequencing techniques to identify the microbiome in model systems such as Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). However, it is not known how the community of microbes identified may play a role to improve plant health and fitness. There are very few detailed studies with isolated beneficial microbes showing the importance of the functional microbiome in plant fitness and disease protection. Some recent work on the cultivated microbiome in rice (Oryza sativa) shows that a wide diversity of bacterial species is associated with the roots of field-grown rice plants. However, the biological significance and potential effects of the microbiome on the host plants are completely unknown. Work performed with isolated strains showed various genetic pathways that are involved in the recognition of host-specific factors that play roles in beneficial host-microbe interactions. The composition of the microbiome in plants is dynamic and controlled by multiple factors. In the case of the rhizosphere, temperature, pH, and the presence of chemical signals from bacteria, plants, and nematodes all shape the environment and influence which organisms will flourish. This provides a basis for plants and their microbiomes to selectively associate with one another. This Update addresses the importance of the functional microbiome to identify phenotypes that may provide a sustainable and effective strategy to increase crop yield and food security.In recent years, the term plant microbiome has received substantial attention, since it influences both plant health and productivity. The plant microbiome encompasses the diverse functional gene pool, originating from viruses, prokaryotes, and eukaryotes, associated with various habitats of a plant host. Such plant habitats range from the whole organism (individual plants) to specific organs (e.g. roots, leaves, shoots, flowers, and seeds, including zones of interaction between roots and the surrounding soil, the rhizosphere; Rout and Southworth, 2013). The rhizosphere is the region of the soil being continuously influenced by plant roots through the rhizodeposition of exudates, mucilages, and sloughed cells (Uren, 2001; Bais et al., 2006; Moe, 2013). Thus, plant roots can influence the surrounding soil and inhabiting organisms. Mutually, the rhizosphere organisms can influence the plant by producing regulatory compounds. Thus, the rhizospheric microbiome acts as a highly evolved external functional milieu for plants (for review, see Bais et al., 2006; Badri et al., 2009b; Pineda et al., 2010; Shi et al., 2011; Philippot et al., 2013; Spence and Bais, 2013; Turner et al., 2013a; Spence et al., 2014). In another sense, it is considered as a second genome to a plant (Berendsen et al., 2012). Plant rhizospheric microbiomes have positive or negative influence on plant growth and fitness. It is influenced directly by beneficial mutualistic microbes or pathogens and indirectly through decomposition, nutrient solubilization, nutrient cycling (Glick 1995), secretion of plant growth hormones (Narula et al., 2006; Ortíz-Castro et al., 2008; Ali et al., 2009; Mishra et al., 2009), antagonism of pathogens (Kloepper et al., 2004), and induction of the plant immune system (Pieterse et al., 2001; Ramamoorthy et al., 2001; Vessey, 2003; Rudrappa et al., 2008, 2010). The establishment of plant and rhizospheric microbiome interaction is a highly coordinated event influenced by the plant host and soil. Recent studies show that plant host and developmental stage has a significant influence on shaping the rhizospheric microbiome (Peiffer et al., 2013; Chaparro et al., 2014).There are various factors involved in the establishment of the rhizospheric and endophytic microbiome. They are greatly affected by soil and host type (Bulgarelli et al., 2012; Lundberg et al., 2012). Apart from these factors, other external factors such as biotic/abiotic stress, climatic conditions, and anthropogenic effects also can impact the microbial population dynamics in particular plant species. Plant host species differences can mainly be perceived from the secretory exudates by microbes. The root exudates act as a crucial driving force for multitrophic interactions in the rhizosphere involving microbes, neighboring plants, and nematodes (Bais et al., 2006). Thus, it is important to understand root exudate-shaped microbial community profiling in establishing phenotypes involved in plant health. Microbial components associated with plant hosts have to respond to these exudates along with utilizing them in order to grow competitively in a complex interactive root environment. Commonly, there are three groups of microbes present in the rhizosphere, commensal, beneficial, and pathogenic microbes, and their competition for plant nutrition and interactions confer the overall soil suppressiveness against pathogens and insects (Berendsen et al., 2012).Traditionally, the components of the plant microbiome were characterized by isolating and culturing microbes on different media and growth conditions. These culture-based techniques missed the vast majority of microbial diversity in an environment or in plant-associated habitats, which is now detectable by modern culture-independent molecular techniques for analyzing whole environmental metagenomes (comprising all organisms’ genomes). Over the last 5 years, these culture-independent techniques have dramatically changed our view of the microbial diversity in a particular environment, from which only less than 1% are culturable (Hugenholtz et al., 1998). After discovering the importance of the conserved 16S ribosomal RNA (rRNA) sequence (Woese and Fox, 1977) and the first use of denaturing gradient gel electrophoresis (DGGE) of the amplified 16S rRNA gene in the analysis of a microbial community (Muyzer et al., 1993), there was a sudden explosion of research toward microbial ecology using various molecular fingerprinting techniques. Apart from DGGE, thermal gradient gel electrophoresis, and fluorescence in situ hybridization, clone library construction of microbial community-amplified products and sequencing emerged as other supporting techniques for better understanding of microbial ecology (Muyzer, 1999). Furthermore, there are many newer techniques used to understand the microbiome, from metagenomics to metaproteomics (Friedrich, 2006; Mendes et al., 2011; Knief et al., 2012; Rincon-Florez et al., 2013; Schlaeppi et al., 2014; Yergeau et al., 2014). These techniques cover the whole microbiome, instead of selecting particular species, unlike conventional microbial analysis. However, their presence was not yet correlated well with the phenotypic manifestation (phenome) they establish in the host plant.As a consequence of population growth, food consumption is also increasing. On the other hand, cultivable agricultural land and productivity are significantly reduced due to global industrialization, drought, salinity, and global warming (Gamalero et al., 2009). This problem is only addressed by practicing the sustainable agriculture that protects the health of the ecosystem. The basic principle of sustainable agriculture is to significantly reduce the chemical input, such as fertilizers, insecticides, and herbicides, while reducing the emission of greenhouse gas. Manipulation of the plant microbiome has great potential in reducing the incidence of pests and diseases (van Loon et al., 1998; Kloepper et al., 2004; Van Oosten et al., 2008), promoting plant growth and plant fitness, and increasing productivity (Kloepper and Schroth 1978; Lugtenberg and Kamilova, 2009; Vessey, 2003). Single strains or mixed inoculum treatments induced resistance to multiple plant diseases (Jetiyanon and Kloepper, 2002). In recent years, several microbial biofertilizers and inoculants were formulated, produced, marketed, and successfully used by farmers worldwide (Bhardwaj et al., 2014). Although plants are being considered as a metaorganism (East, 2013), our understanding of the exact manifestation of this microbiome on plant health in terms of phenotypes is insufficient. Of late, there is a surge to understand and explore the genomic wealth of rhizosphere microbes. Hence, this Update will focus mainly on existing knowledge based on the root microbiome, its functional importance, and its potential relationship to the establishment of a host phenome, toward achieving sustainable agriculture.     

Investigating dynamic interdomain allostery in Pin1

Signaling proteins often sequester complementary functional sites in separate domains. How do the different domains communicate with one another? An attractive system to address this question is the mitotic regulator, human Pin1 (Lu et al., Nature 380:544–547, 1996). Pin-1 consists of two mutually tethered domains: a WW domain for substrate binding and a catalytic domain for peptidyl-prolyl isomerase (PPIase) activity. Pin1 accelerates the cis–trans isomerization of phospho-Ser/Thr-Pro (pS/T-P) motifs within proteins regulating the cell cycle and neuronal development. The early X-ray (Ranganathan et al., Cell 89:875–886, 1997; Verdecia et al., Nat Struct Biol 7:639–643, 2000) and solution NMR studies (Bayer et al., J Biol Chem 278:26183–26193, 2003; Jacobs et al., J Biol Chem 278:26174–26182, 2003) of Pin1 indicated inter- and intradomain motions. We have explored how such motions might affect interdomain communication, using NMR. Our accumulated results indicate substrate binding to Pin1 WW domain changes the intra/interdomain mobility, thereby altering substrate activity in the distal PPIase domain catalytic site. Thus, Pin1 shows evidence of dynamic allostery, in the sense of Cooper and Dryden (Eur J Biochem 11:103–109, 1984). We highlight our results supporting this conclusion and summarize them via a simple speculative model of conformational selection.     

Borderline pulmonary pressures in scleroderma - a ‘pre-pulmonary arterial hypertension’ condition?

Patients with systemic sclerosis may develop borderline pulmonary arterial pressure. The clinical relevance of this condition is not always clear. Reported data support the evidence that this subgroup may represent an intermediate stage between normal pulmonary arterial pressure and manifest pulmonary arterial hypertension, a serious complication in scleroderma. Recognizing the clinical relevance of borderline pulmonary arterial pressure increase in scleroderma patients, future studies should aim for clear evidence for diagnostic and therapeutic algorithms for this population.In their recent study, Visovatti and colleagues [1] present a detailed analysis of patients with borderline pulmonary arterial pressure (PAP) as a subgroup analysis of the DETECT study, providing important clinical data for understanding early pulmonary vasculopathy in patients with systemic sclerosis.In fact, every physician who has observed the dramatic deterioration of patients with pulmonary arterial hypertension (PAH) and successive right ventricular failure would urge for the earlier recognition and therapy of this devastating condition. About 10% of all scleroderma patients may develop PAH [2], which - besides lung fibrosis - represents the most frequent cause of death in this patient population [3]. But can PAH be recognized at an early stage and maybe even prevented?If we assume that the increase of PAP is a process lasting for a longer period of time, there must be a phase of transition from normal (mean PAP ≤20 mmHg) pulmonary hemodynamic conditions to PAH (mean PAP ≥25 mmHg). Patients in this so-called ''borderline'' range may represent the early stage of PAH. Earlier studies found that such patients were more likely to develop pulmonary hypertension than patients with mean PAP ≤20 mmHg, with a hazard ratio of 3.7 [4]. The rate of borderline patients developing PAH was 19% after 3 years and 27% after 5 years. Accordingly, we may argue that borderline PAP is a ''pre-PAH'' condition in scleroderma. Of course, borderline elevation of PAP may be caused not only by pulmonary vasculopathy but also by cardiac or pulmonary co-morbidities [5]. In these cases borderline elevation of PAP may be considered as a general prognostic marker [5,6].The analysis of Visovatti and colleagues [1] includes several clinical (for example, current/past telangiectasis, presence of peripheral edema), laboratory (for example, ACA antibody, NT-proBNP), lung functional (for example, forced vital capacity (percentage predicted)/diffusion capacity for carbon monoxide ratio) and cardiac (for example, tricuspid annular plane systolic excursion) markers that may distinguish scleroderma patients with borderline PAP elevation from those with normal PAP or with manifest PAH. According to this analysis, borderline elevation of PAP in scleroderma patients may represent an intermediate stage in the continuum between normal PAP and manifest PAH.Among the DETECT population, 15% of all patients presented with borderline PAP hemodynamics. Although this number may be different in the general scleroderma population, due to the strict inclusion and exclusion criteria of the DETECT study [7], the borderline population seems to be a substantial subgroup. Unfortunately, follow-up data of the described patients in comparison with normal PAP and manifest PAH patients have not been provided. Such data might impact the development of clinical algorithms regarding further follow-up and treatment of these patients.In addition to the borderline elevation of resting PAP, another specific hemodynamic situation in scleroderma patients needs careful interpretation: exercise-induced PAP increase. Earlier studies showed that this may be a frequent condition among scleroderma patients and clinical deterioration and the development of PAH are frequent in this population [2]. In a recent analysis, a strong correlation between resting and exercise PAP values was evident [5], suggesting that patients with borderline hemodynamics and those with a strong PAP increase during exercise may strongly overlap, closing the gap between these two hemodynamic conditions.The most important question remains open: should targeted PAH therapy be offered to scleroderma patients with borderline PAP or exercise-induced PAP increase? Unfortunately there has been no clinical study investigating patients with borderline PAP so far and only two small studies have selected patients with exercise-induced PAP increase [8,9]. The results of these studies are promising, but need to be confirmed in adequately powered, randomized, prospective trials.Based on a series of studies indicating borderline hemodynamics has an important role in scleroderma patients with regard to the development of PAH and potentially for early treatment, future studies should aim for clear evidence for diagnostic and therapeutic algorithms for this patient population. This may contribute to a substantial prognostic improvement for patients with scleroderma who develop pulmonary vasculopathy     

Targeting subchondral bone in osteoporotic osteoarthritis

The identification of well-defined phenotypes along the course of the disease may open new avenues for personalized management in osteoarthritis (OA). In vivo research carried out in various animal models as well as epidemiological and clinical data support the existence of a particular phenotype – osteoporotic OA. In fact, subchondral bone has become a potential therapeutic target in OA. Depending on the ratio between formation and resorption, subchondral bone remodeling can culminate in either a sclerotic or an osteoporotic phenotype. Patients with osteoporotic OA may thus achieve clinical and structural benefit from treatment with bone-targeted interventions.Subchondral bone has become a potential therapeutic target in osteoarthritis (OA). In a previous issue of Arthritis Research & Therapy, Wang and colleagues demonstrate that osteoporosis aggravates cartilage damage in an experimental model of knee OA in rats [1]. Interestingly, the authors also describe that extracorporeal shockwave therapy (ESWT), a mechanical therapeutic intervention probably acting at subchondral bone, may reduce OA progression [1]. The significance of these findings in experimental osteoporotic OA relates to the search for well-defined phenotypes in human OA that will lead to personalized therapy.The controversy regarding the relationship between subchondral bone quality and cartilage integrity originates from the complex biological and mechanical nature of the osteochondral junction [2]. OA progression is often accompanied by increased subchondral bone remodeling that enables mechanical forces to dynamically modify its structure. Depending on the ratio between formation and resorption, subchondral bone can exhibit either a sclerotic or an osteoporotic phenotype [3]. These phenotypes may represent up to 70% and 30% of patients in daily practice, respectively [4]. Furthermore, OA in females can display a different pathogenic profile from OA in males. In this sense, it is reasonable to underline the consequences of estrogen deficiency during menopause [5]. A low estrogen state could induce a deleterious effect on all articular tissues of the knee joint, the subchondral bone being particularly affected due to its capacity for high bone turnover. Thus, during early post menopause, estrogen deficiency may be a risk factor for the development of knee OA. Taking all these facts into consideration, the characterization of patients with either sclerotic or osteoporotic OA phenotypes may enable individualized targeted therapy [3].The effects of estrogen deficiency on the knee joint have been reported in various experimental animal models of OA. The findings obtained by Wang and colleagues on subchondral bone quality and articular cartilage damage support previous research carried out in rabbits, in which osteoporosis aggravated instability-induced OA [6]. In this combined model, the induction of systemic and subchondral osteoporosis associated with increased bone remodeling resulted in worse cartilage damage compared with control animals. Greater fragility of the subchondral bone was suggested to account for the aggravation of cartilage damage when early OA and osteoporosis coexist [7]. In a further study carried out in the same model, the intermittent administration of parathyroid hormone 1-34, a bone-forming agent, was used to increase subchondral bone density and quality [8]. As a consequence, the improvement of subchondral bone integrity was associated with reduced progression of cartilage damage in OA preceded by osteoporosis. In a similar approach, the inhibition of bone resorption by pamidronate in osteoporotic mice alleviated the instability-induced OA histological score with a reduction in the expression of aggrecanases [9]. Several experimental models therefore indicate that osteopenia/osteoporosis induces an accelerated progression of knee OA that can be reversed not only by bone-forming agents but also by antiresorptive drugs.These findings in animal models could be translated to humans, and together with epidemiological and clinical data they support the existence of a particular phenotype – osteoporotic OA [10]. Indeed, this phenotype characterized by decreased density and high remodeling at subchondral bone defines a subgroup of patients treatable with specific agents. In fact, beneficial effects of bone-acting drugs in OA are increasingly reported, but reliable conclusions regarding their efficacy are hindered by methodological drawbacks in study design [10]. Identifying patients with osteoporotic OA may improve the success of bone-directed agents.The original approach of using ESWT in OA by Wang and colleagues remains intriguing. These authors have reported previously that the application of ESWT to subchondral bone of the proximal tibia showed a chondroprotective effect in the initiation of knee OA and regression of established OA of the knee in rats. These effects were attributed to the ESWT multifunctional actions on cartilage and bone. Yet achieving such beneficial effects in this osteoporotic OA model suggests that the main mechanism of action of ESWT may be improving subchondral bone structure [1]. However, some limitations on the study design and the lack of adequate standardization of dosages and optimal frequency, as well as little information regarding the molecular mechanisms underlying the effects of ESWT, hold back the achievement of solid results. In any case, this study points out the potential benefit of nonpharmacological interventions aiming to improve mechanical properties of articular tissues in OA.In summary, the study by Wang and colleagues further supports the existence of the osteoporotic OA subtype and the potential benefit of bone-acting therapeutic interventions. Consequently, the identification of patient phenotypes along with the discovery of specific therapeutic interventions targeting relevant pathogenic mechanisms during the course of the disease could lead to a personalized approach to the management of OA.     

Interactions of DNA with Biofilm-Derived Membrane Vesicles

The biofilm matrix contributes to the chemistry, structure, and function of biofilms. Biofilm-derived membrane vesicles (MVs) and DNA, both matrix components, demonstrated concentration-, pH-, and cation-dependent interactions. Furthermore, MV-DNA association influenced MV surface properties. This bears consequences for the reactivity and availability for interaction of matrix polymers and other constituents.The biofilm matrix contributes to the chemistry, structure, and function of biofilms and is crucial for the development of fundamental biofilm properties (46, 47). Early studies defined polysaccharides as the matrix component, but proteins, lipids, and nucleic acids are all now acknowledged as important contributors (7, 15). Indeed, DNA has emerged as a vital participant, fulfilling structural and functional roles (1, 5, 6, 19, 31, 34, 36, 41, 43, 44). The phosphodiester bond of DNA renders this polyanionic at a physiological pH, undoubtedly contributing to interactions with cations, humic substances, fine-dispersed minerals, and matrix entities (25, 41, 49).In addition to particulates such as flagella and pili, membrane vesicles (MVs) are also found within the matrices of gram-negative and mixed biofilms (3, 16, 40). MVs are multifunctional bilayered structures that bleb from the outer membranes of gram-negative bacteria (reviewed in references 4, 24, 27, 28, and 30) and are chemically heterogeneous, combining the known chemistries of the biofilm matrix. Examination of biofilm samples by transmission electron microscopy (TEM) has suggested that matrix material interacts with MVs (Fig. ​(Fig.1).1). Since MVs produced in planktonic culture have associated DNA (11, 12, 13, 20, 21, 30, 39, 48), could biofilm-derived MVs incorporate DNA (1, 39, 40, 44)?Open in a separate windowFIG. 1.Possible interactions between matrix polymers and particulate structures. Shown is an electron micrograph of a thin section through a P. aeruginosa PAO1 biofilm. During processing, some dehydration occurred, resulting in collapse of matrix material into fibrillate arrangements (black filled arrows). There is a suggestion of interactions occurring with particulate structures such as MVs (hollow white arrow) and flagella (filled white arrows) (identified by the appearance and cross-dimension of these highly ordered structures when viewed at high magnification), which was consistently observed with other embedded samples and also with whole-mount preparations of gently disrupted biofilms (data not shown). The scale bar represents 200 nm.     

Finding smORFs: getting closer

Millions of small open reading frames exist in eukaryotes. We do not know how many, or which are translated, but bioinformatics is getting us closer to the answer.See related Research article: http://www.genomebiology.com/2015/16/1/179DNA sequences encoding small open reading frames (smORFs) of fewer than 100 amino acids (aa) exist in each eukaryotic genome in numbers several orders of magnitude higher than the corresponding annotated protein-coding genes (Fig. 1). Due to difficulties with bioinformatic detection and experimental analysis, along with their sheer numbers, smORFs have been ignored for a long time by mainstream genomics. Thanks to recent advances in bioinformatic and experimental techniques, however, smORFs are receiving increasing attention. Extensive use of RNA-Seq has shown that thousands of smORFs are transcribed, in many cases, in putative noncoding RNAs, and high-throughput experimental techniques have detected translation of a few hundred of these. However, the possibility remains that many more smORFs are functional, but yet uncharacterized. Bioinformatic methods followed by targeted experimental verification are needed to improve the identification of putative functional smORFs. A new paper in Genome Biology [1] provides a significant step towards such a solution.Open in a separate windowFig. 1The number of small open reading frames (smORFs) in eukaryotic genomes (shown in log scale) greatly exceeds that of annotated protein-coding genes, and reaches 265,000 in yeast [4], 556,000 in the fruit fly Drosophila [2], and 40,700,000 in mouse [3]. Note that the current number of corroborated functional smORFs is but a small fraction of these (see text and [1] for details). The number of annotated protein-coding genes was obtained from the Saccharomyces Genome Database (yeast; http://www.yeastgenome.org/), FlyBase (fruit fly; http://flybase.org/), and Ensembl (mouse; http://www.ensembl.org/index.html) (accessed 12 August 2015)     

Molecular Characterization of Cryptosporidium molnari Reveals a Distinct Piscine Clade

Multilocus phylogenetic analysis of small-subunit (SSU) rRNA and actin from Cryptosporidium molnari clustered this species with the C. molnari-like genotype of an isolate from the guppy, although the two fish isolates seem to be distinct species. The analysis of available piscine genotypes provides some support for cladistic congruence of the genus Piscicryptosporidium, but additional piscine genotypes are needed.Recent reviews accept more than 20 valid cryptosporidium species (7, 20), and characterization of additional isolates is expanding this list rapidly (http://www.vetsci.usyd.edu.au/staff/JanSlapeta/icrypto/index.htm). In addition, numerous morphotypes or genotypes have been proposed whose taxonomic affiliation is unsettled due to incomplete characterization according to minimum consensus standards (5, 7, 24). Five species have been proposed for fish isolates (15), but only Cryptosporidium molnari and Cryptosporidium scophthalmi (2, 4) stand as valid species (20), although not without discussion (7). Fish cryptosporidia present some unique features, which have even led to the genus Piscicryptosporidium being proposed (13). However, lack of genetic support keeps this genus and several fish morphotypes as incertae sedis (12, 15, 24). Detailed biological data on C. molnari and C. scophthalmi have been previously presented (3, 18, 19), but no molecular characterization has yet been conducted, thus hampering species identification of other fish isolates (7, 24) and evaluation of their relationships within the genus (15). Ribosomal and actin gene data on an isolate from guppy fish (Poecilia reticulata) have been obtained, and preliminary analyses of these sequences indicated a basal position in the cryptosporidial tree (17). Although it was regarded as C. molnari-like, biological characterization of this isolate was limited. The purpose of this work was to provide the necessary C. molnari comparative genetic data and to clarify the relationship of available fish isolates in a phylogenetic context.     

Assessment of Bias Associated with Incomplete Extraction of Microbial DNA from Soil

DNA extraction bias is a frequently cited but poorly understood limitation of molecular characterizations of environmental microbial communities. To assess the bias of a commonly used soil DNA extraction kit, we varied the cell lysis protocol and conducted multiple extractions on subsamples of clay, sand, and organic soils. DNA, as well as bacterial and fungal ribosomal gene copies as measured by quantitative PCR, continued to be isolated in successive extractions. When terminal restriction fragment length polymorphism was used, a significant shift in community composition due to extraction bias was detected for bacteria but not for fungi. Pyrosequencing indicated that the relative abundances of sequences from rarely cultivated groups such as Acidobacteria, Gemmatimonades, and Verrucomicrobia were higher in the first extraction than in the sixth but that the reverse was true for Proteobacteria and Actinobacteria. This suggests that the well-known phylum-level bacterial cultivation bias may be partially exaggerated by DNA extraction bias. We conclude that bias can be adequately reduced in many situations by pooling three successive extractions, and additional measures should be considered when divergent soil types are compared or when comprehensive community analysis is necessary.The vast majority of soil bacteria (1, 7, 27) and fungi (13, 29) cannot be cultured via traditional laboratory techniques and must be identified using molecular methods. Successful characterization of microbial communities is therefore often dependent on DNA that is extracted from the environment. However, extraction of high-quality DNA from soil can be problematic (8, 11, 22, 26). Commercial DNA extraction kits are now commonly used in the assessment of taxonomic and functional diversity, community composition, and population abundance (e.g., references 19, 21, 23, 25, and 31). Studies comparing various kits (18, 32) or comparing commercial kits to other methods (2, 10, 24) have shown that DNA yield and purity vary depending on methodology and soil type. While these comparative studies are valuable, it is still unclear to what extent these protocols yield genomic DNA representative of the microbial community found within soil.Our objective in this study was to optimize and assess the bias of a widely used commercial soil DNA extraction kit. We hypothesized that cell lysis would be enhanced and DNA would be removed from adsorption sites by conducting multiple extractions on a single sample, thereby increasing genomic DNA yield and obtaining a more complete survey of microbial taxa. This hypothesis was tested by (i) varying the extraction protocol and measuring DNA yield for three soils with differing characteristics and (ii) examining extraction bias in the genomic DNA obtained from successive extractions by using an improved method. Analytical replicates rather than biological replicates were used in order to focus strictly on variation and bias introduced through methodology, although multiple soil types were analyzed to determine whether biases detected were consistent.     

New Method for Monitoring the Process of Freeze Drying of Biological Materials

A capacitive sensor was proposed and tested for the monitoring and control of a freeze drying process of a vaccine against the Newcastle disease of birds. The residual moisture of the vaccine was measured by the thermogravimetric method. The vaccine activity was determined by titration in chicken embryos. It was shown that, at the stages of freezing and primary drying, a capacitive sensor measured the fraction of unfrozen liquid phase in a material and allowed one to control the sublimation stage of drying in an optimal way. This prevented the foaming of the material and shortened the total drying time approximately twice. The control range at the sublimation stage of drying expanded up to −70°C. It was found at the final stage of drying that the signal of a capacitive sensor passed through a maximum value. We supposed that this maximum corresponds to the minimum of intramolecular mobility of biological macromolecules and hence to the optimal residual moisture of the material, which ensures long-term preservation of its activity. We also suppose that using the capacitive sensor at the final stage of drying allows one to more precisely detect the time when the residual moisture of dried material reaches the optimal value.KEY WORDS: biological materials, capacitive sensor, freeze drying, optimal residual moistureAt present, most biological materials containing live viruses or bacteria are exposed to lyophilization (i.e., drying from the frozen state); this ensures long-term preservation of their activity. Typically, this process consists of preliminary freezing and subsequent freeze drying. The latter process, in turn, consists of two stages: primary drying and secondary drying. During primary drying or sublimation, frozen water is removed from a biological product under vacuum and at temperatures below 0°C. At this stage, the drying rate is limited because of the foaming of a product that occurs due to its high temperature and the excess amount of liquid phase in it. The secondary drying, or final stage, begins after the end of the sublimation stage and occurs at temperatures above 0°C. The goal of the secondary drying is to bring the residual moisture of a biological product to an optimum level, which provides long-term preservation of its activity. Note that the moisture content both above and below the optimum value reduces the effective life of biological materials (1,2)To increase the shelf life of biological products, the following should be investigated: (1) the influence of the composition of the dried biological product and the residual moisture on the change in its activity over the time (3); (2) it is needed to optimize the sublimation drying process for different types of biological products (4). For the investigation of the of the state of water in the dried biologic drugs and the influence of the humidity of the biological on the change in their activity during shelf life, different physical methods are used such as neutron scattering (5), nuclear magnetic resonance (NMR) (6,7), Raman spectroscopy (8), infrared spectroscopy, differential scanning calorimetry, thermal activity monitor (9), and gravimetric sorption analysis (10). The investigations using these methods allow to find an optimum composition of a protective medium for biologics and to determine its optimal residual moisture.At all stages of the freeze drying, the parameters of the material and the parameters of the drying process (temperature of a material, the shelf temperature, the condenser temperature, the pressure in the sublimation chamber, etc.) are also monitored. According to these data, the mode of the process is selected to conduct him for the minimum time and get the best product quality (11). Usually during the drying process, the temperature is measured in several vials with biologic located on different shelves. The sharp increase of the temperature indicates the end of primary drying and the beginning of the secondary drying. The finish of the sublimation stage is revealed by a sharp decrease of the partial pressure of water vapor in the sublimation chamber (12,13). Note that the partial pressure of water vapor in the sublimation chamber does not characterize the state of the biological product to be dried and it is an indirect parameter. For monitoring and controlling the process of freeze drying, it is important to use the own properties of biological materials. In (14), a resistivity sensor placed in a frozen biological material was proposed to control the primary stage of freeze drying. A disadvantage of this method is that one cannot establish an unambiguous relationship between the amount of liquid phase in the frozen material and the value of resistivity: the resistance of the sensor depends not only on the amount of liquid phase but also on the concentration of dissolved salts. Another disadvantage of the resistivity sensor is that, when the temperature decreases, the resistivity of the material sharply increases to values that are difficult to measure, which makes impossible the control of the sublimation stage with this sensor.In (15,16), the interesting methods for determining the moisture of biological materials during secondary drying were proposed. These methods are based on the measurement of the partial pressure of water vapors in the sublimation chamber by NIR spectroscopy or Raman spectroscopy. Note that this method is indirect and requires laborious calibration to establish a correspondence between the current moisture of the biological material in vials and the pressure of water vapor in the sublimation chamber.It should be noted that one has to carry out a series of long-term experiments to find the optimal residual moisture of a biological product. These experiments result in the lifetimes of biological samples with various residual moistures. As the optimal residual moisture of a biological product, one takes the value that provides the longest term preservation of its activity.However, finding the optimal conditions of freeze drying has traditionally been a process of trial and error and required several experimental runs (17). Note also that the freeze drying process is time-consuming and labor intensive.A promising method for the investigation of the properties of biological materials is dielcometry (18,19). This method is relatively simple and very informative since it gives information about the structure of biological macromolecules and the state and role of water in the biological material, etc. This method was used in (20–22) for monitoring biological materials at the primary stage of freeze drying. In (20), authors had found an anomalous low-frequency dispersion of the dielectric permittivity in the biological under study and explain this phenomenon by the proton transfer among water molecules, connected by hydrogen bonds The dielectric relaxation time turned out to be sensitive to the loss of moisture content in the product, and the authors suggested to use of this phenomenon to determine the end point of the freeze drying process. The authors mounted the electrodes of the capacitive sensor on the outer surface of vials with the material to be dried. This approach allows monitoring the sublimation rate and determining the end of the primary stage of freeze drying. Unfortunately, the sensitivity of the capacitive sensor of this design is not enough for the reliable monitoring of the stage of secondary drying.In this paper, a new design of a capacitive sensor and measurement technique are proposed that enable monitoring all stages of the drying process: the freezing stage, the sublimation stage, and the final stage. During freezing and the sublimation stages, the sensor monitors the amount of liquid phase in the frozen material. This allows an optimal control during the whole sublimation stage which prevents the foaming of the material and significantly reduces the total drying time. The sensor also fixes the end of the sublimation stage and the beginning of the final stage of drying. At this stage, the high sensitivity of the measuring system enables one to discover that there is a certain time interval when the signal of the capacitive sensor passes through a maximum. We believe that this maximum corresponds to the minimum of the molecular mobility of biological macromolecules and the optimal residual moisture of the material to be dried.     

Genetic Characterization of Vibrio vulnificus Strains from Tilapia Aquaculture in Bangladesh

Outbreaks of Vibrio vulnificus wound infections in Israel were previously attributed to tilapia aquaculture. In this study, V. vulnificus was frequently isolated from coastal but not freshwater aquaculture in Bangladesh. Phylogenetic analyses showed that strains from Bangladesh differed remarkably from isolates commonly recovered elsewhere from fish or oysters and were more closely related to strains of clinical origin.Vibrio vulnificus causes severe wound infections and life-threatening septicemia (mortality, >50%), primarily in patients with underlying chronic diseases (10, 19, 23) and primarily from raw oyster consumption (21). This Gram-negative halophile is readily recovered from oysters (27, 35, 43) and fish (14) and was initially classified into two biotypes (BTs) based on growth characteristics and serology (5, 18, 39). Most human isolates are BT1, while BT2 is usually associated with diseased eels (1, 39). An outbreak of wound infections from aquacultured tilapia in Israel (6) revealed a new biotype (BT3). Phenotypic assays do not consistently distinguish biotypes (33), but genetic analyses have helped resolve relationships (20). A 10-locus multilocus sequence typing (MLST) scheme (8, 9) and a similar analysis of 6 loci (13) segregated V. vulnificus strains into two clusters. BT1 strains were in both clusters, while BT2 segregated into a single cluster and BT3 was a genetic mosaic of the two lineages. Significant associations were observed between MLST clusters and strain origin: most clinical strains (BT1) were in one cluster, and the other cluster was comprised mostly of environmental strains (some BT1 and all BT2). Clinical isolates were also associated with a unique genomic island (13).The relationship between genetic lineages and virulence has not been determined, and confirmed virulence genes are universally present in V. vulnificus strains from both clinical and environmental origins (19, 23). However, segregation of several polymorphic alleles agreed with the MLST analysis and correlated genotype with either clinical or environmental strain origin. Alleles include 16S rRNA loci (15, 26, 42), a virulence-correlated gene (vcg) locus (31, 41, 42), and repetitive sequence in the CPS operon (12). DiversiLab repetitive extrageneic palindromic (rep-PCR) analysis also confirmed these genetic distinctions and showed greater diversity among clinical strains (12).Wound infections associated with tilapia in Israel implicated aquaculture as a potential source of V. vulnificus in human disease (6, 40). Tilapia aquaculture is increasing rapidly, as shown by a 2.8-fold increase in tons produced from 1998 to 2007 (Food and Agriculture Organization; http://www.fao.org/fishery/statistics/en). Therefore, presence of V. vulnificus in tilapia aquaculture was examined in Bangladesh, a region that supports both coastal and freshwater sources of industrial-scale aquaculture. V. vulnificus strains were recovered from market fish, netted fish, and water samples, and the phylogenetic relationship among strains was examined relative to clinical and environmental reference strains collected elsewhere.     

Impacts of Inter- and Intralaboratory Variations on the Reproducibility of Microbial Community Analyses

With the advent of molecular biological techniques, especially next-generation sequencing and metagenomics, the number of microbial biogeography studies is rapidly increasing. However, these studies involve the synthesis of data generated by different laboratories using different protocols, chemicals, etc., all with inherent biases. The aim of this study was to assess inter- as well as intralaboratory variations in microbial community composition when standardized protocols are applied to a single soil sample. Aliquots from a homogenized soil sample from a rice field in Italy were sent to five participating laboratories. DNA was extracted by two investigators per laboratory using an identical protocol. All DNA samples were sent to one laboratory to perform DNA quantification, quantitative PCR (QPCR), and microarray and denaturing gradient gel electrophoresis (DGGE) analyses of methanotrophic communities. Yields, as well as purity of DNA, were significantly different between laboratories but in some cases also between investigators within the same laboratory. The differences in yield and quality of the extracted DNA were reflected in QPCR, microarray, and DGGE analysis results. Diversity indices (Shannon-Wiener, evenness, and richness) differed significantly between laboratories. The observed differences have implications for every project in which microbial communities are compared in different habitats, even if assessed within the same laboratory. To be able to make sensible comparisons leading to valid conclusions, intralaboratory variation should be assessed. Standardization of DNA extraction protocols and possible use of internal standards in interlaboratory comparisons may help in rendering a “quantifiable” bias.Microorganisms comprise a major part of total biomass and biodiversity (21, 41-43, 49). They play a critical role in biogeochemical processes and ecosystem functioning (16). However, knowledge of ecology and functioning of environmental microbial communities is still far from complete, mainly due to our inability to grow the majority of environmental microbes under laboratory conditions. The introduction of culture-independent DNA- and RNA-based techniques has led to a revolution in environmental microbiology, yielding a wealth of information on community compositions in an ever-growing range of habitats. Phylogenetic as well as functional microarrays (51) and metagenomic techniques (41, 47) enable in-depth analyses and comparison of whole microbial communities in a high-throughput manner.The collective goal of all environmental microbial ecology studies is 2-fold: (i) to obtain an overall understanding of microbial community composition, dynamics, and functioning and (ii) to identify regulating mechanisms. Reaching these goals will necessitate the integrated analyses of data generated in different laboratories and from different habitats. The first step in most if not all environmental microbial community studies is the extraction of total DNA from environmental samples in a way that reflects the in situ community composition as closely as possible. Numerous methods, protocols, and commercial kits have been developed to improve and optimize quantity and quality of extracted community DNA from a wide range of natural environments (4, 8, 28, 37, 39). However, up-to-date bias-free extraction methods are not available, especially not for complex and highly variable matrices, like soil. Beside the challenge of lysing all cells, the incomplete removal of compounds interfering with downstream processing render the development of a bias-free protocol a “mission impossible.” Assessments of the bias introduced by DNA extraction with different methods and kits on microbial community profiling revealed that a perfect protocol fitting all types of environments is not feasible (10, 17, 20, 45). However, in light of the global biodiversity debate, assessment of local and global patterns of microbial diversity and their controlling factors (19, 26) necessitates the comparison of data collected in multiple habitats and processed in different laboratories.In contrast to other scientific disciplines, intercalibration of protocols is not common practice in environmental microbiology. Interlaboratory comparisons (ring analyses) have been applied commonly in food control, veterinary, forensic, and soil studies to evaluate, for example, Salmonella diagnostic accuracy (25), virus isolation (18), enzyme-linked immmunosorbent assay methods (2), mitochondrial DNA sequencing (30), soil microbial biomass C (3), and quantitative PCR (QPCR) (11). Ring analyses assessing the reproducibility of DNA extraction and subsequent community analyses between different laboratories have not been carried out so far in environmental microbial ecology.A microbial functional guild that has been investigated intensively using molecular techniques is represented by the methanotrophs (aerobic methane-oxidizing bacteria [MOB]), which can be found in a wide variety of environments (27). The unique contribution of these bacteria to the global methane cycle has rendered the diversity and ecology of MOB hot topics for decades (9, 14, 34, 46, 48). By using methane as single source of carbon and energy, these microbes represent the only biological sink of the greenhouse gas methane under aerobic conditions (13). Aerobic MOB belong to the Gamma- and Alphaproteobacteria and the Verrucomicrobia (13, 34) and have the following features that enable linking function and identity. Assimilating methane facilitates the application of stable isotope probing of diagnostic lipids and of RNA/DNA (6, 29, 33). Besides this, the key gene in methane oxidation (for methanemonooxygenase subunit A, pmoA) reflects the phylogeny of these bacteria, facilitating a direct link between methane consumption and taxonomy. These features have made this group of microbes a model group for studies in environmental microbial ecology. Combined with the broad distribution and high environmental relevance, this group is highly suited to perform a ring analysis on reproducibility of DNA extraction and subsequent community profiling.In the present study, five independent laboratories from Norway, Finland, Netherlands, Germany, and Austria extracted DNA from the same rice field soil sample, using identical protocols and performed by two different investigators per laboratory. Subsequently, the extracted DNA was sent to one laboratory, where DNA quantification, QPCR, microarray, and denaturing gradient gel electrophoresis (DGGE) analyses were performed by one and the same person. The impacts of inter- as well as intralaboratory variations of DNA extraction are discussed, and recommendations for comparative studies are presented.     

Identification of Diverse Antimicrobial Resistance Determinants Carried on Bacterial,Plasmid, or Viral Metagenomes from an Activated Sludge Microbial Assemblage

Using both sequence- and function-based metagenomic approaches, multiple antibiotic resistance determinants were identified within metagenomic libraries constructed from DNA extracted from bacterial chromosomes, plasmids, or viruses within an activated sludge microbial assemblage. Metagenomic clones and a plasmid that in Escherichia coli expressed resistance to chloramphenicol, ampicillin, or kanamycin were isolated, with many cloned DNA sequences lacking any significant homology to known antibiotic resistance determinants.Activated sludge in wastewater treatment plants is an open system with a dynamic and phylogenetically diverse microbial community (2, 3, 6, 7, 10, 11). Since the activated sludge process promotes cellular interactions among diverse microorganisms, there is great potential for the lateral transfer of antibiotic resistance genes between microbes in activated sludge and in downstream environments. Several studies have previously identified antibiotic resistance determinants from wastewater communities that are carried on bacterial chromosomes (1, 4, 14) and plasmids (9, 12, 13), but to our knowledge, a simultaneous metagenomic survey of antibiotic resistance determinants from all three genetic reservoirs (i.e., chromosomes, plasmids, and viruses) has never been performed within the same environment. To achieve a more comprehensive assessment of antibiotic resistance genes in the activated sludge microbial community, this study used both function- and sequence-based metagenomic approaches to identify antibiotic resistance determinants carried on bacterial chromosomes, plasmids, or viruses within an activated sludge microbial assemblage.