M. leprae strains, as obtained in the first and the second diagnosis, had any known genomic variants associated to resistance to Multidrug therapy; in addition, whole genome sequencing indicated that the same M. leprae was causing two out of the three recurrences. Thus, these individuals were suspected of being particularly susceptible to M. leprae infection, either as relapse or reinfection. To verify this hypothesis, 19 genetic markers distributed across 11 loci (14 genes) classically associated with leprosy were genotyped in the recurrent and in three matching non-recurrent leprosy cases. An enrichment of risk alleles was observed in the recurrent cases, suggesting the existence of a particularly high susceptibility genetic profile among leprosy patients predisposing to disease recurrence.Host genetic susceptibility to leprosy has been intensively investigated over the last decades; however, there are no studies on the role of genetic variants in disease recurrence. A previous initiative identified three recurrent cases of leprosy for which none of the  Mycobacterium leprae, an obligatory intracellular, slow growing, alcohol-acid resistant bacillus with tropism for skin macrophages and Schwann cells of the peripheral nervous system1. The disease affects more than 200.000 people every year globally, with high incidence and prevalence concentrating in India and Brazil2. Leprosy presents a large spectrum of clinical manifestations that varies depending on the host’s immune response, ranging from the localized tuberculoid to the systemic lepromatous forms as defined in the classic Ridley & Jopling classification system3. Alternative, the World Health Organization (WHO) classification protocol distributes leprosy cases as paucibacillary (PB) or multibacillary (MB) for treatment purposes4.Leprosy is a chronic infectious disease caused by 5; treatment is distributed for free in endemic countries since 19956. Currently, there is the proposal for a uniform multidrug therapy regimen for leprosy patients that consists of six doses of MDT prescribed regardless of any clinical classification criteria. A Clinical Trial for Uniform Multidrug Therapy Regimen for Leprosy Patients in Brazil, (U-MDT/CT-BR) was recently conducted to compare outcomes of regular 12 doses MDT (R-MDT) and the uniform six doses MDT (U-MDT). The study included results from laboratory tests  and clinical evaluation during long term follow-up7. Among the recurrent cases of leprosy identified in the U-MDT/CT-BR trial; for three of them, M. leprae isolates obtained in the first and second diagnosis were submitted to whole genome sequencing (WGS); analyses did not show any mutations associated with drug resistance. Based on comparative analysis between M. leprae genomes obtained in the first and second infection of each patient, the authors concluded for two cases of relapses caused by same strain and one case of reinfection caused by a different M. leprae strain8.Leprosy is treated by a multidrug therapy (MDT) consisting of rifampicin, dapsone and clofazimine carried out for six monthly doses for PB patients and for 12 monthly doses for MB patientsM. leprae strain recovered from the three reinvestigated recurrent cases, it is reasonable to assume that leprosy recurrence was not due to characteristics of the etiologic agent but yet, to a combination of continuous exposure to M. leprae associated with an increased host susceptibility genetic background.Considering that (i) all patients were followed and completed the treatment correctly, (ii) U-MDT was efficient in treating the disease, and (iii) no mutation associated with drug resistance was detected in the genomes of any 9. Among them, genes HLA-DR-DQ 10, LTA 11, IL10 (interleukin 10)12, PRKN/PACRG (parkin RBR E3 ubiquitin protein ligase/parkin coregulated gene)13, NOD2 (nucleotide binding oligomerization domain containing 2)14, LACC1/CCDC122 (laccase domain containing 1/coiled-coil domain containing 122)14, SOD2 (superoxide dismutase 2)15, NEBL (nebulette) (unpublished data), GATA3 (GATA binding protein 3)16, IFNG (interferon gamma)17 and TLR1 (toll like receptor 1)18 have been associated with leprosy in Brazilian population samples, the majority of them playing important roles related to the host immune system. However, to date, no attempt has been made to translate this genetic knowledge into the definition of an individual susceptibility profile that could help explain complex leprosy phenotypes such as recurrence/reinfection. Here we genotyped 19 Single Nucleotide Polymorphism (SNP) distributed across these 11 loci associated with leprosy per se on six leprosy cases from the U-MDT/CT-BR cohort: two cases previously reported as relapses and one as reinfection8, and three matching, successfully treated leprosy patients that did not relapse. Allele frequencies were compared across the two groups and with publicly available databases.Host genetics accounts for a great proportion of disease heritability in leprosy and many genes were already identified with substantial evidences in support of their association with leprosyAll 19 SNPs were successfully genotyped for all six samples of leprosy patients and results are summarized in Table loci PRKN/PACRG (r2 = 1 between rs1040079 and rs2276201 and r2 = 0.7 between rs1040079 or rs2276201 and rs9356058), LTA, (r2 = 0.5 between rs2239704 and rs909253), NOD2 , HLA-DRB1/DQA1 (r2 = 0.46 between rs602875 and rs1071630) and CCDC122/LACC1 (r2 = 1 between rs2275252 and rs4942254). Importantly: it is possible that high LD is in fact reflecting the additive effect of two or more variants of distinct functional impact upon the net risk for that gene. This effect would be similar to what has been observed previously for gene TNFSF819: extensive LD has been detected between associated markers identified as independent expression quantitative trait loci (eQTL) for TNFSF8; the authors argue that this combined functional impact could reflect the high correlation observed between the SNP alleles.Comparison of the combined genotypic distribution of all variants tested between the two groups revealed an enrichment of homozygous genotypes for the risk alleles among the three recurrent patients Table : 40% vs.M. leprae strains isolated in the first and the second diagnosis8. Also, patient #1126 presented the shortest time to relapse and the latest age of diagnosis – 32 years – similar to the controls  and TNFSF15-TNFSF822 (leprosy reaction). The enrichment of risk alleles observed for recurrent patients #3208 and #2188 is compatible with the hypothesis that early onset leprosy is more heavily dependent on genetic mechanisms, whereas late onset disease is a balanced combination of genetic and environmental factors.It is interesting to note that recurrent patient #1126 presented allelic and genotypic global counts similar to the controls and in contrast with the two other recurrent individuals. Patient #1126 has been described previously as the only case of recurrence caused by distinct IL10, PACRG, NOD2, HLA-DRB1/DQA1, LTA, GATA3, IFNG and TLR1 – when relapse cases are compared with controls and the frequency available on public databases  of the Ministry of Health, protocol number 12949/2007, as previously describedM. leprae strain and one was considered a reinfection caused by a distinct M. leprae isolate8. The three non-recurrent patients were matched with the recurrent cases by leprosy clinical form, ethnicity , bacilloscopic index, treatment protocol, occurrence of leprosy reaction and place of residence . A summary of the demographic and diagnostic information is presented in Table Six male leprosy patients were selected from the previous U-MDT/CT-BR study; three did not relapse during an eight-year follow-up; two were diagnosed as relapse caused by the same 23; the DNA was quantified spectrophotometrically using NanoDrop 2000/2000c and the concentration of genomic DNA was normalized to 20 ng/µL. Genotyping was performed by fluorescence-based allelic discrimination using TaqMan, as implemented in the Applied Biosystems® 7500 Real-Time PCR platform. The reactions mix was composed by ultrapure water (1.9 μl per sample), TaqMan® SNP Genotyping Assays , TaqMan™ Genotyping Master Mix  and template DNA (3 μl). Reaction was conducted using a denaturing temperature of 95 °C for 15 seconds and an oligonucleotide hybridization and extension temperature of 60 °C for 2 minutes on each of a total of 50 cycles.Genes were selected for genotypic analysis based on previous evidence for validated/replicated association with leprosy in Brazilian population samples. SNP markers have been selected based on previous published, association with leprosy in one or more Brazilian population samples and/or in previous genome-wide association studies (GWAS) (Supplementary Table Linkage disequilibrium (LD) was estimated using Haploview v.4.2 using the combined dataset of all six patients. A descriptive analysis was performed using the Statistical Package for the Social Sciences (SPSS) v.22. Genetic profiles of recurrent and non-recurent cases were described against the frequencies of risk/protection alleles obtained from previous studies as available on Ensembl Genome Browser with data of 1000 genomes, phase 3, combined population. The Fisher’s exact test for small sample sizes was used to compare combined allelic and genotypic frequencies across the two groups.Our study presents, for the first time, suggestive evidence that genes associated with susceptibility to leprosy may also play an important role on disease recurrence. Our data indicates that a combination of alleles in different genes may confer hyper-susceptibility to leprosy detectable even among leprosy susceptible individuals, increasing the chances of disease recurrence. In addition, one could speculate, based on the allelic profile of patient #1126 – similar to the non-recurrent and distinct of the other two recurrent individuals – on the possible existence of distinct genetic mechanisms controlling disease relapse and reinfection. We are fully aware of the limitations of our design, particularly related to the small sample size; thus, this mainly descriptive, qualitative report of a series of cases must be perceived as a hypothesis-generating initiative, opening the possibility for additional studies of larger sample sizes of non-recurrent and recurrent leprosy affected individuals, aiming to identify biomarkers of risk of reinfection that may be used to monitor treated patients continuously exposed to the bacilli in endemic areas, with potential positive effects over leprosy control programs.Supplementary Dataset Number-Supplementary-information.


FH) are prime targets of HIV infection—this creates a sanctuary for infected cells because CD8+ T cells generally do not enter lymph node follicles unless they express CXCR5, and are not as effective at killing infected CD4+ T cells as peripheral CD8+ T cells. In this review, we summarize the current state of research on TFH cell infection in peripheral lymphoid tissues and focus on the question of whether CD8+ T cell exclusion from B cell follicles is responsible, at least in part, for establishing secondary lymphoid tissue B cell follicles as an anatomic site of HIV transcription and replication.As we learn more about the HIV latent reservoir, we continue to discover that the viral reservoir is more complicated than just a pool of infected resting memory CD4+ T cells in peripheral blood. Evidence increasingly points to both certain tissues and certain types of cells as potential viral reservoirs. T follicular helper cells (T As we approach the 5th decade of the HIV pandemic and after years of intensive cure study, we continue to find a cure for HIV outside the reach of natural immunity due to the persistence of the latent reservoir found in resting memory CD4+ T cells. Retrovirus replication has several unique properties that have made eradication a challenge. Recent evidence suggests that the HIV reservoir is established in the very early stages of HIV infection , 2. As CMost studies of the latent reservoir have been done exclusively using peripheral blood mononuclear cells (PBMCs). This presents a problem for accurate estimation of the size of the reservoir as many lymphocytes in the body reside in the lymphatic system and tissues. Therefore, throughout the body there are likely other reservoirs and sanctuaries for HIV which may have different characteristics from the peripheral blood reservoir .Simian immunodeficiency virus (SIV)-infected primates support the hypothesis that CD8+ T cell immunity is critical to natural control of HIV infection. An early HIV-specific CD8+ T cell immune response is associated with increased viral control compared to patients that lack an early cytotoxic T lymphocyte (CTL) response (Studies in people living with HIV (PLWH) and response . SIV-infresponse –12.*57 and HLA-B*27 are significantly overrepresented in ECs , gut-associated lymphoid tissue (GALT), and all lymph nodes. Secondary lymphoid tissues contain large numbers of CD4+ lymphocytes susceptible to infection, and recent studies continue to support the hypothesis that follicles within secondary lymphoid tissues represent a major site of viral persistence. Using inguinal lymph nodes collected from viremic HIV patients, Folkvord et al. showed that CD4+ T cells within follicles are 31 times more likely to be positive for HIV RNA than CD4+ T cells in extrafollicular sites . The samin situ hybridization, there are consistently higher concentrations of SIV+ RNA in follicular than extrafollicular zones in multiple secondary lymphoid organs, including peripheral lymph nodes, the spleen, and GALT in multiple sites , located within germinal centers of secondary lymphoid tissues. A brief review of lymph node (LN) structure and function is provided in FH cells may contribute to the reservoir. LNs are secondary lymphoid tissues that are dispersed throughout the body along the lymphatic vasculature. Since they number in the hundreds, these are relatively easy sites of secondary lymphoid tissue to surgically biopsy, and so they are some of the most commonly studied secondary lymphoid tissue in HIV infection.How has HIV been able to “hide” in lymphoid tissues so effectively? Much of the answer likely lies with the follicular helper T cell subset  infected mice, a frequently used mouse model of chronic viral infection with some similarities to HIV infection , 73. TheFH cells with the possible inability of these CD8+ T cells to either access or kill infected cells within B cell follicles? There are several groups that are working on strategies to specifically direct CD8+ T cells into follicles at the site of smoldering HIV infection of TFH cells. One possibly strategy uses pharmacologic chemokines to direct CD8+ T cells into the B cell follicles. The cytokine IL-15 is important for maintenance of memory CD8+ T cells, so IL-15 agonists are an attractive pharmacologic target to boost CD8+ T cell-mediated HIV-1 immunity. Webb et al. showed recently that the IL-15 superagonist ALT-803 both activates and induces migration of CD8+ T cells into B cell follicles (in vitro (How do we reconcile the need for CD8+ T cell immune responses within B cell follicles to target HIV-infected Tollicles . ALT-803ollicles . Watson ollicles . Taking ollicles . Conversin vitro , indicatHowever, it should be noted that, immunologically speaking, having follicular CD8+ T cells capable of killing within a lymphoid follicle could lead to the disruption of the follicle and the immune response itself. It seems that the existence of a mechanism to exclude activated CD8+ T cells or prevent killing within follicles may be necessary to maintain the integrity of the immune response, but further studies in this area are sorely needed.Years of HIV and SIV latency research has revealed several important conclusions, first that lymphoid tissues represent a major site for HIV replication in viremic individuals and a significant reservoir of inducible virus in patients on ART. Secondly, CD4+ helper T cells are more likely to be productively infected within lymphoid follicles compared to extrafollicular sites. And finally, cytotoxic CD8+ T cells appear to be unable to effectively target these HIV infected cells when localized to a lymphoid follicle. The mechanisms behind the inability of CD8+ T cells to kill productively infected CD4+ cells in follicles are not completely understood. There is evidence that lymphoid CD8+ T cells have deficient cytolytic capabilities compared to CD8+ T cells in peripheral blood, other studies suggest that the CD8+ T cells are unable to target HIV infected CD4+ cells in follicles because of the lack of expression of appropriate chemokine homing receptors, therefore excluding the CD8+ T cells from trafficking to follicular sites of HIV replication. Regardless of the exact mechanism, ineffective CD8+ T cell killing of HIV-infected CD4+ helper T cells in secondary lymphoid tissue follicles is a major barrier to any strategy of HIV cure that relies on CTL-mediated eradication of infected CD4+ T cells. Further studies are needed to clarify the functionality of follicular CD8+ T cells in chronic HIV infection, to discover new ways of targeting CD8+ cells effectively to a major site of ongoing HIV replication as well as to determine if CTL killing within a follicle will alter the integrity of the immune response. Hopefully these future studies will enable scientists to effectively target and eliminate an important sanctuary of infected CD4+ T cells.SB wrote the manuscript. RV and JB reviewed and edited the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Maize is a crop in high demand for food purposes and consumers worldwide are increasingly concerned with food quality. However, breeding for improved quality is a complex task and therefore developing tools to select for better quality products is of great importance. Kernel composition, flour pasting behavior, and flour particle size have been previously identified as crucial for maize-based food quality. In this work we carried out a genome-wide association study to identify genomic regions controlling compositional and pasting properties of maize wholemeal flour.dull endosperm 1 gene that encodes a starch synthase and is determinant on the starch endosperm structure in maize.A collection of 132 diverse inbred lines, with a considerable representation of the food used Portuguese unique germplasm, was trialed during two seasons, and harvested samples characterized for main compositional traits, flour pasting parameters and mean particle size. The collection was genotyped with the MaizeSNP50 array. SNP-trait associations were tested using a mixed linear model accounting for genetic relatedness. Fifty-seven genomic regions were identified, associated with the 11 different quality-related traits evaluated. Regions controlling multiple traits were detected and potential candidate genes identified. As an example, for two viscosity parameters that reflect the capacity of the starch to absorb water and swell, the strongest common associated region was located near the This study allowed for identifying relevant regions on the maize genome affecting maize kernel composition and flour pasting behavior, candidate genes for the majority of the quality-associated genomic regions, or the most promising target regions to develop molecular tools to increase efficacy and efficiency of quality traits selection (such as “breadability”) within maize breeding programs.The online version of this article (10.1186/s12870-019-1729-7) contains supplementary material, which is available to authorized users. Maize is one of the most important food crops worldwide, and a staple crop for large populations in Latin America, Africa, and Asia . Maize bThe maize kernel’s high nutritional value is mainly due to its starch (~ 72% of the kernel dry matter), protein (~ 10% of the kernel dry matter), and fat in the form of oil (~ 4% of the kernel dry matter) . The intMany maize mutants have been widely used to isolate genes encoding key enzymes in starch metabolism, as well as genes regulating zeins, maize primary storage proteins, synthesis and deposition , 10. Curbrittle endosperm2 (bt2), shrunken1 (sh1), and shrunken2 (sh2) that were associated with several kernel compositional traits, and haplotypes of amylose extender1 (ae1) and sh2 that were associated with starch pasting properties.Linkage mapping and association mapping studies have shown that kernel main components are controlled by many genes having complex patterns of inheritance. Examples are the works of Li et al.  and Li ebroa )operties ; brittlein maize , 29. ThiGRMZM2G1499, du1, DGAT1–2) . Indeed,GRMZM2G1499, du1, The rapid rate of LD decay observed in the present study in the SNPs associated with the quality-related traits evaluated suggests that a higher marker density would have been beneficial in the detection of other regions putatively linked to maize flour’s quality. Moreover, it is important to mention that the size of the collection of maize inbred lines used in this work most likely affected the power to detect significant marker-trait associations and the subsequent identification of genomic regions controlling the analyzed traits association. As reported in Yang et al. , using sThis work reports the identification of 57 genomic regions associated with 11 different quality-related traits evaluated in wholemeal maize flour, highlighting candidate genes for the majority of those regions. However, novel regions, with no clear candidate genes, were also identified, which were not previously acknowledged using other germplasm collections studies.Findings from GWAS provide valuable genetic information of trait architecture or candidate loci for subsequent validation . PrelimiNevertheless, prior to that, the significant marker-trait associations detected in the current work need to be validated. Future work will concentrate on the validation of the results retrieved in this work by sequencing those regions on contrasting maize populations for the given trait. Since the actual materials used for the manufacturing of maize-based bread are the traditional maize populations, these are the ideal independent materials to proceed with the sequencing validation.broa production.In this work, a genome-wide association approach was carried out to identify genomic regions controlling the variation of maize kernel major constituents  and parameters affecting the maize flour “breadability” (starch pasting properties and flour’s mean particle size). For that, a unique maize inbred collection containing lines partially derived from Portuguese maize populations was used given that Portuguese traditional maize populations have been developed through centuries adapted both to the local environment and food uses, in particular, for The inbred lines derived from Portuguese maize populations were overall characterized by having a low breakdown and peak viscosity, and starch content; and a high fiber and protein content. A putative positive selection toward the presence of the favorable alleles for protein content, for fiber content, and mean particle size, and for alleles associated with a decrease in breakdown and peak viscosities values and a decrease in starch content was observed in the inbred lines derived from Portuguese traditional maize populations.This work allowed for identifying relevant regions on the maize genome affecting maize kernel composition and flour pasting behavior, and identifying candidate genes for the majority of the flagged genomic regions. A total of 57 genomic regions were detected and candidate genes underlying the majority of those regions were identified. Moreover it was observed that the majority of the detected genomic regions were associated with a single trait. The traits for which the strongest and stable associations were found were protein, breakdown viscosity and peak viscosity. For those the strongest SNP-trait association could result in changes from more than 4% in protein content to more than 10% in the case of the viscosity parameters. Importantly, this work allowed reducing the gap towards the development of selection tools to support breeding for these complex quality traits, such as “breadability”.In this work, we took advantage of the diverse inbred lines developed in the past by the extinct NUMI (Núcleo de Melhoramento de Milho) combining Portuguese germplasm with foreign (mainly US) germplasm. These inbred lines (developed by single seed descent) are currently conserved at the National Portuguese Plant Germplasm Bank . The maize inbred line collection used in this study was assembled observing a significant representation of lines selected from Portuguese traditional maize populations (29 lines) and lines with a mixed Portuguese × foreign origin  in Portugal during the 2011 and 2012 growing seasons, using an organic agriculture converted field. The conversion started in 2011 and the field was considered to be fully managed under an organic agriculture system by 2012. This site is part of the Mondego River irrigation perimeter, a very high-yielding maize area where the average maize hybrids yield is 14.5 Mg.ha− 1 . It is l− 1. Plots were both mechanically weeded and hand-weeded when needed and managed following common agricultural practices for maize in the region. Pollination was controlled within each plot. All the plots were harvested by hand. After harvest, ears were dried at 30–35 °C in an oven  until a ~ 15% in moisture was reached. The ears were then shelled, and the kernel collected per plot basis was packed in paper bags and kept at 4 °C until further analysis.In each year, the maize inbred lines were evaluated using a randomized complete block design, with two blocks (replicates). Information on the spatial distribution of the plots was also recorded (field row and columns coordinates). Each plot consisted of two rows 7.2 m long (6.4 m planted row plus 0.8 m border space between two planted rows), with an inter-row distance of 0.75 m. Each plot was overplanted by hand and thinned at the V7 growth developmental stage to achieve a plant density of approximately 50,000 plants haA seed sample from each of the harvested plots was used for quality determinations in the two years/growing seasons. Eleven nutritional-related and technological-related traits were measured in wholemeal maize flour. Wholemeal maize flour was obtained from all the seed samples using a Falling number 3100 mill  with a 0.8 mm screen. In order to prevent/minimize the enzymatic action and subsequent alteration of the flour properties, flour samples were also lyophilized using Cientificolab® equipment built for pilot-scale lyophilization of food commodities. For that, each sample was individually placed in a flask  and then freeze-dried for long-term preservation.Flour protein (PR), fiber (FI), and fat (FT) content were determined for each non-lyophilized sample by near-infrared reflectance (NIR) spectroscopy , with calibrations for non-lyophilized samples supplied by the manufacturer. Values for protein, fiber, and fat corresponded to the mean value of up to two technical replicates. The total starch content was determined in lyophilized (STL) (both 2011 and 2012 growing seasons) and non-lyophilized (ST) (only the 2012 growing season) samples using Fourier Transform Near-Infrared Reflectance (FT-NIR) spectroscopy , with calibrations for non-lyophilized samples supplied by the manufacturer. Values for total starch content obtained from the 2012 growing season lyophilized and non-lyophilized samples were further used to test whether both datasets were correlated (phenotypic correlation between datasets). Values for total starch content (non-lyophilized (ST) and lyophilized (STL) samples) corresponded to the mean value of two to four technical replicates. Protein, fiber, fat, and starch content was expressed as a percentage (%).The maize flour Particle Size Index (PSI) was also determined using FT-NIR spectroscopy . For the 2011 growing season, only the mean for particle size in lyophilized samples (SIZEL) was measured. For the 2012 growing season, both mean particle size in non-lyophilized (SIZE) and lyophilized flours (SIZEL) were determined. Values for mean particle size (non-lyophilized (SIZE) and lyophilized (SIZEL) samples) corresponded to the mean value of two to four technical replicates. The calibration models for PSI FT-NIR analysis were obtained using the particle size values measured in a subset of 30 non-lyophilized samples according to the AACC method 55–40.01:1999 , with a Maize flour pasting properties were evaluated by recording their viscosity profiles using a Rapid Visco Analyser (RVA) . The viscosity profiles were obtained on non-lyophilized samples according to  at 15% sQuality control was performed for each year/growing season, on the data collected per genotype individually from each of the two replicated plots. Graphical inspection of residuals was used to assess normality (Q-Q plot), homogeneity of variance , and identify outliers. Observations were flagged for closer inspection when they exceeded 1.5 times the interquartile range, and when the standardized residuals after mixed model analysis were extreme. One of the traits  required a squared-root-transformation to stabilize the variance. All analyses were done using Breeding View software , availabA phenotypic analysis was performed per single environment trial: 1) the estimates of genetic variances (and covariances between traits) and of heritability were obtained according to Oakey et al. , and 2) In detail, single trait-single growing season analysis, using mixed models, was performed using the “Single trait field trial analysis” pipeline of Breeding View, selecting the model for resolvable row-column design as implemented in the software. The statistical model includes an intercept, a fixed block effect, a random row and column effects (nested within blocks), a genotypic effect , and a residual. The Field trial analysis node in Breeding View performs two mixed model analyses: In the first step (Step 1) the inbred lines (genotypes) were fitted as a random term, while in the second step (Step 2) the inbred lines were fitted as a fixed term. The Step 1 model is used to obtain estimates of variance parameters. From Step 1 the heritability, as well as the best linear unbiased predictors (BLUPs), was calculated for each inbred line (and correlations between BLUPs of different traits used to obtain estimates of genetic correlations between traits). In Step 2, structural variance components (rows and column variances) are fixed to those estimated in Step 1, and by including the inbred lines as a fixed term, the best linear unbiased estimators (BLUEs) for each inbred line were produced.For each quality trait, a multi-environment trial analysis was also performed to assess the consistency across growing seasons. The analysis of variance was carried out using the residual maximum likelihood (REML) variance components analysis procedure in Genstat software . The miDNA was isolated from adult leaves from each maize inbred line using a modified CTAB procedure described in . DNA quawww.maizegdb.org).The position of each marker along the maize B73 reference genome was updated from the markers’ coordinates available when the MaizeSNP50 BeadChip was originally designed (B73 reference genome version 1) to the coordinates in the released B73 reference genome version 3. These coordinates were taken from the maize genome browser, via the MaizeGDB database . Moreover, markers with a minor allele frequency (MAF) smaller than 5% were removed. After this filter, a total of 48,772 SNPs remained and were used for the association mapping analysis.A subset of 1821 SNPs, evenly distributed across the genome , was used to calculate principal components to study the population structure among inbred lines and to calculate the kinship matrix to estimate pairwise genetic relatedness among inbred lines as implemented in Genstat software .2g × y) were much smaller than the genotype variance component (σ2g), univariate association analysis was carried out using the adjusted means for field trial design (BLUEs) obtained across growing seasons. Genome-wide association studies were conducted with the Genstat software using the available genotypic (SNPs scored with the MaizeSNP50 BeadChip array) and quality data  measured in 132 maize inbred lines. The Genstat software performs association mapping in the mixed model framework, fitting markers as fixed and inbred lines as random terms using REML , that neither accounts for population structure nor familial relatedness; a model accounting for population structure (Q) using 15 principal components from PCA [Phenotype = Q + SNP + (Genotype + Error)]; and a model accounting for familiar relatedness (K) [Phenotype = SNP + Genotype + Error] with Genotype random effects structured following a kinship matrix K. For each chromosome, a different kinship matrix was calculated where only the SNPs located on the other nine maize chromosomes were used to calculate the kinship matrix [Three different models were tested to detect significant marker-trait associations: the naïve model [p matrix , 47.P-values allowed to informally assess to what extent the models accounted for genetic structure/relatedness among the inbred lines and therefore guarded against false discoveries. Models resulting in an inflation factor near 1 perform better, and quantile-quantile (Q-Q) plots should show few P-values that deviate from the expected uniform distribution that holds under the null hypothesis . The observed P-values  of each SNP were plotted against their chromosomal positions so they produce Manhattan plots. A threshold of –log10  = 4 was set to identify significant marker-trait associations. Given that the association panel used was not that large and looking at the background noise in the obtained Manhattan plots, the threshold of -log10  = 4 seemed reasonable not to avoid losing potentially interesting regions, at the expense of applying a more conservative type of correction such as Bonferroni. Examples of other maize studies with similar association panel sizes and number of markers using the same threshold are the works of Liu et al. [The inspection of the inflation values for each model and the quantile-quantile (Q-Q) plots of the respective u et al. , 49. TheA local linkage disequilibrium (LD) study was performed to define chromosomal regions to search for candidate genes for the traits under analysis.2, after correcting for population structure using the principal component scores from Eigenanalysis, as implemented in Genstat software. For this calculation, the same subset of 1821 SNPs previously used for the genetic structure analysis was employed. LD decay was visualized per chromosome by plotting r2 against the physical mapping distance in Mb. A threshold for LD decay (r2 = 0.1) was used to estimate the average genetic distance for which markers were considered to be no longer correlated. In Step 2, a genomic window around each SNP location significantly associated with the traits analyzed was established by subtracting and adding the average genetic distance for LD decay (r2 > 0.1), estimated in Step 1. All the SNP markers located within those windows were then used to estimate the local LD decay. At this point, a stricter threshold of r2 = 0.2 was considered. The markers’ positions flanking each local LD block were further used as query positions on the maize genome browser, via MaizeGDB (https://www.maizegdb.org/gbrowse/), to retrieve the list of candidate genes mapped within those genomic regions.This procedure was done in two steps: In Step 1, the average intra-chromosomal LD was estimated as the squared correlation coefficient rZea mays B73 RefGen_v3) was used as the reference genome for candidate gene analyses [Zea mays Ensembl-18) using the gene model identifier as the query. KEGG: Kyoto Encyclopedia of Genes and Genomes database [The genome sequence of the maize inbred line B73 Additional file 2:Table S2. Estimated genetic correlations among quality traits measured in wholemeal flour of a collection of 132 maize inbred lines. In Table S2 one can find the estimated pairwise genetic correlation between the 11 quality trait evaluated for each growing season. (DOCX 22 kb)Additional file 3:Table S3. Phenotypic values  for 11 quality traits measured in 132 maize inbred lines. In Table S3 one can find for the 11 quality trait evaluated the summary statistics on phenotypic data for each growing season and across growing seasons. (DOCX 24 kb)Additional file 4:Table S4. Observed inflation factors for the models tested in genome-wide association (GWAS) analysis. In Table S4 one can find the inflation factors for each of the three different models that were tested to detect significant marker-trait associations: the naïve model, a model accounting for population structure; and a model accounting for familiar relatedness. (DOCX 21 kb)Additional file 5:Table S5. Significant SNP-trait associations from a genome-wide association study for 11 quality traits in wholemeal maize flour. In Table S5 one can find the genome-wide association study results for the 11 quality trait evaluated based on the information combining the phenotypic data obtained in two growing seasons with the genotypic data obtained from the Illumina MaizeSNP50 BeadChip array using 132 maize inbred lines. Additionally, Table S5 also encloses information on the genomic regions associated to quality-related traits previously identified by other authors. (XLSX 22 kb)Additional file 6:Table S6. Percentage of associated SNPs with opposite effects on each traits value, and the range of phenotypic variance explained. In Additional file Additional file 7:Table S7. Candidate genes underlying the genomic regions associated with 11 quality traits in wholemeal maize flour. In Additional file Additional file 8:Table S8. Maize inbred lines with available quality data, known pedigree, kernel color, and endosperm type. In Additional file Additional file 9:Table S9. Number of maize inbred lines grouped accordingly to their kernel color and endosperm type. In Additional file


Alternative polyadenylation (APA) is emerging as an important layer of gene regulation because the majority of mammalian protein-coding genes contain multiple polyadenylation (pA) sites in their 3′ UTR. By alteration of 3′ UTR length, APA can considerably affect post-transcriptional gene regulation. Yet, our understanding of APA remains rudimentary. Novel single-cell RNA sequencing (scRNA-seq) techniques allow molecular characterization of different cell types to an unprecedented degree. Notably, the most popular scRNA-seq protocols specifically sequence the 3′ end of transcripts. Building on this property, we implemented a method for analysing patterns of APA regulation from such data. Analyzing multiple datasets from diverse tissues, we identified widespread modulation of APA in different cell types resulting in global 3′ UTR shortening/lengthening and enhanced cleavage at intronic pA sites. Our results provide a proof-of-concept demonstration that the huge volume of scRNA-seq data that accumulates in the public domain offers a unique resource for the exploration of APA based on a very broad collection of cell types and biological conditions. There are >10 weaker variants of this canonical PAS, the main one being AUUAAA  as a widespread regulatory layer that generates transcript isoforms with alternative 3′ ends (cis-elements that serve as major docking platforms for microRNAs (miRNAs) and RNA binding proteins (RBPs), which are involved in various aspects of mRNA metabolism, 3′ UTR APA can potentially affect post-transcriptional regulation in multiple ways, including the modulation of mRNA stability, translation efficiency, nuclear export and cellular localization  to avoid inhibition by miRNAs, thereby enhancing their tumorigenic activity  technologies allow the definition and molecular characterization of different cell types to an unprecedented degree, and their usage is growing at an exponential pace ,23. NotaA detailed description of the bioinformatics pipeline that we implemented for APA analysis based on 3′ tag scRNA-seq data is provided in Supplementary Methods.https://github.com/ElkonLab/scAPA.The code and sample input files for this pipeline are available at We used GENCODE  annotaticellranger count with default parameters (dedup procedure (FilterBAM (TAG_RETAIN = UB)  . We next utility . In eachfindPeaks (merge (intersect) with the 3′ UTR annotation files described above. A peak that intersected a 3′ UTR got an ID composed of the 3′ UTR’s ID and a sequential peak index, starting with the most proximal peak (5′-most location) (Peaks were identified using Homer indPeaks  (using ss (merge  to mergeocation) . Adjacenocation)  to identocation) . Specifiocation) . On a trOnce the genomic intervals of the peaks were determined, the number of reads that mapped to each peak in each cell-cluster BAM file was counted using the featureCounts function from the Rsubread package .First, in each dataset, after normalizing peak counts to units of counts per million (CPMs), we considered only peaks that had more than a total sum of 10 CPMs over all the cell clusters. Next, as the usage of oligo-dT primers by scRNA-seq protocols can yield reads that originate from priming internal A-rich regions within the transcript (rather than from the transcript's 3′ end poly(A) tail), to avoid false calls of pA sites we filtered out peaks with downstream A-rich sequences. Specifically, peaks having a genomic sequence of at least eight consecutive As in the region between 10 nt to 140 nt downstream of their 3′ edge were suspected to result from internal priming and were excluded from the analysis.closest, requiring the same strand (-s).Peaks were analysed for enriched motifs using DREME . The 3′ proximal PUI). For a given 3′ UTR, the proximal PUI is defined by:3′ UTRs that showed differential usage of pA sites between different cell types were detected using chi-squared tests, performed on peak counts and corrected for multiple comparisons using BH FDR correction. 3′ UTRs with a q-value below 0.05 were considered significant. To quantify the relative usage of the most proximal pA site within a 3′ UTR (with two or more peaks), we defined the proximal pA site usage index (We considered 3′ UTRs with exactly two peaks to identify events of 3′ UTR shortening (or lengthening).  For such 3′ UTRs, an increase in the value of the proximal PUI in cell type 1 relative to cell type 2 indicates 3′ UTR shortening in cell type 1. The global tendency for 3′ UTR shortening or lengthening in one cell cluster relative to another was tested using a one-tailed binomial test.For 3′ UTRs with more than two peaks that showed a significant differential usage of pA sites, the usage of each peak was tested separately (using chi-squared tests).All tests were performed in R-3.4.4 and plots were made using ggplot2 R package.intersect procedure to intersect the peaks’ bed file with a bed file of intronic regions downloaded from the UCSC table browser . Per intronic pA site and cell cluster, we calculated the intronic pA site usage index:Starting with the filtered 3′ UTR peaks count matrix, we summed the count of all peaks in each 3′ UTR to obtain a count matrix with UTR IDs as rows and cell clusters as columns. We then normalized this matrix by transforming counts to CPMs followed by quantile normalization.The 3′ tag-based scRNA-seq methods use oligo-dT primers, which anneal to the poly(A) tail of transcripts for ligating the cell barcode to the RNA molecules. Library preparation of these protocols generates short cDNA fragments  that contain the cell barcodes and the start of the poly(A) tail at one of their ends. Sequenced reads  are generated from the opposite end of the fragment Figure  in additin vivo murine T cells  and its main variant (AUUAAA), which together were detected in 79% of the peaks ) over the three stages demonstrated the gradual evolvement of the immense 3′ UTR shortening during the progression through the sperm cell maturation trajectory  in analogy to the proximal PUI defined above (Methods), where a higher value of this index reflects higher usage of the intronic site relative to the 3′ UTR sites. Cancer cells showed a significant increase in this index compared with the normal alveolar cells  of the 3′ UTR peaks identified . DetectiIn recent years, several bioinformatics tools were developed to infer APA modulation from bulk RNA-seq datasets, including DaPars   and ChanLast, while our analysis builds on single-cell data, given the limited coverage of individual cells , we did not perform single-cell-level analysis but rather pooled reads across all the cells that were assigned to the same cluster . Nevertheless, we sought to examine whether, despite limited coverage, current single-cell data can discern single-cell-level APA modulation. For this task, we calculated, per cell, the mean proximal PUI, where higher levels reflect elevated pA activity resulting in enhanced cleavage at proximal pA sites (and thus 3′ UTR shortening). Interestingly, in all the datasets, this analysis delineated the main APA patterns at the level of individual cells Figure .In this study, we provide a strong demonstration for the utility of scRNA-seq data generated by 3′ tag-based methods for the analysis of APA, despite it not being intentionally developed for the study of this regulatory layer. By analysing single-cell (SC) data, from T cells we detected the global 3′ UTR shortening that is associated with the proliferative state, and by analyzing SC data from spermatogenesis we delineated the drastic 3′ UTR shortening that accompanies this developmental trajectory. The analysis of SC data from the brain pinpointed neurons as the cell type that is characterized as having the greatest incidence of longer isoforms, whereas the analysis of a lung tumour showed global aberration of APA in cancer cells, manifested by enhanced cleavage at both proximal 3′ UTR and intronic pA sites.By comparison of different cell types or different biological conditions, analysis of 3′ tag-based transcriptomic data globally delineates changes in the relative expression of short versus long gene isoforms. Such changes can stem in principle from either differential activity of the APA machinery that alters the balance between usage of proximal and distal pA sites or from the differential activity of factors that regulate mRNA stability . Only experimental analysis can reveal the underlying causal mechanism . Furthermore, the observed changes probably reflect the combined effect of these two regulation modes. Accordingly, it was shown that in spermatogenesis, during the differentiation of spermatocytes into spermatids, the relative expression of the isoforms with shorter 3′ UTRs is drastically elevated compared with the longer ones due to both increased cleavage at proximal 3′ UTR pA sites and enhanced mRNA degradation of the longer isoforms that contain destabilizing elements ,47,59–61The functional impact of APA on gene expression is largely unknown. Since miRNAs mainly have a repressive effect on target genes, 3′ UTR shortening is expected to be generally associated with increased stability. In contrast to this expectation, recent studies observed that global 3′ UTR shortening in mouse fibroblasts and T cells is not accompanied by significant changes in mRNA or protein levels ,10. In oet al. analysed 3′ tag scRNA-seq data to explore the dynamics of APA in acute myeloid leukaemia (AML) and observed elevated APA modulation in AML patients compared with healthy controls (In the analysis of the lung cancer dataset, we observed that the cancer cells showed increased cleavage at both proximal 3′ UTR and intronic pA sites. These results are in line with a recent study that implicated premature cleavage and polyadenylation at intronic pA sites, indicating it as yet another process that is harnessed by cancer cells for selective proliferative advantage . It emercontrols .An inherent limitation of APA analysis using 3′ tag scRNA-seq data is the resolution of pA site detection. The characteristic width of the peaks hampers the separation between very close pA sites. Using pA site annotations from PolyA DB, we found that in the analysed datasets, while we robustly separated adjacent pA sites with distances above 300–400 nt, we were able to separate ∼30% of successive sites whose distance is 200–300 nt and only ∼5% of the sites whose distance is <200 nt .APA is still a largely unexplored layer of gene regulation. The study of APA was hampered for years by the lack of widely adopted transcriptomic techniques for quantification of pA usage that allowed systematic analysis of APA modulation. Our analyses demonstrate that the huge volume of 3′-tag scRNA-seq data that accumulates in the public domain fills this gap, and provides a unique resource for exploration of APA under a very broad collection of cell types and biological conditions. It thus holds great promise for improving our understanding of the roles of APA in normal physiological processes and the development of pathological conditions.gkz781_Supplemental_FileClick here for additional data file.


Whole genome bisulfite sequencing (WGBS) also known as BS-seq has been widely used to measure the methylation of whole genome at single-base resolution. One of the key steps in the assay is converting unmethylated cytosines into thymines (BS conversion). Incomplete conversion of unmethylated cytosines can introduce false positive methylation call. Developing a quick method to evaluate bisulfite conversion ratio (BCR) is benefit for both quality control and data analysis of WGBS.Here we provide a computational method named “BCREval” to estimate the unconverted rate (UCR) by using telomeric repetitive DNA as native spike-in control. We tested the method by using public WGBS data and found that it is very stable and most of BS conversion assays can achieve> 99.5% efficiency. The non-CpG DNA methylation at telomere fits a binomial model and may result from a random process with very low possibility (the ratio < 0.4%). And the comparison between BCREval and Bismark , a widely used BCR evaluator, suggests that our algorithm is much faster and more efficient than the latter.Our method is a simple but robust method to QC and speculates BCR for WGBS experiments to make sure it achieves acceptable level. It is faster and more efficient than current tools and can be easily integrated into presented WGBS pipelines. DNA methylation, as a fundamental epigenetics modification, plays critical roles in various biology processes including embryonic development, pluripotency maintenance, genomic imprinting, gene expression regulation, and genomic stability maintenance. It involves the addition of a methyl group to the carbon 5 position of CpG (most of tissues) and non-CpG dinucleotides  by DNA methyltransferases in a tissue-specific way. Knowledge of the genomic methylation landscape is essential for understanding how methylation patterns are established and maintained and the significance of DNA methylation in development and disease.Several methods exist for measuring DNA methylation in genomic wide including Whole genome bisulfite sequencing (WGBS), reduced representation bisulfite sequencing (RRBS), post-bisulfite adapter tagging (PBAT)  and Meth7. At other hand, prolonged bisulfite treatment causes DNA degradation in a way of remaining methylated reads. So it is important to estimate bisulfite conversion ratio (BCR) for each WGBS experiment.In a WGBS assay, it was implicitly assumed that this bisulfite conversion should run to completion. However, it is not always the case. Incomplete conversion of unmethylated cytosines will make it impossible to distinguish unconverted unmethylated cytosines from methylated ones and therefore will result in false positive methylation callsSome studies have used observed BCR in closed non-CpG sites to estimate BCR by assuming very low methylation ratio of non-CpG sites which may not be the case especially in some cell type (e.g. ES cell). Additionally, some (C/T) SNPs and low coverage regions may also introduce noise for the strategy. Another option to estimate BCR is using spike-in control of nonnative DNA with a known methylation state, which increases the complexity of procedure and rely on another assumption that DNA and spike DNA have the same conversion properties which is also questionable.Telomeres are distinctive structures found at the ends of chromosomes, which protect the ends of chromosomes from deterioration or fusion with neighboring chromosomes. In vertebrate telomeres, the sequence of TTAGGG is repeated strictly approximate 3000 times and can reach up to 15,000 base pairs in length. Its complementary DNA strand contains CCCTAA repeats which have three non-CpG sites (one CpT and two CpC sites) for each repeat. As there are a lot of non-CpG site exist in telomeres, using telomeric DNA as native spike-in control may be a better way to evaluate BCR.Here, we provide a computational method named “BCREval” to evaluate BCR using telomeric DNA as native spike-in control for WGBS experiment. We tested the method using 11 public available WGBS data of various cell lines and tissues and found that this method is easy to use and stable. In most of cases, the BCR of telomeric DNA is above 99.5% suggesting that telomeric DNA are unmethylated in all test samples and the DNA methylation at telomere fits a binomial model and may result from a random process with very low possibility. Interestedly, no significant differences of non-CpG methylation ratio was found in three non-CpG cytosine sites. Additionally, the comparison between BCREval and Bismark , a wideln > =8  are much more than ones from C strand (low GC contents) in both FASTQ files, which may result in the GC bias of PCR step  in both forward and reversed FASTQ files  of three non-CpG sites of telomeric reads were calculated for both forward and reversed FASTQ files. We found that UCRs from reversed FASTQs file frequently slightly higher than their count parts from forward FASTQs Fig. c. The poMethylated cytosines are found primarily at CpG dinucleotides, but are also found at non-CpG sites  in specific mammal cell types including pluripotent stem cells, oocytes, neurons, and glial cells . Using oBased on the random model, the expected number of R3 blocks should be zero for all samples  Bisulfite conversion assay is really stable and usually achieves > 99.5% efficiency; 2) In most cases, the cytosine methylation at telomeres is a random processes and the methylation rates of telomere usually are very small (< 0.4%); 3) No locational or sequence preferences are found in the three non-CpG sites; 4) Although it is impossible to distinguish random cytosine methylation from failure of bisulfite conversion in WGBS, our method have the potential to detect enzymatic DNA methylation by comparing the distribution of N1 and N2 blocks; 5) Our method has the ability to detect trace untreated genomic DNA contamination for QC purpose.More importantly, comparing with existing BCR evaluator Bismark , BCREvalAdditionally, because all mammals share the same telomere DNA sequence, this method should be applicable to nonhuman mammalian samples without any modifications. it is also easy to modify program for other species with distinct telomere repeats by following the same principle of our method.https://github.com/hqyone/BCR_Evaluator.BCREval is a simple but robust method to speculates BCR for WGBS experiments to make sure it achieves acceptable level. It is much faster and more efficient than existing tools and can be easily integrated into current WGBS pipelines. A python script to implement BCREval is freely available at All WGBS testing data (FASTQ files) were download form ENCODE database including 2 cell lines, 1 primary cell and 3 tissues (Table n-3′) and C-strand (5′(CCCTAA)n-3′); II. dsDNA are denatured and become ssDNAs; III. Bisulfite treatment converts unmethylated cytosines in the C strand into thymines; IV. The polymerase chain reaction (PCR) library construction to form dsDNA; V. Next generation pair-end sequencing and data analysis. As the patterns of c-strand origin telomeric reads in two FASTQ files are known, it is easy to calculate UCR by comparing them with theoretical bisulfite covered sequences  into four categories based on the number of unconverted cytosines (we named them as N0~N3 blocks). We considered the unconverted events as Bernoulli trials with certain possibility (UCR). So the percentage of N0~N3 telomeric blocks (R1~R3) should fit a binomial model and following formulas:As R1, R2 and R3 can be observed, it is easy to speculate UCR theoretically using these formulas. Actually, we only used the formula https://github.com/FelixKrueger/Bismark) and run following its manual with default settings. For each FSATQ file, 12 million reads are randomly extracted to save testing time.All algorithm testing and comparisons were run at a DELL PowerEdge R730 server, with 128G RAM and two Xeon E5–2600 v3 processors with 18 cores. Bismark was downloaded from here 7 repeats in hg38 genome. Table S1. Detailed analysis results.


Pseudomonas, a typically aerobic taxa which is ubiquitous in coal seam microbial communities worldwide and which has been shown to be abundant at early time points in studies of ecological succession on coal. The current study performed aerobic isolations of coal seam microbial taxa generating ten facultative anaerobic isolates from three coal seam formation waters across eastern Australia. Subsequent genomic sequencing and phenotypic analysis revealed a range of ecological strategies and roles for these facultative anaerobes in biomass recycling, suggesting that this group of organisms is involved in the degradation of accumulated biomass in coal seams, funnelling nutrients back into the microbial communities degrading coal to methane.Microbes in subsurface coal seams are responsible for the conversion of the organic matter in coal to methane, resulting in vast reserves of coal seam gas. This process is important from both environmental and economic perspectives as coal seam gas is rapidly becoming a popular fuel source worldwide and is a less carbon intensive fuel than coal. Despite the importance of this process, little is known about the roles of individual bacterial taxa in the microbial communities carrying out this process. Of particular interest is the role of members of the genus  As a cleaner alternative, methane derived from coal, known as coal seam gas (CSG) or coal bed methane has become an increasingly important ‘bridge’ fuel for a global transition to renewables. With the discovery that significant portions of the worlds CSG are produced through microbial degradation of the organic matter in coal to methane, has come an increasing interest in understanding the microbial communities involved in this process, with the aim of stimulating CSG production from coal reserves4.Globally, coal represents a key fuel, accounting for almost ~25% of the world’s energy consumption . The use of coal for power generation, however, is associated with significant environmental and health impactsin situ on or in laboratory grown microcosms . These studies have typically used 16S rRNA gene based community profiling. This approach has been informative in characterising the members of coal-associated microbial communities, including which taxa appear to be ubiquitous in coal systems and those which appear to be dependent upon local conditions such as coal rank, depth and temperature. This type of research has enabled some generalisations to be made about the composition of these communities: all contain ubiquitous methanogenic archaea, a small number of very abundant bacterial taxa from the Proteobactera or Actinobacteria; and less frequently Firmicutes, and a long tail of rare organisms from a range of phyla6.Efforts to understand the process of biological coal degradation have focussed primarily on either (1) understanding what nutrients to add to stimulate microbial communities to degrade organic matter in coal to methane, and/or; (2) characterising the microbial community compositions on coal and associated formation waters either 8), it is considerably less reliable in the majority of bacterial groups where metabolic functions are not always taxonomically conserved. In order to address this, some effort to assign functions to coal seam microbes has been attempted through genome reconstructions from metagenomic sequences11. This approach has generated some insights into the metabolisms of members of these environments, notably the discovery of a novel methanogenic taxon10, however, as many genes in the process are unknown the effectiveness of this method is limited. Finally, classical isolation into either axenic or gnotobiotic culture can be used to elucidate the metabolic roles of individual organisms. Unlike metagenomics-based approaches, isolation has the advantage of being able to experimentally test the metabolic and physiological characteristics of the isolated taxa through growth studies, though a key drawback remains that many microbial species are recalcitrant to isolation.One key limitation of this approach is that assigned functions of any these uncultured organisms are obtained from related, cultured taxa. While this is useful for some groups such as the methanogenic archaea, where metabolic capabilities are largely constrained  observed in this 16S rRNA amplicon sequence based study was taxonomically identified as a pseudomonad (OTU_9), and its presence during early colonisation suggested it may play some role in degrading organic matter in coal. Interestingly, Pseudomonas species have been previously identified from almost all surveys of coal seams conducted to date25 and pseudomonads isolated from coals in the past have been reported for the production of biosurfactants26 and lignin degradation phenotypes27. Additionally, a previous study has noted the prevalence of seemingly aerobic taxa and metabolisms in deep anoxic hydrocarbon environments28. In order to try to assign functions to these coal-associated pseudomonads, and functionally related facultative aerobic taxa, a culturing effort was undertaken to bring facultatively aerobic organisms, including that corresponding to OTU_9, into axenic culture. This isolation was followed by genomic and phenotypic characterisation to uncover the metabolic and ecological roles played by these organisms in coal seams. As these organisms are facultative aerobes, the present study employed oxic conditions and a complex medium to obtain axenic cultures.In 2016, Vick Ten bacterial isolates were obtained from three coal enrichment cultures derived from coal seam formation waters from the Sydney, Bowen and Surat coal basins of eastern Australia. The isolates all grew under oxic and anoxic conditions on either NA (Nutrient agar) or TSA (tryptone soy agar). Cellular and colony morphology were characterised for aerobically grown cells on rich complex media (NA and TSA) and are summarised in Fig. Chelatococcus sp. BOW-1 is closely related to Chelatacoccus caeni, first isolated from a sludge biofilm wastewater reactor29. Both Citrobacter sp. BOW-7 and Citrobacter sp. SUR-1 isolates had highly similar 16S rRNA sequences and shared Citrobacter amalonaticus as their closest relative in the phylogenetic tree. Pseudomonas BOW-2 and Pseudomonas SYD-2 clustered within different species clades within the genus Pseudomonas tree. Bow-2 clustered within the P. stutzeri species clade, whereas SYD-2 clustered with a clade containing P. linyingensis and P. sagittaria. Actinotalea sp. SUR-A1, isolated from the Surat coal basin, showed the closest relationship to A. fermentans, a cellulolytic organism isolated from a municiple waste dumping site30. Marinobacter sp. SUR-4 sits in a clade shared by close taxonomic relatives M. alkaliphilus and M. shengliensis, isolated from alkaline sub-seafloor mud and oil contaminated soil, respectively32. Vibrio sp. SUR-5 has a very similar 16S rRNA sequence to V. cincinnatiensis and clusters closely to it in the Vibrio genus tree. Tessaracoccus sp. SUR-6 clusters within a clade containing T. profundi and T. oleiagri, previously isolated from the deep terrestrial subsurface33 and oil contaminated soil, respectively34. Thauera sp. SYD-3, isolated from formation waters sourced from the Sydney coal basin, does not cluster closely with any named species of Thauera but has very similar or identical 16S rRNA gene sequences to several unnamed environmental sequences from diverse industrial wastewater sources  datasetTessaracoccus SUR-6 and Pseudomonas SYD-2, showed no observable growth or respiration in Biolog media under the conditions required for the assays, and were therefore not able to be assessed for carbon utilisation profiles. Other isolates grew on a range of different carbon substrates with the exception of Actinotalea sp. SUR-A1, which only showed growth on the carbolic acids: acetic acid and acetoacetic acid  and Actinotalea SUR-A1 encoded genes for the respiratory nitrate reductase (NarG) indicating that they are capable of using nitrate as a terminal electron acceptor also. Actinotalea SUR-A1 was also predicted to be able to use sulphate as a terminal electron acceptor. IMG/ER annotation also revealed that Pseudomonas BOW-2 was the sole isolate to carry the genes necessary for nitrogen fixation.In order to better understand the lifestyles and metabolic strategies of the bacterial taxa isolated in the current study from coal seam formation waters, the genomes were examined for genes and genetic elements relevant to ecological lifestyle. Isolates were all isolated under oxic conditions indicating they are capable of using oxygen as a terminal electron acceptor and the requisite metabolic pathways/enzymes for this are observed in each genome. The genomes of both Actinotalea SUR-A1, Vibrio SUR-5 and Tessaracoccus SUR-6 showed a high number of genes in the benzoate catabolism category, a central intermediate in several aromatic degradation pathways. This included three complete pathways and two pathways missing only a single gene component. Additionally, Marinobacter SUR-4 and Thauera SYD-3 contained complete catabolism pathways for benzene and toluene, while Pseudomonas SYD-2 contained complete pathways for benzene only. Interestingly, all benzene catabolism pathways observed appeared to proceed through the intermediate catechol, indicative of aerobic catabolism rather than benzoyl-CoA which is indicative of anaerobic catabolism  to determine the presence of aromatic hydrocarbon degradation genes and pathways. All isolates except 35. Genes which matched carbohydrate-active enzymes were then analysed with signalP to determine if the enzymes were likely excreted or transferred to the outer cell surface36. A number of carbohydrate-active enzyme genes were identified in all of the isolate genomes  and glycosyl transferase (GT) genes, and Chelatococcus BOW-1, Tessaracoccus SUR-6, Citrobacter BOW-7 and Citrobacter SUR-1 in the second, which had higher numbers of GH and GT genes. Outside of these two clusters Vibrio SUR-5 and Actinotalea SUR-A1 were outliers, having markedly different carbohydrate-active enzyme gene profiles , GH and S-layer homology domain (SLH) genes with accompanying signal peptide sequences, suggesting that this isolate can form a cellulosome. Vibrio SUR-5 also appeared to have a high number of GH and CBM genes, however it lacked the SLH genes characteristic of cellulosomes and a lower number of its genes contained signal peptides  were outliers having quite different profiles  family of transporters, involved in dicarboxylate uptake, and a larger number of ABC transporters involved in the uptake of amino acids, sulphate and polyamines. Differences in the Citrobacter transporter profiles appear to be driven by increased numbers of sugar transporters in the SSPTS (Sugar Specific Phosphotransferase System), GPH (Glycoside-pentoside-hexuronide) and ABC transporter families, and amino acid transporters in the HAAAP (Hydroxy/Aromatic Amino Acid Permease) and APC (amino acid-polyamine-organocation) transporter families , homoserine lactones (hserlactone) commonly used for quorum sensing, bacteriocins involved in competitive bacteriocidal interactions, ectoine used as a compatible solute and siderophores used for iron scavenging  identified CRISPR sequences in six of the isolate genomes while four didn’t appear to have any CRISPR elements  were investigated to assess horizontal gene transfer and viral predation on the bacterial isolates. Analysis using the ISsaga tool identified numerous insertion sequence elements in all isolate genomes with Pseudomonas represents a ubiquitous bacterial genus observed in almost all surveyed coal seam microbial communities. Despite this, the ecological and metabolic roles played by these pseudomonads and related facultatively aerobic taxa in coal seams remains poorly understood. The current study aimed to isolate representatives of these pseudomonads from multiple coal seam environments and to characterise their capabilities both genomically and phenotypically, in order to better understand their roles in this environment. Aerobic isolation from three coal seam formation waters on peptide rich media successfully generated two pseudomonad isolates from different species clades. This isolation effort also resulted in the generation of eight additional bacterial isolates from the actinobacterial genera Tessaracoccus and Actinotalea and the proteobacterial genera Thauera, Marinobacter, Chelatococcus, Citrobacter and Vibrio. As a phylogenetically diverse range of bacterial isolates were obtained it was decided to pursue genomic and phenotypic characterisation of all bacterial isolates to investigate putative ecological functions for this set of facultatively anaerobic, heterotrophic bacteria. The cellular morphology of all isolates was examined through scanning electron microscopy, carbon metabolisms characterised through Biolog phenotype screening and genomes sequenced and annotated to examine ecophysiologically relevant genes and genetic elements.42. These lifestyle classifications and the catabolisms and phenotypes associated with them are, in microbial systems, dependent upon the type of environment and how the energy and nutrient resources are introduced into the environment43. The coal seam constitutes an endogenous heterotrophic environment in that it is a closed system without regular microbial, nutrient or energy inputs from external sources43. In this type of environment initial colonising ruderal species are heterotrophic organisms which modify the physicochemistry of the environment through their metabolic processes until the environment is modified to a point where slower growing, stress tolerating organisms or those with specialised metabolic capabilities are able to compete and proliferate43.The roles of microbes in coal seam microbial communities are typically thought of in terms of their carbon catabolism, where the organic components of coal are sequentially degraded to methane in a linear fashion by a succession of microbial species. The ecological functions in a microbial community, however, are more complex and include a range of community functions including primary and secondary degradation, predation, scavenging and biomass recycling, amongst others. In fields of macro-ecology these ecological roles are often interrogated in terms of life strategy categories such as the competitive, stress tolerant and ruderal (CSR) classification used to classify the ecological strategies of plants during successionCitrobacter SUR-1, Citrobacter BOW-7 and Pseudomonas BOW-2, characterised by rapid growth on common, labile biomolecules with few genes associated with specialised metabolisms. The second life strategy appeared to be an opportunotrophic lifestyle as described by Singer et al.44. This was characterised by genes associated with diverse metabolisms suitable for survival across a wide range of different environments and was observed in Thauera SYD-3, Marinobacter SUR-4 and Pseudomonas SYD-2. The third life strategy group represents the specialists. This group is broader in function and includes different specialist strategies but shares the common trait of having narrower metabolisms with a greater genomic investment in a targeted catabolic process. Isolates which could be considered to have specialist life strategies include Chelatococcus BOW-1 and Actinotalea SUR-A1. In addition to isolates that had characteristics aligning with known ecological strategies, two isolates (Tessaracoccus SUR-6 and Vibrio SUR-5) had life strategies that did not appear to conform to known models based on the genotypic and phenotypic characterisation performed here  have been observed in a previous study of succession in coal seams45. In this previous study these opportunotrophic organisms remained at low abundances during the succession process45. These were also the only isolates to have considerable numbers of genes involved in aromatic hydrocarbon degradation  did not appear to conform to any clear life strategy models based on the genotypic and phenotypic characterisations performed in the current study. It may be that these organisms are also involved in biomass recycling albeit on a smaller range of cellular biomolecules than the other scavenger and opportunotroph organisms. Alternatively, it may be that these organisms are involved in novel or unexamined catabolic niche processes in coal or other subsurface waters.A small number of isolates from the current study  and 40 °C (Surat) for several months prior to use as an inoculum. Chemical analysis of formation water was performed by the ALS Environmental .Formation water for enrichment cultures was sampled anoxically from the wellhead of CSG wells in the Bowen Basin , Sydney Basin  and Surat Basin . 250 mg/L of Na4Cl, 400 mg/L K2HPO4.2H2O added to increase growth rates. Gamma sterile (8 kGY) crushed coal (<1 mm) collected from the same coal basins as the corresponding formation waters was used as the sole carbon source. An anoxic headspace consisting of 95% Argon: 5% H2 was used in the butyl rubber stoppered vials and these enrichment cultures were incubated for several months at temperatures matching those measured in the produced formation waters (40 °C for the Bowen and Sydney Basin and 30 °C for the Surat Basin).Actively methanogenic enrichment cultures were generated from these Bowen, Sydney and Surat Basin formation waters. To mimic the coal seam environment as closely as possible sampled waters were used as a culture medium with 25 mg/L NHIn order to isolate facultative aerobic taxa, 50 µL of enrichment culture was plated onto multiple nutrient agar (NA)  plates which were then incubated under oxic conditions at temperatures matching those of the corresponding enrichment cultures until colonies were apparent. Colonies were then picked based on morphological differences and streaked multiple times on NA and tryptone soy agar (TSA)  plates to produce axenic cultures. Isolates were screened to identify novel isolates by colony PCR amplification of the 16 S rRNA gene using Bioline MyTaq following the manufacturer’s instructions. Amplicons were purified (QiaQuick PCR purification kit) and sequenced by the Ramaciotti Centre for Genomics in both the forward and reverse directions .To examine cell morphology isolates were grown in 10 ml of nutrient broth (same as for NA excluding agar) overnight at 40 °C for Bowen and Sydney basin isolates and 30 °C for Surat basin isolates with shaking (140 rpm) or until visible turbidity was observed. 200 µl of broth culture was then spotted onto poly-L-lysine  coated glass coverslips for 5 min. Broth culture was then removed and the coverslips incubated in 3% glutaraldehyde in 0.01 M phosphate buffer (pH 7.4) for 24 hours at room temperature before being washed three times, each for 10 min with 0.01 M phosphate buffer. The coverslips were then incubated for 10 min in each of 20%, 50%, 70%, 80% and 90% ethanol solutions, twice with 100% ethanol before final dehydration with a Leica EM CPD300 critical point dryer. Coverslips were mounted on metal stubs, coated with 20 nm of gold with an Emitech K550 gold sputter coater unit and imaged using a JEOL JSM-7100F field emission scanning electron microscope operating at 5 kV accelerating voltage.http://bioinformatics.csiro.au/blue) before de novo assembly with Velvet 1.2.1060. Assemblies were submitted to the Genomes Online Database (GOLD) (https://gold.jgi.doe.gov/) and annotated using the IMG-ER pipeline61. Genome assemblies are available under the project accession ID’s: Gp0191703 (Chelatococcus sp. BOW-1), Gp0191702 (Pseudomonas sp. BOW-2), Gp0191704 (Citrobacter sp. BOW-7), Gp0191706 , Gp0151178 (Citrobacter sp. SUR-1), Gp0191707 (Marinobacter sp. SUR-4), Gp0191708 (Vibrio sp. SUR-5), Gp0191709 (Tessaracoccus sp. SUR-6), Gp0191711 (Pseudomonas sp. SYD-2) and Gp0151176 (Thauera sp. SYD-3).Isolates were grown as for visualisation. Cells were pelleted by centrifugation and genomic DNA was isolated using either the Isolate II genomic DNA kit (Bioline), PowerSoil® DNA Isolation Kit (MO BIO Laboratories) or FastDNA® KIT . Library preparation and whole genome sequencing were performed at the Ramaciotti Centre for Genomics  using the Nextera XT sample preparation kit (Illumina) and an Illumina Miseq platform to generate 250 bp paired-end reads. Sequence reads were error corrected using Blue (https://github.com/PaulGreenfieldOz/WorkingDogs/tree/master/Kelpie). BLAST searches were conducted against the NCBI RNA reference sequence database to find closest relatives and percentage identity. 16S rRNA gene sequences for representative sequenced relatives of each of the isolates were obtained from GenBank. Phylogenetic trees were constructed from 16S rRNA gene sequences using the default settings at the Phylogeny.fr webserver (http://www.phylogeny.fr.)62. In brief, sequences were aligned with Muscle63, the alignment checked and corrected using Gblocks64, the tree structure calculated using PhyML65, prior to visualisation using TreeDyn66. Branch support for the 16S rRNA phylogenetic tree was carried out using the aLRT method to bootstrap analysis67.16S rRNA gene sequences were taken from IMG annotations of genomes or through the use of the bioinformatic tool Kelpie 6.In order to examine the biogeography of isolates, the V4 region of 16S rRNA gene sequences of isolates were matched to the Coal Seam MicroBiome (CSMB) OTU dataset, which represents a large set of environmental survey OTUs from studied coal seams worldwide69 and predicted protein sequences functionally annotated using: CRISPRFinder41, ISsaga40, TransportDB 2.037, dbCAN35, antiSMASH39, MEROPS38 and signalP 4.170.Genomes were annotated for predicted coding sequences using the PROKKA softwarein situ for the coal seams from which isolates were obtained: 40 °C for isolates BOW-1, BOW-2 and BOW-7, 30 °C for isolates SUR-A1, SUR-4, SUR-5, SUR-6 and Sur-1 and at 37 °C for isolates SYD-2 and SYD -3 with absorbance at 590 nm measured at 15 minute intervals for each well.Carbon utilisation capabilities of isolates were assayed with the Biolog microplate system . PM1 and PM2 (Phenotype Microplate) carbon source microplates were used according to the manufacturer’s instructions with either the gram negative or positive protocol depending on the gram stain of the isolate. Respiration was measured by colourimetric changes caused by the reduction of a tetrazolium redox indicator dye mix. The dye mixes used for the individual isolates were chosen according to manufacturer recommendations based on taxonomic affiliation and rates of growth of the isolates. Dye mix A was used for BOW-2, BOW-7, SUR-1 and SYD-3; dye mix H was used for BOW-1, SUR-A1, SUR-4, SUR-6 and SYD-3 and dye mix D was used for SUR-5. Inoculated Biolog microplates were incubated in the Omnilog automated incubator-reader for 36 hours at temperatures matching those found Supplementary material 1


Mixed germ cell tumors (GCT) with teratoma components can transform into somatic malignancies which can include histologies outside of traditional germ cell lineages. We describe a case of an 18-year-old man with a metastatic testicular GCT with both mature and immature teratoma components containing malignant transformation into multiple histologies including PNET in the primary testicular tumor and osteosarcoma in a separate pulmonary metastatic lesion. Management with targeted chemotherapy resulted in a durable remission. This is the first reported case that we know of a patient with primary PNET malignant transformation with subsequent metastatic transformation to osteosarcoma. Germ cell tumors (GCT) of the testis are the most common solid tumors diagnosed in males between the ages of 15 and 40 years .GCTs with malignant transformation into somatic histologies are rare, occurring in only 2.7–8.6% of all GCT cases . MalignaAn 18-year-old man with a past medical history significant for an osteochondroma of the right forearm presented with a three-month history of a slowly enlarging right testicle. At the time of his initial presentation, the testicle had reached 9–10 cm in diameter. The patient was asymptomatic aside from the enlarged testicle without any constitutional symptoms. Tumor markers, including alpha fetoprotein and beta human chorionic gonadotropin, were negative. Family history was significant for a maternal grandmother with uterine and colon cancer both diagnosed in her 60s, a paternal grandfather diagnosed with prostate cancer in his 60s, and a maternal great grandfather diagnosed with leukemia in his 30s.18F-FDG-PET (PET) imaging was obtained which revealed a 1 cm PET avid left lower lobe lung nodule with a standard uptake value (SUV) of 2.8. A multidisciplinary team discussed treatment and planned for surgical resection of the lung nodule following initiation of therapy. There was concern that the patient was progressing when the FDG-PET avid nodule was discovered, and there had been considerable delay in confirming the diagnosis. As such, it was decided to proceed with chemotherapy and explore the pathology of the nodule if the patient did not experience adequate treatment response. Given the unusual nature of his case and the presence of several family members with a history of cancer, the patient was offered TP53 genetic testing but declined.A unilateral orchiectomy was performed. Pathology was consistent with mature teratoma (90%) and PNET (10%). Chest and abdominal CT scan revealed multiple retroperitoneal lymph nodes matted into a mass. Retroperitoneal lymph node dissection (RPLND) was performed revealing mature and immature teratoma with 60–70% transformation to PNET. This positive lymph node spread prompted second opinion review of the pathology. Second opinion pathologic evaluation of the primary tumor revealed nonseminomatous mixed germ cell tumor composed of mature and immature teratoma , yolk sac tumor (3%), and embryonal carcinoma (2%). Due to the PNET component, Combination chemotherapy was initiated with an alternating regimen that included cycles of vincristine/doxorubicin/cyclophosphamide and ifosfamide/etoposide given in compressed two-week cycles. The patient tolerated chemotherapy well without any major toxicity aside from intermittent mild myelosuppression.Reevaluation of the PET avid lung nodule occurred prior to cycle 5 and showed persistent avidity with an SUV of 2.92. A wedge resection of the left lower lung lobe nodule was completed following cycle 9 of chemotherapy. Pathology of this nodule revealed mature teratoma (40%), osteosarcoma (30%), and adenocarcinoma (30%) components .2, cisplatin 360 mg/m2, ifosfamide 54 g/m2, etoposide 3 g/m2, and cyclophosphamide 6 g/m2. He received dexrazoxane for cardioprotection prior to each doxorubicin infusion for a total cumulative dose of 6 g/m2. The patient's end of therapy evaluation was negative for any evidence of disease, and he is alive with no evidence of disease after 18 months.Treatment was subsequently amended to an osteosarcoma-based treatment regimen that contained four cycles of cisplatin with doxorubicin again alternating with 3 cycles of ifosfamide and etoposide. Total cumulative dose included doxorubicin 600 mg/mWhile germ cell tumors are a common malignancy in young men, it is rare for them to develop somatic malignant transformation. Malignant transformation more commonly arises in mediastinal nonseminomatous germ cell tumors than in gonadal germ cell tumors . SarcomaBecause of the rarity of these tumors, prognostic factors and optimal management of germ cell tumors with somatic malignant transformation are poorly defined. Cisplatin-based chemotherapy regimens have good outcomes in nontransformed malignant germ cell tumors, with a cure rate of greater than 80% , 9. UnfoFurther research is needed to adequately define treatment paradigms for patients with germ cell tumors transformed into multiple somatic histologies. It has been suggested that treatment for patients with unresectable malignant transformations be tailored towards the specific transformed histology . We have


Membrane proteins are notoriously difficult to crystallise for use in X-ray crystallographic structural determination, or too complex for NMR structural studies. Circular dichroism (CD) is a fast and relatively easy spectroscopic technique to study protein conformational behaviour in solution. The advantage of synchrotron radiation circular dichroism (SRCD) measured with synchrotron beamlines compared to the CD from benchtop instruments is the extended spectral far-UV region that increases the accuracy of secondary structure estimations, in particular under high ionic strength conditions. Membrane proteins are often available in small quantities, and for this SRCD measured at the Diamond B23 beamline has successfully facilitated molecular recognition studies. This was done by probing the local tertiary structure of aromatic amino acid residues upon addition of chiral or non-chiral ligands using long pathlength cells (1–5 cm) of small volume capacity (70 μl–350 μl). In this chapter we describe the use of SRCD to qualitatively and quantitatively screen ligand binding interactions ; to distinguish between functionally similar drugs that exhibit different mechanisms of action towards membrane proteins (exemplified by FsrC); and to identify suitable detergent conditions to observe membrane protein-ligand interactions using stabilised proteins (exemplified by inositol transporters) as well as the stability of membrane proteins . The importance of the in solution characterisation of the conformational behaviour and ligand binding properties of proteins in both far- andnear-UV regions and the use of high-throughput CD (HT-CD) using 96- and 384-well multiplates to study the folding effects in various protein crystallisation buffers are also discussed. Circular Dichroism (Circular dichroism (CD))CDCircular dichroism (CD) and Synchrotron Radiation Circular dichroism (CD) (Synchrotron radiation circular dichroism (SRCD)) has been proven to be highly useful for studies of Ligand binding by soluble proteins, particularly as it is a relatively quick and easy spectroscopic measurement, requiring no extensive sample preparation, and it has the potential to be used in high throughput (HT-CD)Ligand bindingSynchrotron radiation circular dichroism (SRCD) screening Mason .Circular dichroism (CD) spectroscopy has been widely used for the purposes of determining secondary structural content and integrity of membrane proteins  spectroscopy for Ligand binding studies of membrane proteins has proved more limited, largely due to the technical challenges associated with working with hydrophobic membrane proteins. The use of the B23 beamline (Diamond Light Source synchrotron) for Synchrotron radiation circular dichroism (SRCD) has overcome the limitations encountered in studying precious membrane proteins often available in very small quantities. The B23 beamline has enabled the use of small volume capacity cuvette cells for the measurements in the Far-UV and Near-UV spectral regions that could not otherwise be used with bench-top Circular dichroism (CD) instruments. The UV protein denaturation assay, a unique feature of the B23 beamline, is another method developed to assess Ligand binding interactions, in particular for achiral fatty acid ligand analogues or small organic molecules devoid of UV chromophores, which are difficult, if not impossible to investigate with bench-top Circular dichroism (CD) instruments. The higher vacuum UV and Far-UV photon flux has proved essential for the spectroscopic characterisation of membrane proteins in high salt concentrations to enhance protein stability, which cannot be achieved satisfactorily with bench-top instruments due to absorption cut-off.In this chapter, several examples of Synchrotron radiation circular dichroism (SRCD) spectroscopy applied to the study of membrane proteins in solution using the Diamond B23 beamline  beamlines around the world, has been developed to accommodate a horizontal X-Y motorised stage that can hold either the temperature controlled stage (such as Linkam™ stage), which can operate in cryogenic and high temperature conditions (from −150 °C to 300 °C), or standard microtiter or microwell plates Radiation circular dichroism. The beamline consists of two distinct end-stations: module A in operation since 2011 and module B in operation since 2009, see Fig. Module B is dedicated to Ligand binding interactions that are often carried out as Circular dichroism (CD) titrations using small aperture cuvette cells that require the ability to optimise beam alignment in a fast and reproducible manner using a manual X-Y stage )Isothermal Calorimetry (ITC), Surface Plasmon Resonance (SPR), Fluorescence and Circular Dichroism (Circular dichroism (CD))Circular dichroism (CD). Each technique has its own strengths and weaknesses. ITC can often be inconclusive when the thermal effects associated with the displacement of the bound solvent molecules by the ligand are rather small. SPR requires one of the components to be immobilized, which can lead to false positive or false negative results when compared to non-immobilized conditions. Fluorescence requires the presence of a fluorophore that does not absorb and emit light at the same wavelength for the ligand and/or protein (Tryptophan and Tyrosine residues). Circular dichroism (CD) relies on detectable spectral differences between the observed spectrum of the protein-ligand mixture at (x:y) molar ratio and the calculated sum of the spectra of the protein at (x) molar ratio and ligand at (y) molar ratio. For achiral ligands, the comparison is facilitated by the fact that the ligand chromophore will acquire an induced Circular dichroism (CD) upon binding of a protein site that is chiral. In this case, the detection of any induced Circular dichroism (CD), which is any spectral difference from that of the protein alone, is unambiguously indicative of the presence of a bound species, as the free achiral form is devoid of any Circular dichroism (CD) from its UV absorbing chromophore (Siligardi and Hussain Binding studies using the Circular dichroism (CD) titration method are even more challenging for membrane proteins than they are for soluble proteins. A common limitation encountered with membrane proteins is that they are often expressed in rather small quantities. At the B23 beamline, the highly collimated incident micro-beam (0.3 × 0.5 mm) is enabling the use of a small aperture cuvette cells of low volume capacity (from few μl to 25 μl for 0.01 cm to 1 cm pathlengths) to measure the Synchrotron radiation circular dichroism (SRCD) of precious and scarce membrane proteins.FsrC, a membrane protein histidine kinase, showed very little conformational changes in secondary structure upon addition of ligand Gelatinase Biosynthesis-Activating Pheromone (GBAP). However, the local tertiary structure of FsrC showed significant changes when GBAP was added, indicating the involvement of aromatic residues binding to GBAP, see Fig. Sinorhizobium meliloti bacteroids within plant cells and favours chronic infections with Brucella abortus and Mycobacterium tuberculosis in mice. A Synchrotron radiation circular dichroism (SRCD) spectroscopic study provided evidence that SbmA and BacA interact in vitro with Bac7 (1–35), a proline rich peptide. Bac7 was titrated at various molar ratios to SbmA and BacA in both the Far-UV (180–260 nm) and Near-UV (250–330 nm) regions. In the Far-UV region, significant changes of secondary structure were observed upon addition of Bac7 to SbmA  units from millidegree units and the plot of ΔA intensities at 223 nm versus the concentrations of Bac7 used in the titration was analysed with a non-linear regression method  oligomers. A SbmA homolog, BacA, is required for the development of see Fig.  and BacAsee Fig.  indicatisee Fig. , charactsee Fig.  no signid) of 6 μM , no significant conformational changes in the Far-UV region (180–250 nm) were observed in the presence of an achiral chlorhexidine antibacterial drug  of SbmA and the melting temperature of a mixture of SbmA and Bac7  by Synchrotron radiation circular dichroism (SRCD) is the case of the membrane protein GDP-mannose-dependent mannosyltransferase WbdD. In this example, the accurate determination of the α-Alpha helical content of the protein was crucial as a molecular ruler to regulate O-antigen chain length in lipopolysaccharide of WbdD is a membrane-associated protein and its interaction with WbdA (another GDP-mannose-dependent mannosyltransferase) is essential for the ability of the soluble polymerase to act on the membrane-embedded undecaprenyl lipid–linked acceptor  of the B23 has recently been exploited for the use of 96- or 384-well plates, to allow for high throughput Circular dichroism (CD) (HT-CD)  spectroscopy for such characterisations would be rather laborious and time consuming as this would normally be carried out by measuring the samples in a single cuvette cell, one by one. The unique highly collimated incident micro-beam (from 0.3 mmCD) Fig.  screeninCD) Fig. . Fig. 4.Myoglobin, a highly α-Alpha helical protein, was investigated by Synchrotron radiation circular dichroism (SRCD) spectroscopy dissolved in a selection of 48 conditions from the MemGold2 crystallisation screen (Molecular Dimensions) that is widely used for membrane protein crystallization. The corresponding 48 Synchrotron radiation circular dichroism (SRCD) spectra Fig.  showed sMost membrane proteins are highly helical and it is not inconceivable that they too might behave similarly to myoglobin under various buffer conditions. This is consistent with the fact that membrane proteins only crystallise in certain buffer conditions Privé  but not The availability of HT-CD facility at the B23 beamline opens up the possibility of finding cross-correlations between buffer conditions and protein conformation, identifying possible buffer targets that could promote crystallisation for further 3D structural determination by X-ray crystallography.The work described in this chapter highlights the use of Circular dichroism (CD) and Synchrotron radiation circular dichroism (SRCD) spectroscopy for studies of membrane proteins, particularly when a wide spectral range from Far-UV to Near-UV region (180–350 nm) is achieved for both protein and ligand. This approach enables the determination of the stability and content of the Protein Secondary Structure, the qualitative and quantitative assessment of Ligand binding interactions and the characterisation of the solvent (Detergents) conditions to optimise protein stability and binding properties. It has been successful in the identification of drugs that despite similar activity revealed different thermodynamics properties when bound to various protein constructs.The amide bond of the protein backbone structure gives information about the Protein Secondary Structure while the aromatic side-chains of the tryptophan, tyrosine and phenylalanine amino acid residues provide details about their local tertiary structure, as such, these are ideal as molecular probes for Ligand binding interactions. The chromophore of the ligand can be used to unambiguously determine Ligand binding in both far- and Near-UV regions and in particular whether protein conformational changes are occurring upon Ligand binding. Further development in high throughput allows the screening of crystallization buffers and the potential screening of ligands in drug discovery with membrane proteins acting as host or target receptor. This broad approach of Circular dichroism (CD) spectroscopy in solution for membrane proteins is advantageous. Synchrotron radiation circular dichroism (SRCD) in particular provides wavelength extension in the vacuum UV region and higher photon flux, which enables more penetrating measurements with less transparent media (NaCl content up to 500 mM) and in small volume capacity cuvette cells that are unattainable using bench-top Circular dichroism (CD) instruments.