Clinical laboratory reference values from North American and European populations are currently used in most Africans countries due to the absence of locally derived reference ranges, despite previous studies reporting significant differences between populations. Our aim was to define reference ranges for both genders in 18 to 24 year-old Mozambicans in preparation for clinical vaccine trials.A cross-sectional study including 257 volunteers  between 18 and 24 years was performedat a youth clinic in Maputo, Mozambique. All volunteers were clinically healthy and human immunodeficiency virus, Hepatitis B virus and syphilis negative.Median and 95% reference ranges were calculated for immunological, hematological and chemistry parameters. Ranges were compared with those reported based on populations in other African countries and the US. The impact of applying US NIH Division of AIDS (DAIDS) toxicity tables was assessed.+ T cell values 713 cells/µL in males versus 824 cells/µL in females (p<0.0001). Hematologic values differed from the US values but were similar to reports of populations in western Kenya and Uganda. The lower and upper limits of the ranges for hemoglobin, hematocrit, red blood cells, white blood cells and lymphocytes were somewhat lower than those from these African countries. The chemistry values were comparable to US values, with few exceptions. The upper limits for ALT, AST, bilirubin, cholesterol and triglycerides were higher than those from the US. DAIDStables for adverse events predicted 297 adverse events and 159 (62%) of the volunteers would have been excluded.The immunology ranges were comparable to those reported for the US and western Kenya.There were significant gender differences in CD4This study is the first to determine normal laboratory parameters in Mozambique. Our results underscore the necessity of establishing region-specific clinical reference ranges for proper patient management and safe conduct of clinical trials. The number of clinical trials related to HIV/AIDS, tuberculosis and malaria conducted in Africa is increasing sharply and is expected to increase further in the coming years Laboratory reference intervals for healthy populations have not been established in most African countries. Common practice in these countries, including Mozambique, is to use reference ranges derived from populations living in Europe or the United States (US). Studies have shown differences between clinical reference ranges in African populations compared to those established in industrialized countries The use of improper clinical reference ranges to assess participant eligibility and safety for clinical trials may lead to unnecessary exclusion of eligible participants, contribute to over-reporting of adverse events (AEs) Prior to execution of a phase I/II HIV vaccine trial (TaMoVac 01) in Mozambique, we performed a study to define the prevalence and incidence of HIV and other sexually transmitted viruses in Maputo in a population of young adults. This was also an opportunity to establish clinical reference values in 18 to 24 year-old Mozambicans.This study establishes reference ranges for immunological, hematological and chemistry parameters in healthy young adults in Mozambique. We determined gender differences and compared values established for Mozambican young adults with those previously reported for the same age group in other African countries and with established intervals from the US  This study was approved by the National Bioethics Committee for Health of Mozambique. Written informed consent was obtained from each participant prior to conducting any study procedures.The study took place at the SAAJ clinic (SAAJ: ‘Serviço Amigo de Adolescentes e Jovens’ or Adolescent and Youth Friendly Service) at the Department of Obstetrics and Gynecology, Maputo Central Hospital. The SAAJ clinic provides services (free of charge) for young people seeking counseling and treatment for any health problem, but with particular attention to reproductive health and control of sexually transmitted infections (STIs). A low prevalence of STIs and HIV and a high level of awareness has previously been reported in a study performed at the SAAJ clinic 2 and had a population of 1,094,315 in 2007 Maputo is the capital of Mozambique and is situated in a coastal area adjacent to the Indian Ocean, between the coordinates 25° 50′ and 26° 10′ S and 32° 30′ and 32° 40′ E A total of 257 healthy individuals between 18 and 24 years old were recruited from a cohort of youths participating in a study of the prevalence and incidence of sexually transmitted viruses at the SAAJ clinic, Maputo Central Hospital. Medical staff performed physical examinations and collected clinical histories. Volunteers who were febrile, pregnant, or seropositive for HIV, syphilis or hepatitis B surface antigens were excluded from the study.The national algorithm for HIV testing was used to diagnose HIV. HIV testing was performed using two immunochromatographic assays, the Determine HIV-1/2  followed by the UniGold HIV-1/2 . Syphilis testing was performed using SD Bioline Syphilis 3.0. Serum samples were tested for Hepatitis B virus (HBV) using the Hepatitis B Surface Antigen (HBsAg) ELISA Kit .A urine pregnancy test was administered to all females prior to collection of blood samples, using the QuickVue One-Step HCG Urine Test .Sample collection took place between August 2009 and September 2012. Most samples (70%) were collected between November 2009 and August 2010, but the inclusion period was extended to recruit additional males to the study. Blood was collected in 4 ml EDTA Vacutainer tubes in preparation for lymphocyte and hematological testing. Whole blood was collected in 10 ml serum Vacutainer tubes in preparation for testing chemical parameters and HBV status. Samples were collected in the morning between 8.00 AM and 12.00 noon, kept at room temperature and transferred to the laboratory of the National Institute of Heath in Maputo for analysis.FITC/CD8PE/CD45perCP/CD4APC or CD3 FITC/CD16+CD56 PE/CD45PerCP/CD19 APC MultiTest reagents  was mixed with 50 µl of whole blood and incubated in the dark at room temperature for 15 min. Red blood cells were then lysed by adding 450 µl of fluorescence-activated cell sorter lysing solution .The tubes were then incubated at room temperature for another 15 min. MultiSET software  was used to perform the analysis.Immunophenotyping was performed using a FACS Calibur flow cytometer . Samples were analyzed within 24 h of specimen collection. In brief, 20 µl of CD36] per liter.A complete blood count and differential was performed using the Sysmex KX-21N Hematology Analyzer  as recommended by the manufacturer. The samples were analyzed within 6 h of specimen collection. The machine automatically dilutes a whole-blood sample, lyses and counts the cells, and then gives a printout result. Seventeen parameters were analyzed; leukocytes (WBC), erythrocytes (RBC), platelets (PLT), lymphocytes (LYM), neutrophils (NEUT), hemoglobin concentration (Hb), hematocrit (HCT), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), red blood cell distribution width measured by standard deviation (RDW-SD), red blood cell distribution width measured by coefficient of variation (RDW-CV), platelet distribution width (PDW), mean platelet volume (MPV), platelet larger cell ratio (P-LCR) and the percentages of lymphocytes (LYM), neutrophils (NEUT), and the mixed population of monocytes, basophiles and eosinophils (MXD). The absolute cell counts were expressed as number of cells × [10Serum chemistry was performed using a Vitalab Selectra Junior  per the manufactureŕs instructions. Serum was separated within 4 h of collection and analyzed within 7 h of blood draw. Each sample was analyzed for creatinine, total bilirubin (T-Bil), albumin, aspartate aminotransferase (AST), alanine aminotransferase (ALT), glucose, urea, uric acid, amylase, HDL cholesterol, triglycerides and alkaline phosphatase (ALP).In addition to commercial controls run daily with each instrument, the laboratory routinely participates (3 times per year) in external quality assurance testing programs distributed by Thistle  for hematology and clinical chemistry, and the International Quality Assurance Program-QASI  for lymphocyte typing. In the case of internal control failure, testing was suspended.Clinical and laboratory personnel trained in GCP and GCLP, respectively, conducted the study according to ICH/GCP guidelines, employing standard operating procedures.Data was entered into Microsoft Office Excel 2007 and analyzed using R version 3.0.0 th- 97.5th percentiles) were established for immunology, hematology and chemistry values. The non-parametric Wilcoxon rank-sum test (Mann-Whitney U test) was used to test for differences by gender. For all analysis the significance was set at 0.05.Median and 95% reference ranges  Further outlier presence was checked using the plots of the resample of the mean minus the trimmed mean as explained by Chernick and Labudde We then compared values established for Mozambican young adults with those previously reported for the same age group in other African countries A total of 257 healthy volunteers aged 18 to 24 years were enrolled in this study. Of these, 102 (40.3%) were males and 155 (59.7%) were females. The target of >120 males was not reached because of the comparatively low attendance of males at the Youth Clinic from which volunteers were recruited. The full range of lymphocyte subsets, hematology and chemistry analytes was not run in all subjects, primarily due to insufficient access to reagents required to test some parameters.+ cells, percentage of CD4+ cells, percentage of CD8+ cells, and CD4:CD8 ratios. Reference ranges for the absolute number of CD4+ cells (p<0.0001) and percentage of CD4+ cells (p<0.0001), CD4:CD8 ratios (p = 0.0001) as well asCD3+ cells (p = 0.0420) were significantly higher in females than males; however, the percentage of CD8+ cells was significantly higher in males (p = 0.0038). There were no significant gender differences in CD45+cell counts , percentage of CD3+ and absolute CD8+ cell count. Gender comparisons were also performed for CD16+56+  and CD19+ cells (B-cells) despite the comparatively low number of male samples analyzed (n = 29). A statistically significant gender difference was seen in percentage of CD16+56+ cells (p = 0.0390). No significant gender difference was found with respect to absolute number of CD16+56+ cells or absolute number and percentage of CD19+ cells.+ and CD8+ T cells derived in the present study were more comparable to values reported from the population in western Kenya than in Uganda , with a few exceptions. The upper limits of the reference ranges for ALT, AST, bilirubin and cholesterol derived in the present study were somewhat higher than those from the US. The Maputo values were lower compared to western Kenya in the same age group . We alsoClinical laboratory reference ranges have not previously been established in Mozambique. In this study we established reference ranges using samples derived from healthy young adults aged 18–24 years who attended a youth clinic at Maputo Central Hospital.The number of males was disproportionate to the number of females (40.3% vs 59.7%), mainly because a lower proportion of males attended the SAAJ clinic. This affected the recruitment of males into the study, and the target of 120 subjects tested per analyte as recommended by CLSI + T cells and CD8+ T cell percentage, with females having higher values than males in each case. These findings are consistent with those reported for young adults in Kericho, Kenya + T cell counts than males Our immunophenotyping data showed significant gender differences between total lymphocyte counts, absolute T cell counts, absolute count of and percentage of CD4+56+ natural killer cells and absolute count of CD19+ B cells. Lower percentages of CD16+56+ natural killer cells were seen in females compared to males, while absolute CD19+ B cells were lower in males than females. These findings were in general comparable to those reported in two studies performed in Tanzanian adults, which reported significant gender differences in percentage of natural killer cells and both the absolute count and percentage of CD19+ B cells + B cells than females. These findings are consistent with a study of US adolescents (13–19 y) in which CD19+ B cells were reported to significantly decrease in males as age increased Due to insufficient access to reagents for natural killer cells and B cells determinations, only 34 males and 104 females were tested for these parameters. Although the number of participants was fewer than the 120 recommended by CLSI, a significant gender difference was seen for percentage of CD16In the present study, we found significant gender differences in red blood parameters , with males having higher values than females; these results are consistent with previous reports Most of the hematological values derived from this study were lower than those derived from the US population, which is consistent with studies of similar age groups conducted in western Kenya and Uganda Clinical chemistry reference ranges derived in the present study were comparable to those derived from the North American population, with a few exceptions. The upper limits of the reference ranges for ALT, AST, Bilirubin and cholesterol derived in this study were slightly higher than those from the US, which is consistent with results from Uganda The clinical reference ranges derived from US MGH have been used in most clinical research studies due to the absence of local ranges. A comparison between values derived from the present study and US MGH values The Division of AIDS (DAIDS) toxicity table for grading adverse events is used in many clinical trials but may not be appropriate for the young adults included in the present study. For example, the lower limit ranges of neutrophil (1200 cells/µl), Hb (7.7 d/L) and AST (13.7 U/L) would qualify as grade 1, 3 and 1 AEs, respectively. The upper limits for ALT (48.2 U/L) and T-Bilirubin (27.9 µmol/L or 1.63 mg/dl) would be qualified as a grade 1 AEs. This is consistent with results found in Uganda Several limitations are apparent in the design of the present study. Importantly, we did not screen for all medical conditions that might have influenced the laboratory findings. Participants with parasitic infections or with other subclinical conditions may have been included, which may have influenced the results. Secondly, the participants were recruited at a youth health center in Maputo and the findings may therefore not be generalizable to young adults in the rest of Mozambique or other African countries. Despite these limitations, the reference values established here are being used in ongoing HIV-vaccine trials in Maputo that recruit healthy volunteers from the cohort of young adults attending the Maputo Central Hospital Youth Clinic. Additionally, given that indigenous reference values have not been previously defined for any Mozambican population, the ranges defined in this study are suitable for use in assessment of young adults in a more generalized setting.In conclusion, this study is the first to assess clinical laboratory reference ranges in Mozambique. The hematological and biochemistry reference values from this African population differ from those derived from a North American population. This study also highlights the need for region-specific clinical reference ranges for patient management and clinical research.


Cannabis has the potential to affect agricultural practice by improving plant fitness and production yield. Furthermore, Cannabis presents an interesting model to explore plant-microbiome interactions as it produces numerous secondary metabolic compounds. Here we present the first description of the endorhiza-, rhizosphere-, and bulk soil-associated microbiome of five distinct Cannabis cultivars. Bacterial communities of the endorhiza showed significant cultivar-specificity. When controlling cultivar and soil type the microbial community structure was significantly different between plant cultivars, soil types, and between the endorhiza, rhizosphere and soil. The influence of soil type, plant cultivar and sample type differentiation on the microbial community structure provides support for a previously published two-tier selection model, whereby community composition across sample types is determined mainly by soil type, while community structure within endorhiza samples is determined mainly by host cultivar.Understanding microbial partnerships with the medicinally and economically important crop  Cannabis spp., little is known about its soil-based microbial associations Soil microbes play a major role in plant ecology by providing a variety of benefits such as nitrogen fixation, production of growth stimulants, improved water retention, and suppression of root diseases 2 concentration, and O2 levels Microbial composition in soil depends on complex interactions between the soil type, root zone location, and plant species terroir for crop plants, as has been shown recently for wines Rhizosphere bacteria not only colonize the rhizosphere and/or the rhizoplane soil, but can also colonize plant tissues. Bacteria that have colonized root tissue—more specifically known as the endorhiza Acidobacteria within the endosphere.A growing body of work has united the colonization of both the rhizosphere and plant tissues under the two-tier selection model, where soil type defines the composition of rhizosphere and root-inhabiting bacterial communities Cannabis in order to explore how soil microbiota and plant strain affect the endorhiza microbial community of this commercially important crop. We hypothesize that different cultivars maintain significantly different microbial communities, and that these differences diminish from endorhiza to rhizosphere to bulk soil.This study aims to characterize bacterial diversity in the root and soil systems of five strains of Cannabis spp. tested strains—Burmese, BooKoo Kush, and Sour Diesel. Soil physicochemical data was taken for all bulk soil samples in the first experiment, however there was minimal edaphic variation. The second experiment sought to understand the effect of strain with more significant edaphic variation, and was accomplished using two different strains—White Widow and Maui Wowie—and two different soil types. Four plants of the two strains were grown in the same soil, and then two plants of White Widow were grown in a completely distinct soil type. Triplicate samples were taken from each plant for both the rhizosphere and endorhiza, as well as for each of the two soil types.The data for this paper were collected in two experiments: First, an experiment to identify variation in the microbial communities, and second, an experiment designed to understand the nature and strength of cultivar-specificity. The first experiment was composed of bulk soil, rhizosphere, and endorhiza samples taken from nine plants of the three different Cannabis sativa, associated with a high tetrahydrocannabinol (THC) to cannabidiol (CBD) ratio. Bookoo Kush is a sativa-dominant hybrid cultivar of Cannabis sativa and Cannabis indica, associated with a moderately high THC to CBD ratio. Burmese is a balanced hybrid cultivar of both Cannabis sativa and Cannabis indica, associated with a moderate THC to CBD ratio. For the second experiment, we used Maui Wowie and White Widow cultivars. Maui Wowie is a cultivar of Cannabis sativa, associated with a high THC to CBD ratio. White Widow is a balanced hybrid cultivar of both Cannabis sativa and Cannabis indica, known to have a more moderate THC to CBD ratio.Different cultivars were used for each one of the experiments. For the first experiment, we used Sour Diesel, Bookoo Kush, and Burmese cultivars. Sour Diesel is a cultivar of Cannabis plants of three different strains  in Vista, California, in November, 2011, for a total of 27 samples. Therefore, the triplicate DNA extracts were acquired for endorhiza, rhizosphere and bulk-soil for each of the 3 Cannabis spp. strains, resulting in a single endorhiza, rhizosphere, and bulk soil sample for each plant. The plants were grown in locally composted soil. Eight weeks following the harvesting of the Cannabis flowering bud and foliage from each plant, a 50 g bulk soil sample was taken 10 cm from the stem of each of the nine plants at a depth of 20 cm, as well as a larger sample of soil for testing edaphic factors  from two locations in August, 2012: Vista and Orange County, California. Triplicate samples were taken from each of the six plants (18 samples) and surrounding rhizosphere (18 samples), as well as from each of the two bulk soils used in the different locations (6 samples), totaling 42 samples. In contrast to the first experiment, all samples were taken two weeks prior to harvest. Additionally, triplicate samples from the second experiment were taken from different roots on the same plant (pseudoreplicates). Cannabinoid data was taken from the buds of three White Widow plants and one Mauie Wowie plant (Table S1). All cannabinoid data was processed at Delta-9-Technologies, LLC . Otherwise, sampling procedure matched the first experiment.Endorhiza, rhizosphere, and bulk soil samples for the second experiment were taken from 6 organically-grown Cannabis in the first study (27 samples), and two different strains of Cannabis in the second study (42 samples), for a total of 69 samples. The V4 region of the 16S rRNA gene was amplified and sequenced using the primers specified in Caporaso et al. (2012) following the Earth Microbiome Project's standard pipeline (http://www.earthmicrobiome.org/emp-standard-protocols/) http://www.earthmicrobiome.org/emp-standard-protocols/). Each 25 µL PCR reaction contained 12 µL of MO BIO PCR Water (Certified DNA-Free), 10 µL of 5 Prime HotMasterMix (1x), 1 µL of Forward Primer , 1 µL Golay Barcode Tagged Reverse Primer , and 1 µL of template DNA. The conditions for PCR are as follows: 94°C for 3 minutes to denature the DNA, with 35 cycles at 94°C for 45 s, 50°C for 60 s, and 72°C for 90 s, with a final extension of 10 min at 72°C to ensure complete amplification. PCR was completed in triplicate and products were pooled. Each pool was then quantified using Invitrogen's PicoGreen and a plate reader. Once quantified, different volumes of each of the products were pooled into a single tube so an equal amount (ng) of DNA was in the pool, and cleaned using the UltraClean PCR Clean-Up Kit (MO BIO). After quantification, the molarity of the pool is determined and diluted down to 2 nM, denatured, and then diluted to a final concentration of 6.1 pM with a 30% PhiX spike for sequencing on the Illumina MiSeq. A 151 bp×12 bp×151 bp MiSeq run was performed using the custom sequencing primers and procedures described in the supplementary methods in Caporaso et al. (2012). All raw sequence data is available publicly We utilized Illumina 16S rRNA sequencing to analyze samples of the endorhiza, the rhizosphere, and the bulk soil of three different strains of de novo (i.e. open reference). Representative sequences were aligned to the Greengenes core set with PyNAST see vegan::bioenv) All sequence analysis was done using QIIME 1.7.0 Cannabis strains , and second, an experiment designed to understand the nature and strength of plant cultivar-specificity between two different strains (White Widow and Maui Wowie) in two different soil types (with significant differences in edaphic variables). Triplicate samples were taken from each plant for both the rhizosphere and endorhiza, as well as for each of the two soil types.Work for this study was accomplished in two experiments. First, we performed an experiment to identify variation in the microbial communities between roots and soil in three different 2 = 0.26, p = 0.001) and bulk soil  samples from the other categories, but rhizosphere samples were not significantly different . Weighted UniFrac distances yielded similar results with endorhiza  and bulk soil  samples demonstrating significant differences from other sample types, but no significant differences for rhizosphere  samples. Division of all communities via strain  or unweighted  analyses, however, division of endorhiza communities via strain was significant for both weighted  and unweighted  analyses. The abundance of Methylophilus explained a significant portion of this difference (FDR: p = 0.012), comprising 13% of the microbial community in the endorhiza of Bookoo Kush, 0.13% in Burmese and was absent in Diesel. Despite these significant differences, all endorhiza samples maintained a core community of Pseudomonas, Cellvibrio, Oxalobacteraceae, Xanthomonadaceae, Actinomycetales, and Sphingobacteriales. With the exception of the aerobic cellulytic bacterium Cellvibrio, all prevalent members of the core endorhiza community were well known endophytic bacteria In the first experiment, using unweighted UniFrac, beta-diversity comparisons of each individual sample type against all other sample types Fig. 1a 2 = 0.32, p = 0.001), among sample types , and strains . Cluster comparisons of each individual sample type against all other sample types  and rhizosphere  samples, but no significant differences for bulk soil  samples. Using weighted UniFrac, community beta diversity varied significantly by soil type , sample type , and strain . Cluster comparisons of each individual sample type against all other sample types  and rhizosphere  samples, with mixed results for bulk soil samples .In the second experiment, using unweighted UniFrac, community beta diversity was significantly different between soil types Fig. 2a 2 = 0.196, p = 0.001), sample type , and strain  were highly significant for all tests using unweighted UniFrac. Cluster comparisons of each individual sample type against all other sample types yielded significant results for endorhiza samples , and mixed results for rhizosphere  and bulk soil samples . Likewise, using weighted UniFrac, the division of all communities via soil type , sample type , and strain  was highly significant for all tests. Cluster comparisons of each individual sample type against all other sample types yielded significant results for endorhiza samples , and mixed results for rhizosphere  and bulk soil samples .Pooling the first and second experiments together, division of all communities via soil type Fig. 3a For individual OTUs, both unweighted (g-test) and weighted (ANOVA) analyses showed that soil type had the strongest influence over significant OTU differences Table 2.Acidobacteria and an increase of Proteobacteria and Actinobacteria relative to the rhizosphere and bulk soil (Acidobacteria from the order iii1-15 in endorhiza samples (Bonferroni-corrected ANOVA: p = 1.12e-7). Of the 51 OTUs significantly differentiating between sample types, the 17 OTUs which increased in abundance within the Cannabis endorhiza relative to rhizosphere were predominantly Proteobacteria, including several from the Rhizobiales order. Mean abundance of the 51 OTUs were highly correlated between bulk soil and rhizosphere samples (Pearson's rho: 0.92), versus a lower correlation between rhizosphere and Cannabis endorhiza (Pearson's rho: 0.63), and even lower between bulk soil and Cannabis endorhiza (Pearson's rho: 0.42).As suggested by the two-tier model ulk soil Fig. 4. Proteobacteria, notably Pseudomonadales, Burkholderiales, Sphingomonadales, and Rhizobiales. Apart from Proteobacteria, Bacteroidetes orders Sphingobacteriales and Flavobacteriales were also responsible for several significant OTU differences between Cannabis strains. Intriguingly, one of the significant OTUs between strains was the prevalence of Sphingomonas wittichii in the Maui Wowie strain, which in some contexts can metabolize phenazine-1-carboxylic acid and has been implicated in increased survival in soil environments.Significant OTU abundance differences between strains were composed mostly of differences in unweighted: t = −4.59, p<0.001 weighted: t = −11.82, p<0.001). Beta distances between rhizosphere and bulk soil communities were significantly lower than distances between bulk soil and endorhiza communities for both unweighted and weighted analyses . Beta distances between rhizosphere and endorhiza communities were not significantly different from distances between bulk soil and endorhiza communities for both unweighted and weighted analyses .Beta distCannabis strain and analyzing the core microbiome within each strain. As bulk soils are the putative source of microbes for the plant, endorhiza communities would be expected to share more OTUs with their own soil than with another. White Widow was grown in two different soils, and roots shared more OTUs with the soil they were grown in than with the different soil in which the different white widow plant was grown. The number of shared OTUs between endorhiza and their own soil  was significantly greater  than the number of shared OTUs between endorhiza and the other soil .Previously, a two-step process of root colonization, first fueled by rhizodeposition and followed by fine-tuning by host genotype has been posited r-stat: 0.863, p-value  = 0.001). However, due to higher THC composition and concentration in plants from one of the soil types, THC variables were also significantly correlated to the soil edaphic variables, and as such any association between microbiota and THC is very hard to disassociate from soil physicochemical variables.Each plant in the second experiment was tested for a variety of cannabinoids, including delta-9-tetrahydrocannibinol. Cannabinoid data associated with the plants was used in Mantel tests to understand the potential biochemical associations with community composition or structure; with significant differences between strains , followed by salinity , Carbon , water content , and pH . For the unweighted analysis, the relative importance of the edaphic factors remained the same, with Nitrogen as the most important , followed by salinity , Carbon , water content , and pH . Running a BEST analysis, the variance in community data is optimally explained by three edaphic factors; Nitrogen, Carbon, & Water (rho = 0.632).In both experiments, edaphic data associated with the plants was used in Mantel tests to understand the effect of edaphic factors on structuring bulk soil, rhizosphere, and  factors Table 2 chao1: µ = 4947; σ = 717) to rhizosphere samples , followed by a dramatic reduction in alpha diversity from rhizosphere to endorhiza . Although diversity was significantly higher in MB bulk soil  and rhizosphere  in comparison to OC bulk soil  and rhizosphere , diversity of MB endophytes  was not significantly different from that of the OC endosphere . Despite much shallower sequencing in the first experiment, the same pattern was recovered, with both species richness and chao1 diversity index highest in bulk soil , slightly lower in the rhizosphere , and lowest in the endorhiza . Observedchao1: µ = 916.1, σ = 161.7) in comparison to the endospheres grown in MB soil  and OC soil . Although this might be explained by decreased diversity in the MB soil from the first experiment (MB1), comparisons of diversity between rarified samples demonstrate MB1 bulk soil had intermediate diversity  relative to the MB bulk soil  and the OC bulk soil . This reduction in alpha diversity in the endosphere from the first experiment is consistent with the early stages of root decay following the harvesting of the plant.Curiously, when samples from both experiments were pooled and rarified to the level of the first experiment, alpha diversity of the endosphere from the first experiment was greatly reduced  versus 0.095%  in the endosphere of the second experiment.After analysis of the data from the first experiment yielded high abundances (greater than 10% of taxonomy assigned reads) of the known cellulytic bacterium Cannabis strain is the main determinant of PC1 (34.51%) for the weighted analysis of all samples in the second experiment, suggesting that convergent host genotype-dependent selection acts through controlling community structure (abundance) more than composition. PCoA results exhibit how all sample types form significantly differentiated clusters in weighted analyses but that only rhizosphere and endorhiza samples form significantly differentiated clusters in unweighted analyses, suggesting niche-filtering of microbes in rhizosphere and endorhiza samples from bulk soil. Furthermore, there were no significant segregating OTUs based on unweighted analysis between cultivars in endorhiza and rhizosphere samples in the second experiment, however there were 71 when abundance was accounted for. This differs greatly from the 657 OTUs that significantly differ between soil types in the same dataset. Testing of the two-step selection model with pairwise comparisons of shared OTUs between endorhiza and bulk soil samples also validated the hypothesis that a portion of the endophytic microbes are inherited and selected from the surrounding soil, showing significantly more OTU overlap between endorhiza and their own bulk soil compared to endorhiza and foreign bulk soil.Recent literature has suggested a two-step selection model for the endorhiza, where bulk-soil microbial communities are filtered by increased concentration of rhizodeposits, followed by convergent host genotype-dependent selection on endophytic communities Cannabis cultivars have important structuring effects on both rhizosphere and endorhiza samples, it may seem troubling that results from the first experiment do not suggest this for the rhizosphere samples. However, differences in Cellvibrio abundance between experiments show that root decay could have diminished the rhizosphere effect, thus diminishing this potential signal. Sampling for the first experiment was done post-harvest, when plant tissues were undergoing senescence and decay, while samples for the second experiment were taken from actively growing plants. Considering the extensive work demonstrating the importance of plant growth stage on the microbiota Given the results from the second experiment strongly suggesting that Although we have presented several highly significant findings supporting expectations of the two-step selection model, some expectations remain to be validated. Specifically, although the mean beta-diversity distances indicate that rhizosphere and endorhiza samples are closer than bulk soil and endorhiza samples, this difference was not significant and thus provides little evidence for the first differentiation step of the two-step selection model Cannabis microbiome should focus on elucidating the role of cultivar on rhizosphere, as well as what aspects of host genotype are producing the structure observed across Cannabis strains. Increased testing of cannabinoids and decoupling this variation from edaphic factors will improve our understanding of the importance of cannabinoid production in structuring endorhiza communities. Sampling a time series of endorhiza communities across several plants may help us to understand natural variation in the endorhiza during the reproductive cycles of Cannabis. Understanding this natural variation will help direct future mechanistic studies aimed at using microbial communities to increase plant fitness, suppress disease, or augment desired metabolite production.Future work with the Table S1THC-testing data.(DOCX)Click here for additional data file.


We evaluated mRNA expression levels of genes that encode TGF-β1; the TGF-β1 receptor; the collagen-modifying enzymes LOX, PLOD1, and PLOD2; and the extracellular matrix proteins COMP, FN1, TNC and TNXB in synovial/capsule specimens from patients with idiopathic adhesive capsulitis. Possible associations between the measured mRNA levels and clinical parameters were also investigated.B2M and HPRT1 genes were used as references to normalize target gene expression in the shoulder tissue samples.We obtained glenohumeral joint synovium/capsule specimens from 9 patients with idiopathic adhesive capsulitis who had not shown improvement in symptoms after 5 months of physiotherapy. Adhesive capsulitis was confirmed in all patients by magnetic resonance imaging. We also obtained specimens from 8 control patients who had underwent surgery for acute acromioclavicular joint dislocation and who had radiological indication of glenohumeral capsule alteration based on arthroscopic evaluation. mRNA expression in the synovium/capsule specimens was analyzed by quantitative reverse transcription PCR. The TNC and FN1 expression than those from the controls. Additionally, symptom duration directly correlated with expression of TGFβ1 receptor I.The synovium/capsule samples from the patients with adhesive capsulitis had significantly higher TNC and FN1 expression may be a marker of capsule injury. Upregulation of TGFβ1 receptor I seems to be dependent on symptom duration; therefore, TGFβ signaling may be involved in adhesive capsulitis. As such, TNC, FN1 and TGFβ1 receptor I may also play roles in adhesive capsulitis by contributing to capsule inflammation and fibrosis.Elevated levels of  Adhesive capsulitis, or frozen shoulder, is a debilitating condition in which patients present limited active and passive glenohumeral motion. Adhesive capsulitis occurs in 3%-5% of the general population Rodeo et al. suggested that cytokines, such as transforming growth factor beta (TGFβ), may be involved in the inflammatory and fibrotic processes that occur in adhesive capsulitis. These cytokines may cause abnormal regulation of collagen expression and augment fibroblast proliferation TGFβ induces fibroblasts to synthesize, remodel and contract extracellular matrix (ECM), making this cytokine a key mediator of the fibrotic response PLOD1 and PLOD2 genes, respectively) 11TGFβ1, a key member of the TGFβ superfamily, regulates the collagen-modifying enzymes lysyl oxidase (LOX) PLOD2 expression has been reported in fibroblasts isolated from hypertrophic scars, keloids and palmar fascia from patients with Dupuytren disease Lysyl hydroxylases such as PLOD1 and PLOD2 promote cross-linking in ECM molecules, which contribute to ECM structural stability and maturation TGFβ regulates and is regulated by several ECM proteins. Cartilage oligomeric matrix protein (COMP), a glycoprotein found in the ECM of joints, plays a catalytic role in fibrillogenesis FN1 gene, is involved in several biological processes, including cell adhesion, tissue development and wound healing Fibronectin (FN), a glycoprotein encoded by the Moreover, the tenascins (TN), including TNR, TNC and TNX, are a highly conserved family of ECM glycoproteins. TNR is expressed only in the brain, whereas TNC and TNX are expressed in several organs and tissues, including in the joints TGFβ1, TGFβR1, LOX, PLOD1, PLOD2, COMP, FN1, TNC and TNXB genes in glenohumeral synovium/capsule samples collected from patients with adhesive capsulitis and from controls. We also evaluated how these mRNA levels are associated with clinical features.In the present study, we quantified the mRNA expression of the The current study used a case-control study design (level 3 evidence). All patients and controls were treated at the Hospital São Paulo of the Universidade Federal de São Paulo. Each patient agreed to participate by signing a written consent form before data and sample collection. This study was approved by the ethics committee of the Universidade Federal de São Paulo .The case group was composed of 9 patients with idiopathic adhesive capsulitis of the shoulder in freezing or frozen stages who were diagnosed by clinical evaluation. During the clinical evaluations, the patients presented with pain, loss of motion and severe limitations during daily activities; no history of trauma or previous shoulder pathologies; and functional restriction of both active and passive shoulder motion. Magnetic resonance imaging (MRI) was used to exclude secondary stiff shoulder. The patients underwent arthroscopic shoulder capsular release after a concerted effort was made to treat them with conservative management for at least 5 complete months. In all cases, the physiotherapy had failed. Additionally,patients meeting the following exclusion criteria were omitted: generalized arthritis; previous compromise of the shoulder, such as major trauma, fracture, rotator cuff tear, calcifying tendinitis, or shoulder instability; and superior labral anterior and posterior (SLAP) lesions. Additionally, patients who did not agree with the informed consent terms were excluded. All enrolled patients underwent an arthroscopic procedure.The control group consisted of 8 physically active subjects who underwent arthroscopically assisted treatment for acute acromioclavicular dislocation. None of the controls presented with a history of adhesive capsulitis. Moreover, radiological indication of glenohumeral capsule alteration was detected. A standard complete joint evaluation by arthroscopy confirmed that the controls did not present any other concomitant pathology in the shoulder.All patients answered a preoperative questionnaire concerning gender, age at surgery, age of pain onset, duration of symptoms, bilaterality, suprascapular nerve block, physical activity, type of work and smoking habits .3 were obtained from the anterior-inferior portion of the glenohumeral capsule during the arthroscopic procedure. To reduce sampling variation, only two of the authors (CC and BE) were responsible for collecting the tissue samples. The samples were collected as previously described 30Tissue samples of approximately 2 mm®  and then stored at -20 °C.To provide immediate stabilization of RNA, all synovium/capsule specimens were instantly preserved in Allprotect Tissue ReagentAn AllPrep DNA/RNA/miRNA Universal Kit  was used to purify total RNA from the synovium/capsule specimens. Tissue Lyser LT equipment  was used to mechanically lyse the tissue samples. A NanoDrop ND-1000 spectrophotometer  was used to determine RNA concentration and quality. RNA integrity was verified by 1% agarose gel electrophoresis. The RNA samples were stored at -80 °C.B2M and HPRT1 genes were used as reference genes to normalize sample input amount. These genes were chosen based on a previous study of suitable internal controls for the evaluation of mRNA expression in shoulder capsule samples Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to evaluate mRNA expression. First, a High-Capacity cDNA Archive kit  was used for cDNA synthesis. Then, RT-qPCR was performed as previously described using a ViiA 7 Real-Time PCR System  The relative cycle threshold method (Crt method) was used to quantify mRNA expression. In this method, the lower the cycle threshold value (Crt) value, the greater the number of initial target copies in the sample. Thus, low Crt values indicate high gene expression. The expression of the target genes was determined using the following equation: ΔCrt=target gene Crt – the mean of the reference genes Crt.All ΔCrt values are shown as the median with the interquartile range (IQR).versus non-manual job) and smoking habits. Spearman’s correlation was used to assess possible correlations between mRNA levels and duration of symptoms or age at surgery: a value below 0.40 was considered a weak correlation, a value between 0.40 and 0.59 was considered a moderate correlation, a value between 0.6 and 0.79 was considered a strong correlation and a value ≥0.80 was considered a very strong correlation. For all analyses, a p-value<0.05 was considered statistically significant. Statistical analyses were performed using PASW (SPSS) software, version 18 .The gender and age distributions between the patients with adhesive capsulitis and the controls were compared using the Chi-square test and the Mann-Whitney test, respectively. The Mann-Whitney test was also applied to compare mRNA levels between the cases and the controls, as well as to investigate the possible associations between mRNA expression and preoperative clinical variables, such as gender, practice of sports involving the upper limbs, type of job . However, the controls were significantly younger than the patients with adhesive capsulitis .TNC .p=0.005;  and FN1 p=0.043;  expressiTGFβR1 mRNA was significantly and directly correlated with the duration of symptoms . Additionally, no association was found between the mRNA levels of the studied genes and any of the clinical features assessed in the patients with adhesive capsulitis (p>0.05).No correlation was found between the age of the patients at the time of surgery and the age at symptom onset  may be considered when patients remain in pain and do not regain satisfactory range of motion after prolonged nonoperative treatment TNC and FN1 expression in glenohumeral synovium/capsule samples collected from patients with adhesive capsulitis compared to those collected from controls. TNC immunoreactivity was previously reported in other shoulder diseases, including in rotator cuff tendon tears and in the subacromial bursa of patients with impingement syndrome TNC and FN1 mRNA levels were upregulated in the glenohumeral capsules of patients with traumatic anterior shoulder instability (unpublished data). TNC is a large hexameric ECM glycoprotein that has roles in cell adhesion, fibroblast migration and other processes related to tissue remodeling and wound healing In this study, we found higher levels of Therefore, we hypothesize that increased TNC expression may be a marker of capsule injury and the genes involved may participate in inflammatory and fibrotic processes in the glenohumeral capsule.FN is essential for collagen fibril assembly TGFβR1 mRNA in the capsule was directly correlated with symptom duration in the patients with adhesive capsulitis. To the best of our knowledge, only one previous study has evaluated the role of the TGFβ receptor in adhesive capsulitis TGFβ and its receptor in capsule and synovium samples collected from patients with adhesive capsulitis and in those collected from controls We also observed that the expression of TGFβ1 and TGFβR1 mRNA between the cases and the controls. Because the synovium is adhered to the capsule and cannot be separated from the capsule using arthroscopic instruments, our investigation did not discriminate between gene expression in synovial and capsular tissues. However, molecular alterations in both tissues are important in adhesive capsulitis TGFβR1 in adhesive capsulitis. Our results suggest that TGFβR1 may have a role in adhesive capsulitis, especially in the long-term disease.In the present study, we found no differences in the expression of TGFβ1, TGFβR1, LOX, PLOD1, PLOD2, COMP, FN1, TNC and TNXB mRNA expression in the shoulder capsules of patients with adhesive capsulitis. However, this study has some limitations. First, few patients with adhesive capsulitis are surgically treated; as such, there is a limited number of tissue samples available for studies of gene expression 5230To the best of our knowledge, this study is the first to quantify TNC and FN1 mRNA may be a marker of capsule injury and may be involved in capsule inflammation and fibrosis. Upregulation of TGFβR1 seems to be related to symptom duration in adhesive capsulitis; therefore, TGFβ signaling may play a role in this condition.Elevated expression of Cohen C, Leal MF, Smith MC, Ejnisman B and Faloppa F conceived and designed the experiments. Cohen C, Belangero PS, Figueiredo EA, Andreoli CV, Pochini AC and Ejnisman B were involved in data collection. Cohen C, Belangero PS, Figueiredo EA, Figueiredo EA, Pochini AC and Ejnisman B were responsible for sample collection. Leal MF was involved in the genetic analysis. Cohen C, Leal MF, Belangero PS and Figueiredo EA performed the literature search. Leal MF and Smith MC were involved in data and statistical analyses. Cohen C and Leal MF wrote the first draft of the manuscript. All authors listed have contributed to all subsequent drafts and all have approved the final manuscript.


BRCA1 and BRCA2 genes have a high lifetime risk of breast cancer. BRCA1 and BRCA2 are involved in DNA double-strand break repair, DNA alterations that can be caused by exposure to reactive oxygen species, a main source of which are mitochondria. Mitochondrial genome variations affect electron transport chain efficiency and reactive oxygen species production. Individuals with different mitochondrial haplogroups differ in their metabolism and sensitivity to oxidative stress. Variability in mitochondrial genetic background can alter reactive oxygen species production, leading to cancer risk. In the present study, we tested the hypothesis that mitochondrial haplogroups modify breast cancer risk in BRCA1/2 mutation carriers.Individuals carrying pathogenic mutations in the BRCA1/2 for 129 mitochondrial polymorphisms using the iCOGS array. Haplogroup inference and association detection were performed using a phylogenetic approach. ALTree was applied to explore the reference mitochondrial evolutionary tree and detect subclades enriched in affected or unaffected individuals.We genotyped 22,214  mutation carriers belonging to the Consortium of Investigators of Modifiers of BRCA2 mutation carriers compared with the rest of clade T (hazard ratio (HR) = 0.55; 95% confidence interval (CI), 0.34 to 0.88; P = 0.01). Compared with the most frequent haplogroup in the general population , the T1a1 haplogroup has a HR of 0.62 . We also identified three potential susceptibility loci, including G13708A/rs28359178, which has demonstrated an inverse association with familial breast cancer risk.We discovered that subclade T1a1 was depleted in affected This study illustrates how original approaches such as the phylogeny-based method we used can empower classical molecular epidemiological studies aimed at identifying association or risk modification effects.The online version of this article (doi:10.1186/s13058-015-0567-2) contains supplementary material, which is available to authorized users. BRCA1 and BRCA2. Pathogenic mutations in BRCA1 and BRCA2 confer lifetime breast cancer risk of 60% to 85% [BRCA1 and BRCA2) have been identified as modifiers of breast cancer risk and increase or decrease the risk initially conferred by BRCA1 or BRCA2 mutation [Breast cancer is a multifactorial disease with genetic, lifestyle and environmental susceptibility factors. Approximately 15% to 20% of the familial aggregation of breast cancer is accounted for by mutations in high-penetrance susceptibility genes , such as% to 85% ,5 and 40BRCA1 and BRCA2 are involved in DNA repair mechanisms, including double-strand break (DSB) repair by homologous recombination [bination ,8. DSBs bination . Reactivbination .ROS are naturally occurring chemical derivatives of metabolism. Elevated levels of ROS and downregulation of ROS scavengers and/or antioxidant enzymes can lead to oxidative stress, which is associated with a number of human diseases, including various cancers . The eleHuman mitochondrial DNA (mtDNA) has undergone a large number of mutations that have segregated during evolution. Those changes are now used to define mitochondrial haplogroups. Some of these changes slightly modify metabolic performance and energy production; thus, not all haplogroups have identical metabolic capacities . It has Mitochondrial haplogroups have been associated with diverse multifactorial diseases, such as Alzheimer’s disease , hypertrBRCA1/2 (CIMBA) [. CIMBA is a collaborative group of researchers working on genetic modifiers of cancer risk in BRCA1 and BRCA2 mutation carriers. As part of the COGS project, more than 200,000 single-nucleotide polymorphisms (SNPs) were genotyped for BRCA1 and BRCA2 female mutation carriers on the iCOGS chip, including 129 mitochondrial polymorphisms. The iCOGS chip is a custom Illumina™ Infinium genotyping array  designed to test, in a cost-effective manner, genetic variants related to breast, ovarian and prostate cancers.The Collaborative Oncological Gene-environment Study  (COGS) i (CIMBA) . CIMBA iBRCA1 or BRCA2 mutations. Our study includes females diagnosed with breast cancer and unaffected carriers belonging to CIMBA. We used an original analytic phylogenetics-based approach implemented in a homemade algorithm and in the program ALTree [In this study, we explored mitochondrial haplogroups as potential modifiers of breast cancer risk in women carrying pathogenic m ALTree ,34 to inA signed informed written consent form was obtained from all participants. All contributing studies involved in CIMBA received approvals from the institutional review committees at their host institutions. Ethical committees that approved access to the data analyzed in this study are listed in Additional file BRCA1 mutation carriers, as well as 3,989 invasive breast cancer and 3,689 unaffected BRCA2 mutation carriers, all belonging to CIMBA. Supplementary specifications regarding inclusion profiles and studies belonging to CIMBA are available in the reports by Couch et al. [et al. [BRCA1 and BRCA2 mutation carriers . Eligible female carriers were aged 18 years or older and had a pathogenic mutation in BRCA1 and/or BRCA2. Women with both BRCA1 and BRCA2 mutations were included in downstream analyses. Data were available for year of birth, age at study recruitment, age at cancer diagnosis, BRCA1 and BRCA2 mutation description and self-reported ethnicity. Women with ovarian cancer history were not excluded from analyses, and they represented 15% and 7% of BRCA1 and BRCA2 mutation carriers, respectively. Information regarding mastectomy was incomplete and was therefore not used as an inclusion or exclusion parameter.Final analyses included 7,432 breast cancer cases and 7,104 unaffected h et al.  and Gaud [et al. . All anaBRCA1 and BRCA2 mutation carriers. SNPs fulfilling the following criteria were excluded from downstream analyses: monoallelic SNPs , SNPs with more than 5% data missing, annotated as triallelic, or having probes cross-matching with the nuclear genome. Heterozygous genotypes were removed from analyses, and we further filtered out SNPs having more than 5% of heterozygous calls to limit the potential for heteroplasmy affecting our results. We also did not retain SNPs representing private mutations. These mutations are rare, often restricted to a few families, and not sufficiently prevalent in the general population to be included in the reference mitochondrial evolutionary tree (see below). This last step of filtration yielded 93 and 92 SNPs for the pop1 and pop2 analyses, respectively  were included in downstream analyses .Genotyping was conducted using the iCOGS custom Illumina Infinium array. Data from this array are available to the scientific community upon request. Please see  for moreAnalyses were based on the theoretical reconstructed phylogenetic tree of the mitochondrial genome (mtTree) known as PhyloTree  (v.15). pop1 and pop2, respectively. Thus, for each of the 7,864 nodes of the phylogenetic tree, the corresponding short haplotype  was defined. Some of the short haplotypes are unique, and they can be matched with their corresponding haplogroup directly. However, most of the time, given the small number of SNPs analyzed, several haplogroups correspond to the same short haplotype. Consequently, a unique haplogroup cannot confidently be assigned to each short haplotype. Therefore, each short haplotype was assigned the most recent common ancestor of all the haplogroups that share the same short haplotype. Once this matching was done, short haplotypes were reconstructed in the same way for each individual in our dataset and were assigned the corresponding haplogroup. The accuracy of the method used was assessed by application to a set of 630 mtDNA sequences of known European and Caucasian haplogroups  are permutated 1,000 times to see to what extent the observed distribution of affected or unaffected is different from a random distribution. A procedure to correct for multiple testing adapted to nested tests [P-value obtained for all tests performed on one tree is corrected.This phylogenetic approach is based on the identification of subclades in the reference phylogenetic tree of the mitochondrial genome differentially enriched for cases and unaffected controls compared with neighboring subclades. We used ALTree ,34 to peed tests  is impleALTree is used to perform homogeneity tests to detect differences in enrichment or depletion of affected or unaffected individuals between clades in the phylogenetic tree. This kind of test can be performed only on independent data. However, because some individuals in the CIMBA dataset belong to the same family, we constructed datasets with genetically independent data by randomly selecting one individual from among all those belonging to the same family and sharing the same short haplotype. To take into account the full variability of our data, we resampled 1,000 times. The results of the analysis pipeline are obtained for each resampling independently and then averaged over the 1,000 resamplings to obtain final results.Before the ALTree localization algorithm was launched, ancestral sequences were reconstructed at each internal tree node; that is, short haplotypes were inferred with maximum likelihood at all nodes that were not leaves. We used the software PAML  to perfoaltree-add-S adds to the short haplotype sequence a supplementary character called S, which represents the disease status associated with this short haplotype. Are individuals carrying this short haplotype more often affected or unaffected? S is calculated based on the affected and unaffected counts, the relative proportion of affected and unaffected in the whole dataset, and sensibility parameter ε. ε was set to its default value, which is 1. After S character computation, haplotypes including character S are reconstructed at ancestral nodes. Susceptibility site localization is achieved with ALTree by computing a correlated evolution index calculated between each change of each site and the changes of the character S in the two possible directions of change. The sites whose evolution are the most correlated with the character S are the most likely susceptibility sites.ALTree also includes an algorithm used to identify which sites are the most likely ones to be involved in the association detected. For each short haplotype observed, the ALTree add-on The analyses were carried out on the full evolutionary tree. However, the more haplogroups there are at each level, the less statistical power homogeneity tests have. Therefore, analyses were also applied to subclades extracted from the tree. Subclades were defined using counts of individuals in each haplogroup of the clade to maximize statistical power. The chosen subclades and corresponding affected and unaffected counts are presented in Table BRCA1 or BRCA2). Familial dependency was handled by using a robust sandwich estimate of variance .We quantified the effect associated with enrichment discovered by applying ALTree by building a weighted Cox regression in which the outcome variable is the status (affected or non-affected) and the explicative variable is the inferred haplogroup. Analyses were stratified by country. Data were restricted to the clades of interest. The uncertainty in haplogroup inference was not taken into account in the model. The weighting method used takes into account breast cancer incidence rate as a function of age  and the BRCA1 and BRCA2 mutation carriers. For BRCA1 mutation carriers, we reconstructed 489 distinct short haplotypes of 93 loci from the genotypes data. Only 162 of those 489 short haplotypes matched theoretical haplotypes reconstructed in the reference mitochondrial evolutionary tree. These 162 haplotypes represented 13,315 of 14,536 individuals. Thus, 91.6% of BRCA1 mutation carriers were successfully assigned a haplogroup. For BRCA2 mutation carriers, we reconstructed 350 distinct short haplotypes of 92 loci from our genotype data. Only 139 of those 350 short haplotypes matched theoretical haplotypes reconstructed in the reference mitochondrial evolutionary tree. These 139 haplotypes represented 6,996 of 7,678 individuals. Thus, 91.1% of BRCA2 mutation carriers were successfully assigned a haplogroup. Because more BRCA1 than BRCA2 mutation carriers were genotyped , we logically observed more distinct haplotypes in pop1 than in pop2 (489 vs. 350 haplotypes).In Additional file The accuracy of the main haplogroup inference method used was estimated at 82% and reached 100% for haplogroups I, J, K, T, U, W and X. Given the set of SNPs we disposed of, our method has difficulty differentiating between H and V haplogroups  in the population of individuals of BRCA2 mutation carriers (P = 0.04).For both populations of P-values were examined to determine at which level of the tree ALTree detects a difference of enrichment in affected or unaffected individuals . We also tested haplogroup T1a1 and compared it with other T* haplogroups and the H haplogroup , and we found a breast cancer HR of 0.62 .The ALTree method is able to detect an association, but cannot to quantify the associated effect. We estimated the risk of breast cancer for individuals with the T1a1 haplogroup compared with individuals with another T subclade haplogroup in the population of BRCA1/2 mutation carriers. We successfully inferred haplogroups for more than 90% of individuals in our dataset. After haplogroup imputation, the ALTree method identified T1a1 in the T clade as differentially enriched in affected BRCA2 mutation carriers, whereas no enrichment difference was found for BRCA1 mutation carriers. The T subclade is present in 4% of African populations compared with 11% in Caucasian and Eastern European populations [BRCA1 mutation carriers and 9.30% of BRCA2 carriers. The ALTree method also identified three potential breast cancer susceptibility loci in mtDNA. The main goals of using the phylogenetic method we used were to improve statistical power by regrouping subclades according to genetic considerations, to limit the number of tests performed and to precisely quantify this number. ALTree identified three SNPs of interest. Whereas the association we observed could possibly be driven by a single SNP, no difference was observed between multivariate and univariate cox models including the three SNPs identified by ALTree (data not shown).We employed an original phylogenetic analytic method, coupled with more classical molecular epidemiologic analyses, to detect mitochondrial haplogroups differentially enriched for affected ulations . In our BRCA1/2. A large proportion of breast cancer heritability still remains unexplained today [BRCA1 and BRCA2 susceptibility genes) or genome-wide association studies (GWASs). However, classical linkage analysis cannot be applied to the haploid mitochondrial genome. Furthermore, commercial GWAS chips available do not adequately capture the majority of mtDNA SNPs. A non-genome-wide and mtDNA-focused approach was required to explore how mtDNA variability influences breast cancer risk. Here we have shown that BRCA2 mutation carriers with the subclade T1a1 have between 30% and 50% less risk of breast cancer than those with other clades, which, if validated, is a clinically meaningful risk reduction and may influence the choice of risk management strategies.In this study, we investigated to what extent mtDNA variability modified breast cancer risk in individuals carrying pathogenic mutations in ed today . DiffereBRCA2, but not BRCA1, mutation carriers may reveal a functional alteration that would be specific to mechanisms involving BRCA2-related breast cancer. Today, it is established that BRCA1- and BRCA2-associated breast cancers are not phenotypically identical. These two types of tumors do not harbor the same gene expression profiles or copy number alterations [BRCA1/2 mutation carriers have already been identified [BRCA2 mutation carriers only.The association we observed among erations . Breast entified . Howeverentified . It is tOur inability to assign haplogroups to 9% of study participants could have three main explanations. First, given the high mutation rate in the mitochondrial genome, observed combinations of mtDNA SNPs might have appeared relatively recently in the general population, and the corresponding haplotypes might not yet be incorporated into PhyloTree. Second, only one genotyping error could lead to chimeric haplotypes that do not exist, although, given the quality of our genotyping data, this is unlikely. Third, the mitochondrial reference evolutionary tree PhyloTree is based on phylogeny reconstruction by parsimony, and, for some subclades, it might be suboptimal, especially for haplogroups relying on few mitochondrial sequences, as is the case for African haplogroups . In caseWe quantified the effect corresponding to the detected association by using a more classical approach. We built a weighted Cox regression including inferred haplogroup as an explicative variable. However, the uncertainty in haplogroup inference was not taken into account in this model. Nevertheless, based on haplogroup assignment and regrouping performed in clade T, affected and unaffected counts of individuals in this clade were not biased.With only 129 loci genotyped over the 16,569 nucleotides composing the mitochondrial genome, we certainly did not explore the full variability of mitochondrial haplotypes. A characterization of individual mitochondrial genomes would require more complete data acquisition methods to be used, such as next-generation sequencing. However, next-generation sequencing has its own limits and challenges, because some regions of the mitochondrial genome are not easily mappable, owing to a high homology with the nuclear genome, among other factors, and important bioinformatics treatment is necessary to overcome sequencing technology biases. Finally, even for a relatively short genome of “only” 16,569 bp, mtDNA sequencing of more than 20,000 individuals would represent a major increase in cost relative to genotyping 129 SNPs.MT-CO3, MT-ND4 and MT-ND5, respectively. When looking at PhyloTree, T9899C seems to be involved in T1 subclade definition, whereas G13708A and A11812G are involved in T2 subclade definition. Whereas T98899C and G11821/rs41544217 are synonymous SNPs, G10398A leads to a change of amino acid in the final protein . These two synonymous SNPs have never been described in a disease context in the literature. G13708A is also known for being a secondary mutation for Leber’s hereditary optic neuropathy (LHON) and multiple sclerosis [ALTree identified T9899C, G11812A/rs41544217 and G13708A/rs28359178 as three potential susceptibility sites for the discovered association (see Additional file clerosis . Althougclerosis . A high clerosis . Interesclerosis . None ofP-value obtained using ALTree in studying clade T is 0.02, which is not highly significant. A replication step should be performed to validate these results. However, it will be difficult to include enough women in this replication step, given the specific profile studied here. In fact, the estimations of BRCA2 pathogenic mutations in the general population range from 0.068% [The corrected m 0.068%  to 0.69%m 0.068% . T1a1 reBRCA2 mutation carriers. For now, this observation cannot be extended to the general population. Further investigation of the biological mechanism behind the associations we observed may further reinforce the hypothesis that the mitochondrial genome is influential in breast cancer risk, particularly among carriers of BRCA2 mutations, and, if validated, is of a level to influence cancer risk management choices.This study and our results suggest that mitochondrial haplogroup T1a1 may modify the individual breast cancer risk in


Our findings indicate that individual sets of parameters may require different shipment settings . Most of the parameters except for ion  handling and, possibly, reticulocytes counts, tend to favor transportation at 4°C. Whereas plasma and intraerythrocytic Ca2+ cannot be accurately measured in the presence of chelators such as citrate and EDTA, the majority of Ca2+-dependent parameters are stabilized in CPDA samples. Even in blood samples from healthy donors transported using an optimized shipment protocol, the majority of parameters were stable within 24 h, a condition that may not hold for the samples of patients with rare anemias. This implies for as short as possible shipping using fast courier services to the closest expert laboratory at reach. Mobile laboratories or the travel of the patients to the specialized laboratories may be the only option for some groups of patients with highly unstable RBCs.Transportation of blood samples is unavoidable for assessment of specific parameters in blood of patients with rare anemias, blood doping testing, or for research purposes. Despite the awareness that shipment may substantially alter multiple parameters, no study of that extent has been performed to assess these changes and optimize shipment conditions to reduce transportation-related artifacts. Here we investigate the changes in multiple parameters in blood of healthy donors over 72 h of simulated shipment conditions. Three different anticoagulants  for two temperatures (4°C and room temperature) were tested to define the optimal transportation conditions. Parameters measured cover common cytology and biochemistry parameters , red blood cell (RBC) volume, ion content and density, membrane properties and stability , Ca Guidelines to handle blood samples for analysis in clinical laboratories have been established and are continuously updated by the International Council for Standardization in Hematology. However, these guidelines refer mostly to standard operating procedures (SOPs) for particular types of analysis and the instrumentation for assessment of the standard clinical parameters. Whereas, the safety of shipment of blood samples is regulated by the guidelines issued by the World Health Organization  stability and function  for transportation it is more difficult to maintain conditions like the temperature constant or to control shear stress to which the samples may be exposed and (ii) clinical practice and laboratory conditions at the place of blood collection may not allow for complicated or time consuming procedures, e.g., for blood component separation, after blood withdrawal.Putative lysis of white blood cells and platelets and the associated enzyme release is of particular importance as are known to have negative effects on the RBCs and are difficult to control. Leucodepletion before shipment would improve the quality of RBCs and reduce the transportation-related artifacts. However, this is often not possible also due to a limited blood sample size of anemic patients or children.In the present study we have evaluated the impact of up to 3 days of transportation of whole blood collected from healthy donors into standard vacutainers supplemented with the most widespread anticoagulants  at 4°C or at room temperature on a number of parameters measured with common and specialized techniques used within the research consortium CoMMiTMenT, Combined Molecular Microscopy for Therapy, and Personalized Medication in Rare Anemia Treatments'. Measurements were performed in parallel in four laboratories in Barcelona, Homburg/Saar, Utrecht, and Zürich. Although the present study was performed on blood of healthy volunteers, we aimed for producing some guidelines for optimal shipment conditions for whole blood samples for investigations of RBCs from patients with rare and very rare anaemias to ensure reproducibility of results obtained by different groups within the consortium and beyond.In all laboratories participating in the present study the same blood collection system  and the same batches of 9 mL containers for K3EDTA (referred to as EDTA), Sodiumheparin (referred to as heparin) and citrate phosphate dextrose-adenine (referred to as CPDA), respectively,  were used. For the sake of standardization, six tubes of blood were collected from each donor (3 anticoagulants × 2 transportation temperatures) at the nominal tube capacity to ensure well-defined anticoagulant concentrations. However, depending on the duration of the experiments to perform, the time points of withdrawal for the different conditions may have been adapted. In other words: the time schedule of the experiments was given the priority at the cost that blood withdrawal (of the same donor) was at different time points. For all participating laboratories ethical statements of the national authorities have been granted . Within this study we investigated blood samples from 22 donors.2 Affinity, pO250 was measured in these blood samples within the first hour of blood collection, at 24, 48, and 72 h after blood withdrawal. All statistical analysis, even in case of single cell methods, were based on the donors.Freshly drawn whole blood samples supplemented with heparin, CPDA, or EDTA were stored at 4 ± 1°C (in a refrigerator or cold storage room) and at room temperature 22 ± 2°C. To simulate transportation, we introduced cycles of immobilization with several rounds of shaking a day. Different shakers have been used but we sticked to a protocol of a shaking frequency of 120 per minute for a total of 3 h shaking within a 24 h period divided into 3 intervals. The whole range of parameters listed in Sections from Complete Blood Count (CBC) to Measurements of Hemoglobin OAutomatic cell analyzers, ADVIA 2120  and Cell-Dyn Sapphire  were used to measure hematological parameters: red blood cell count (RBC), hemoglobin concentration (Hb), RBC volume percentage (HCT), mean cell volume (MCV), mean cell hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and absolute as well as percentage number of reticulocytes in all samples.Peripheral blood smears were prepared on microscope slides  and stained with a May–Grünwald-Giemsa protocol. The staining procedure consisted of immersing the slides for 1.5 min in May–Grünwald's eosin-methylene blue solution  and, after washing up the excess solution with water, staining the slides for 20 min with 10% Giemsa stain solution . Furthermore, slides were left to dry for at least 30 min ]. This buffer was designed taking into accounts recent findings on the role of plasma-borne amino acids and Zn2+ ions in control of Ca2+ uptake by RBCs  density gradient 0.5 mL of blood sample were gently placed on top of the 90% Percoll mixture  was measured as a function of continuously changing osmotic conditions. The EI is defined as the ratio between (A−B)/(A+B), where A and B are defined as the length and the width of the RBC population under this changing osmolality at constant shear stress. Results were analyzed with the supplied Osmoscan software.The sensitivity of the RBC membrane to heat was tested at three different incubation times  and at two different temperatures (46 and 49°C) in a cacodylate solution , IgG2bκ, eBioscience, San Diego, CA, USA]. Biotinylated monoclonal mouse anti-human CD235a  and isotype controle IgG2bκ  were used as secondary antibodies. Finally, streptavidin poly-HRP (Sanquin) and Super Signal West Pico Chemiluminescent Substrate  were used as detection reagents and measured using a Biotek Syngery2 plate reader. For Western Blot analysis, vesicles from plasma were first isolated using differential centrifugation, one time for 45 min at 10,000 g followed by two times for 70 min at 100,000 g, in a Beckman Coulter Optima L-90K. Samples were dissolved in DTT containing sample buffer and equally loaded (10 μg protein) on 10% SDS-page gels. After migration, samples were loaded to PVDF membranes and incubated with monoclonal mouse anti-human Band 3  and polyclonal rabbit anti-human CD235a  antibodies.For ELISA experiments, whole blood was centrifuged for 10 min at 2,000 g and the obtained plasma was further centrifuged for 10 min at 10,000 g to remove residual cells and debris. Plasma was then diluted and transferred to Nunc Maxicorp21, CaCl22, D-glucose 5, HEPES 10, pH = 7.3. Gigaseals were considered successful if exceeding 1 GΩ . Gigaseal formation was facilitated by the use of a seal enhancing solution as recommended by the manufacturer of the Patchliner containing (in mM): NaCl 80, KCl 3, MgCl210, CaCl235, HEPES  10, pH = 7.4. Whole-cell configuration was achieved by negative pressure suction pulses of between −45 and −150 mbar and its formation was judged by the appearance of sharp capacitive transients.Patch-clamp measurements were performed with a Patchliner . The resistance of chips was between 5 and 8 MΩ with internal solution (in mM): CsCl 50, CsF 60, NaCl 20, EGTA 20, HEPES 10, MgATP 5, pH = 7.2, and external solution (in mM): NaCl 140, KCl 4, MgCl2+imaging was performed based on the Ca2+-fluorophor Fluo-4  using a protocol of stimulation with lysoposphadidic acid  and a consecutive analysis as previously described  for 1 h. Subsequently RBCs were washed in buffer C supplemented with 0.1% BSA for three times  and the final volume of RBC mass was determined as hematocrit. Next, one part of packed cells was mixed with 30 parts of lysis buffer  and incubated on ice for 30 min. RBC membranes were precipitated  and the amount of [3H]MK-801 molecules bound to NMDA receptors was assessed using Packard 1600 TR liquid scintillation analyzer . The quantity of NMDA receptors per cell was calculated as described elsewhere . Then RBC concentration was adjusted to 20% HCT by buffer C and cells were incubated with the NMDA receptor channel blocker MK-801 binding sites per cell is a quantitative measure for the number of active NMDA receptors in RBCs , hexokinase (HK), phosphofructokinase (PFK), and pyruvate kinase (PK) are enzymes that can be affected. It should be noted though that spectrophotometric analysis is of limited sensitivity and fails to detect moderate to small changes in G6PD activity  instant conservation of the cell at the time of withdrawal and (ii) maintenance of RBCs living conditions to keep the surrounding undisturbed imitating in vivo parameters.If we regard a transportation condition as best, when under one condition (anti-coagulant and temperature) all time points show maximal consistency and minimal differences with control values, we have to admit that we face a complex situation lacking an universal optimal shipment condition for all parameters we have measured. For example cation gradients are best preserved at 22°C Figure , whereas0 Figure , just toMost of the transport-induced alterations develop over time Figures –11 but s* give values that change with time of transportation following a certain pattern that can be described with a correcting equation  and (ii) could possibly be relevant for the transportation-induced alterations in reticulocyte count for the blood samples in EDTA Figure  and are 2+ and metabolic activity. In order to relate the results for the parameters obtained we performed cross correlation analysis trying to decipher interdependencies between different measured parameters , the Na+/K+-ATPase is suppressed approximately three-fold .CaH Figure . Since sFurthermore, the much higher rate of lactate production correlated with the higher acidification rate and plasma acidification at 22°C compared to 4°C shows that RBCs metabolic processes are strictly temperature-dependent Figure . Over ti250 as presented in Figure A correlation between pH-value and pO2+ . In order to use these abnormal shipment-induced RBC alterations as markers, blood samples of healthy subjects should be shipped together with the samples of patients. Special attention in the context of diseased RBCs needs the hemolysis Figure  that migLK, JV, RV, AB, MM, and HE planned the study design; AM, RH, LV, MD, EL, PP, JW, and AB performed experiments; AM, RH, LV, MM, EL, PP, JW, AB, RV, and LK analyzed the data; LK wrote the paper; AM, RH, MM, PP, HE, AB, RV, JV, and LK 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. The reviewer AFM and handling Editor declared a previous collaboration and the handling Editor states that the process nevertheless met the standards of a fair and objective review.


Due to the importance and complexity of photo assimilate transport in raffinose family oligosaccharide (RFO)-transporting plants such as melon, it is important to study the features of the transport structure (phloem) particularly of the lateral branches connecting the source leaves and the sink fruits, and its responses to environmental challenges. Currently, it is unclear to what extents the cold environmental temperature stress would alter the phloem ultrastructure and RFO accumulation in RFO-transporting plants. In this study, we firstly utilized electron microscopy to investigate the changes in the phloem ultrastructure of lateral branches and RFO accumulation in melons after being subjected to low night temperatures (12°C and 9°C). The results demonstrated that exposure to 9°C and 12°C altered the ultrastructure of the phloem, with the effect of 9°C being more obvious. The most obvious change was the appearance of plasma membrane invaginations in 99% companion cells and intermediary cells. In addition, phloem parenchyma cells contained chloroplasts with increased amounts of starch grains, sparse cytoplasm and reduced numbers of mitochondria. In the intermediary cells, the volume of cytoplasm was reduced by 50%, and the central vacuole was present. Moreover, the treatment at 9°C during the night led to RFO accumulation in the vascular bundles of the lateral branches and fruit carpopodiums. These ultrastructural changes of the transport structure (phloem) following the treatment at 9°C represented adaptive responses of melons to low temperature stresses. Future studies are required to examine whether these responses may affect phloem transport. Phloem is responsible for the transport of photoassimilates, such as carbohydrates, amino acids, and other nutrients from source tissues such as mature leaves to sink tissues such as fruits, shoots and root apical tissues, and developing organs –3. HormoThe functions of the phloem are different according to the organ’s locations. While the loading phloem in source organs (minor veins) is responsible for the active loading of photo assimilates into the phloem, the unloading phloem in sink organs delivers assimilates to sink tissues, and the transport phloem  translocates water and solutes from sources to sinks . Active Arabidopsis and tobacco, raffinose family oligosaccharide (RFO)-transporting plants such as melons (belonging to the family Cucurbitaceae) translocate significant concentrations of RFOs in their phloem, primarily stachyose . The experiment of low night temperature treatments was performed in three replicates.Following pollination for 7 d and after the young fruit had started to expand, the plants were environmentally hardened in a controlled environmental chamber to receive different night temperature treatments [12 h light; 6:00–10:00 (475±50) μmol/ examination. The small phloem fragments of the lateral branches in the same position  overnight at 4°C with three changes, dehydrated in an graded ethanol series, critical-point-dried through carbon dioxide, mounted on stubs, and coated with gold . The pre-1 phosphate buffer, dehydrated in a graded series of ethanol and acetone solutions , infiltrated with acetone and resin mixtures at proportions of 3:1, 1:1 and 1:3 and then embedded in resin. After polymerization , the embedded tissues were sectioned with a LKB-2088 ultramicrotome, stained with uranyl acetate and lead citrate followed by Reynolds lead citrate [The sample fragments were fixed in 2.5% glutaraldehyde overnight at 4°C with three changes. The phloem of a single vascular bundle was excised from the same region of each lateral branch, collected, washed with 0.1 M phosphate buffer and fixed with 1% osmiumtetroxide overnight at 4s°C. The phloem tissues were then washed again with 0.1 mol·L citrate . StainedThe samples of lateral branches and carpopodiums were ground in 10 mL 80% (v/v) ethanol in a tube, and then the tube was placed in a boiling water bath for 1 h, cooled, and centrifuged at 1,000 g for 10 min. The pellet was extracted two additional times with 10 mL 80% (v/v) ethanol. The supernatants from each extraction were combined and evaporated to dryness in a boiling water bath. The samples were resolubilized in 0.5 or 1 mL distilled water and filtered through an acetate filter .2 column  and a Waters 2410 refractive index detector connected to a strip chart recorder. Distilled water, at a flow rate of 10 mL/min, was used as the solvent of the 70% (v/v) acetonitrile. The column temperature was maintained at 35°C and was preceded by a Waters Bondapak C18/Corasil guard and a set of anion and cation cartridges . All guards were operated at an ambient temperature of 25°C, and 20 μL samples were injected. The RFOs were identified and quantified from the retention times and the peak heights of stachyose and raffinose standards. All of chemicals were of chromatographical grade in purity. The standards of stachyose and raffinose were purchased from Sigma .The contents of RFOs (including stachyose and raffinose in this experiment) were determined using the method of high performance liquid chromatography (HPLC) . The sysThe experiment was performed in three replicates, and each replicate has three samples (from three plants). For the analyses of TEM images, each replicate has three samples (from three plants), fifty visual fields were observed for each sample and about one hundred cells were analyzed. The percentages of certain phenotypes were the ratios of the numbers of phenotype cells to the total of one hundred cells in the fifty visual fields . The results shown in The vascular bundles of the melons consisted of inner and outer rings, with each ring containing five vascular bundles . The vasThe phloem in lateral branches of melons was mainly composed of sieve elements (SE), companion cells (CC), intermediary cells (IC) and phloem parenchyma cells (PP) . The sieThe fully mature sieve elements (SE) in the phloem of vascular bundles in the lateral branches were hollow conducting cells . At earlCompanion cells (CC) were located in close proximity to sieve elements and formed sieve element-companion cell complexes. These companion cells contained strongly stained, dense cytoplasm and numerous organelles, e.g., mitochondria and plastids (no starch). The companion cells also contained a large nucleus and a small number of vacuoles (V) . It was Parenchyma cells (PP) in the phloem of vascular bundles in the lateral branches of melons were larger than companion cells. Phloem parenchyma cells were found around sieve elements. Compared with companion cells, the cytoplasm of parenchyma cells was rather sparse. In addition, these cells contained a relatively large, round or irregularly shaped nucleus and were rich in organelles such as spherical mitochondria and rod-shaped chloroplasts. Some endoplasmic reticulum was also present in phloem parenchyma cells .A subset of the parenchyma cells were in the process of differentiating into sieve elements. In these differentiating parenchyma cells, vacuoles underwent fusion to form larger vacuoles. A filamentous structure, likely composed of P-proteins, was found in the vacuoles. In the nuclei, the chromatin had begun to condense and aggregate towards the edge. The perinuclear space became enlarged, and the vacuoles gradually occupied most of the cell volume, with vacuolar fusion occurring at areas of contact between vacuoles. Small vesicles formed at the edge of the vacuoles, trapping cytoplasm inside, where it slowly disintegrated. The vacuoles then started to lose membrane integrity. Multi-membranous structures formed in some vacuoles, with a small amount of cytoplasm trapped within. The vacuolar membrane eventually broke down completely, and the clear boundary between the vacuoles and the cytoplasm disappeared. The cytoplasm then became rather sparse, leaving small floccules in the cells. The volume of the nucleus decreased, and apoptotic bodies formed. Ultimately, the nucleus completely disintegrated, and the cytoplasm nearly disappeared. Some parenchyma cells retained a small amount of membrane structure containing protein bodies .Under normal temperature conditions, some of companion cells (CC) contained a large number of small vacuoles . VacuolaAfter 12 d of low night temperature treatment at 12°C, about 59% companion cells exhibited strong electron staining. These cells contained dense cytoplasm and numerous small vacuoles . Slight The number of intermediary cells (IC) decreased, from 50 to 25% in, as plants were growing under normal temperature conditions, most likely due to the continuous differentiation of intermediary cells into sieve elements. A cavity was formed at the center of all intermediary cells, and the cytoplasm was concentrated at the edge, forming a strongly stained, thin annular ring . These iUnder normal temperature conditions, the cytoplasm was sparse in phloem parenchyma cells (PP). Mitochondria and chloroplasts were concentrated around the edges of these cells, and little endoplasmic reticulum was present . CompareLow night temperature treatments significantly affected the RFO content in lateral branches . CompareLow night temperature treatments had a greater impact on the RFO content in carpopodiums . After 1As the main function of plant phloem is the transport of organic nutrients, primarily sugar ,21, chanPlasma membrane invagination was observed being obvious in companion and intermediary cells following low night temperature treatment at 9°C. Plasma membrane invagination has been observed in wheat under low temperature stresses . The phyMitochondria are particularly sensitive to low temperatures, though the plasma membrane is the primary site of cold injury –27. MitoLow night temperature treatments also increased the number of starch grains in chloroplasts of phloem parenchyma cells. One potential explanation of starch accumulation would be that, due to the low night temperature, sink strength of developing fruit and other sink parts of the plant is reduced as a result of decreased metabolic activity and thus there is less demand for carbon to support metabolism and growth. This would then lead to starch storage from carbon.Vacuoles are important components of the plant protoplasts. They are surrounded by vacuolar membranes and filled with dissolved substances, including hydrolytic enzymes. Once released from the vacuoles, these enzymes hydrolyze certain cellular components ,29. Low 14CO2 as a tracer to evaluate the 14C content of phloem sap in purple mullein and showed that phloem transport velocity declined at low temperatures [Our results also showed that low night temperature treatment at 9°C resulted in an increase in the RFO accumulation in lateral branches and carpopodiums. Popov et al. showed that hypothermia inhibited active transport in vascular bundles by affecting metabolic activity . Caskilleratures . It is pLow night temperature treatments at 9°C and 12°C altered the ultrastructure of cells of the transport structure (phloem) to varying degrees, with the changes at 9°C being more obvious. The ultrastructural changes included plasma membrane invagination in companion and intermediary cells; the presence of central vacuole in intermediary cells; the appearance of large numbers of starch grains, and reduced numbers of mitochondria in phloem parenchyma cells. In addition, RFO also accumulated in the vascular bundles of lateral branches and fruit carpopodiums. The changes described above represent adaptive responses of melons to low temperature stresses. However, these changes also result in a shortage of the cellular energy required for phloem transport and cellular damage, neither of which is conducive to phloem transport.S1 FigNO plasma membrane invagination in companion cells (×36000).(PDF)Click here for additional data file.S2 FigNO plasma membrane invagination in companion cells (×58000).(PDF)Click here for additional data file.S3 FigNO plasma membrane invagination in companion cells (×19000).(PDF)Click here for additional data file.S4 FigNO plasma membrane invagination in intermediary cells (×19000).(PDF)Click here for additional data file.S5 FigNO expanded central vacuole and strongly stained and thinner annular rings in intermediary cells (×14000).(PDF)Click here for additional data file.S6 FigNO expanded central vacuole and strongly stained and thinner annular rings in intermediary cells (×19000).(PDF)Click here for additional data file.S7 FigNO expanded central vacuole and strongly stained and thinner annular rings in intermediary cells (×19000).(PDF)Click here for additional data file.