Vollenhovia emeryi Wheeler (Hymenoptera: Myrmicinae), queens and males are produced clonally, while sterile workers arise sexually, unlike other ant species and Hymenopteran insects in general. Furthermore, there is a wing length polymorphism in the queen caste. Despite its evolutionary remarkable traits, little is known about the population structure of this ant species, which may provide insight into its unique reproductive mode and polymorphic traits. We performed in‐depth analyses of ant populations from Korea, Japan, and North America using three mitochondrial genes . The long‐winged (L) morph is predominant in Korean populations, and the short‐winged (S) morph is very rare. Interestingly, all L morphs were infected with Wolbachia, while all Korean S morphs lacked Wolbachia, demonstrating a association between a symbiont and a phenotypic trait. A phylogenetic analysis revealed that the S morph is derived from the L morph. We propose that the S morph is associated with potential resistance to Wolbachia infection and that Wolbachia infection does not influence clonal reproduction (as is the case in other ant species).Many eusocial insects, including ants, show complex colony structures, distributions, and reproductive strategies. In the ant  The figure clearly shows the wing morphology and Wolbachia infection status. Winglessness and wing reduction in reproductive ants are widespread across all subfamilies  is a common ant species endemic to East Asia; this species has invaded North America  and other arthropods  the population genetic structure of the mitochondrial genes of V. emeryi; (b) the phylogeographic relationships among the two winged morphs from Korea and Japan; (c) the approximate divergence time of the two winged morphs; (d) the ubiquity of Wolbachia infection in this ant species; and (e) potential relationships between host phenotype and Wolbachia infection.The present study focused on the association between the ant species, 22.1V. emeryi were collected from 74 locations between 2010–2013, including 65 locations in South Korea, eight in Japan, and one in the United States , according to the manufacturer's instructions. The extracted genomic DNA was kept at −20°C until further analyses.Genomic DNA was extracted from the whole body of Kobayashi, Hasegawa, and Ohkawara , KobayasV. emeryi (exceptions were Pat for COI and 21v2 and r8v2 for COII). The PCR temperature profile was as follows: denaturation for 3 min at 95°C, followed by 35 cycles of 1 min at 95°C, 1 min at each annealing temperature, 1–2 min at 72°C, and a final extension step at 72°C for 5 min. To examine the infection status of Wolbachia, diagnostic PCR was performed using the Wolbachia‐specific primer set WspecF, R  or a PeqSTAR Universal Gradient Thermocycler (Peqlab Gmbh). The PCR amplicons were visualized in a 1% agarose gel dyed with TopGreen Nucleic Acid Gel Stain (Genomic Base) and purified using a commercial kit  prior to sequencing. In all cases, sequences were read in both directions for maximum clarity.2.32.3.1The resultant sequences were aligned and analyzed using ClustalW embedded in MEGA  and pairwise FST, was performed with 1,000 permutations. To test the model of evolution and demographic expansion for the COI gene, neutrality tests  among regions, including the overall fixation index statistics , with a fixed connection limit at 1,000 steps between haplotypes , 2 MYA, and 3 MYA, were used, that is, The HKY + G + I model  was selected as the best fit evolutionary substitution model based on the Bayesian information criterion, as determined using MEGA  was used to examine whether there is a relationship between wing morph and 33.1h) decreased in the order COI , Cytb , and COII  and were highest in region F .We analyzed the mitochondrial COI 1,224 bp), COII (663 bp), and Cytb (839 bp) genes for a specimen from each of the 145 ant colonies. We identified 37 (COI), 25 (COII), and 26 (Cytb) unique haplotypes Table . Overall24 bp, CO3.2FST values for COI, COII, and Cytb were 0.781, 0.687, and 0.803, respectively, indicating that the regional populations are genetically isolated. For COI, the estimated migration rate  was 0.07 migrants per generation , C (−2.6215), and D (−2.4064) with 99% statistical significance, indicating that the current haplotype diversity resulted from selection on certain genotypes. Tajima's D for regions B, E, F, and H was not statistically significant, indicating neutral evolution. The τ values that represent the estimated time of expansion were very low in regions A, B, C, and D (min = 0.0 in region B and max = 1.6 in region D), indicating sudden and recent population growth , including 41.4% of samples in region A, 32.8% in region C, 17.2% in region B, and 8.6% in region D Figure . For all3.4In the phylogenetic tree, we observed that the haplotypes were clearly divided into two clades, that is, clade 1 and clade 2, and the S morph was derived from the ancestral L morph  harbored Wolbachia, but the Japanese S morph populations collected from the mid‐northern part of Japan, that is, Ishikawa and Toyama (Hap 22), were completely infected whereas populations from Tokyo  and Gifu (Hap 24) were free of Wolbachia . These results also suggest that Wolbachia is not involved in clonal reproduction in the ant species because clonal reproduction occurs in both wing morphs , which is isolated from the mainland of the Korean peninsula, had haplotype compositions distant from those of regions A to D. The haplotype compositions and frequencies in region H (Japan) were different from those in Korea  are closely related to populations in region H  indicates an extremely low dispersal rate after regional colonization, similar to the situation in Japan  seem to be undergoing purifying selection, although mitochondrial DNA is a neutral marker ; Formal analysis (lead); Investigation (lead); Methodology (lead); Software (lead); Visualization (lead); Writing‐original draft (lead). Seung‐Yoon Oh: Data curation (lead); Formal analysis (supporting); Investigation (lead); Methodology (supporting); Resources (lead); Software (supporting); Writing‐original draft (lead). Soyeon Park: Data curation (supporting); Investigation (supporting); Methodology (supporting); Resources (supporting); Software (supporting); Visualization (supporting); Writing‐original draft (supporting). Taesung Kwon: Methodology (supporting); Resources (supporting). Yonghwan Kim: Investigation (supporting); Methodology (supporting). Jae Chun Choe: Funding acquisition (supporting); Methodology (supporting); Project administration (supporting); Supervision (lead). Gilsang Jeong: Conceptualization (lead); Data curation (lead); Formal analysis (lead); Funding acquisition (lead); Investigation (lead); Methodology (lead); Project administration (lead); Resources (lead); Software (lead); Supervision (lead); Validation (lead); Writing‐original draft (lead); Writing‐review & editing (lead).Figure S1Click here for additional data file.Tables S1–S8Click here for additional data file.


Background: The purpose of this study was to evaluate the growth, tolerance and compliance effects of an extensively hydrolyzed formula with added 2′-FL in an intended use population of infants. Methods: A non-randomized, single-group, multicenter study was conducted. Infants (0–60 days of age) with suspected food protein allergy, persistent feeding intolerance, or presenting conditions where an extensively hydrolyzed formula (eHF) was deemed appropriate were enrolled in a 2-month feeding trial. The primary outcome was maintenance of weight for age z-score during the study. Weight, length, head circumference, formula intake, tolerance measures, clinical symptoms and questionnaires were collected. Forty-eight infants were enrolled and 36 completed the study. Results: Weight for age z-scores of infants showed a statistically significant improvement from study day 1 to study day 60 . Conclusions: Overall, the results of the study demonstrate that the study formula was well tolerated, safe and supported growth in the intended population. Extensively hydrolyzed infant formulas (eHF) are often the first formula recommended for infants with suspected or confirmed cow’s milk allergy or protein sensitivity who are not breast-fed or who do not tolerate breast milk. They are also used in infants with persistent intolerance symptoms such as fussiness, diarrhea, spit-up, vomiting, or constipation.Ongoing research has shown that human milk oligosaccharides (HMOs) play an important role in breast-fed infants. HMOs provide several benefits, such as acting as a prebiotic, acting as a soluble decoy receptor to prevent pathogen adhesion to the infant gut and enhancing the development of the immune system ,2. MaturIn previous growth and tolerance studies, healthy infants have been fed formula containing 2′-FL. Overall, no safety concerns were observed, and growth and measurements of tolerance were not significantly different between the experimental formulas with added 2′-FL and control formula ,10,11. IThe purpose of this study was to assess the growth, tolerance, compliance and change in clinical symptoms in infants with suspected food protein allergy or persistent feeding intolerance on an extensively hydrolyzed casein-based infant formula with added 2′-FL.Between March of 2019 and January of 2020, 48 infants were enrolled in a prospective, single group, non-randomized multicenter study. The protocol was conducted in accordance with Good Clinical Practices.clinicaltrials.gov (NCT03884309). All participants’ parents gave written informed consent approved by an Independent Ethics Committee/IRB and signed Health Insurance Portability and Accountability Act (HIPAA) documents.This study was approved by the Institutional Review Board (IRB) and was registered at Inclusion criteria included infants that were less than 60 days of age with a past medical history and clinical symptoms that accounted for the infant being placed on a hypoallergenic extensively hydrolyzed formula (eHF).® , or Nutramigen®  for persisting feeding intolerance symptoms, symptoms of suspected food protein allergy sensitivity or other conditions where eHF was deemed appropriate by their health care professional. Parent(s) of infants confirmed their intention not to administer prescription medications, over-the counter (OTC) medications (such as Mylicon® for gas), home remedies (such as juice for constipation), prebiotics, probiotics, herbal preparations or rehydration fluids that might affect gastrointestinal (GI) tolerance, unless the infants were currently consuming and had been directed by their health care professional to continue their use during the study. Parent(s) also confirmed their intention not to administer solid foods, juices, vitamins and minerals (with the exception of vitamin D). Infants received the study formula ad libitum as their sole source of nutrition.The infants were consuming an eHF formula without 2′-FL, either AlimentumInfants were excluded if they were receiving oral or inhaled steroids or if they had been treated with antibiotics , or other medications that may affect growth, GI tolerance and/or development, within 2 weeks prior to enrollment. Exclusion also included an adverse maternal, fetal or participant medical history that was thought by the investigator to have potential for effects on growth, and/or development or if the infant had an allergy or intolerance to any ingredient in the study product, as reported by the parent.® Alimentum®, Abbott Nutrition, Abbott Laboratories, Columbus, OH, USA). The study formula with the exception of the added 2′-FL was the Similac® Alimentum® commercially available in the US.The study formula was a clinically labelled hypoallergenic casein-based powdered eHF designed to provide 20 kcal per fl oz at standard dilution with 0.2 g/L of 2′-FL.  growth standards  at studyThe primary outcome was maintenance of weight for age z-score during the study. The secondary variables were mean rank stool consistency (MRSC), predominant stool color, predominant stool consistency, average daily number of stools per day, percent of feedings with spit-up/vomit associated with feeding (within 1 h), weight, interval weight gain per day, length, interval length gain per day, head circumference (HC), and interval HC gain per day.Supportive variables were average volume of study formula intake per day (mL/day), parental responses to the Infant Feeding and Stool Patterns Questionnaire, the Formula Satisfaction Questionnaire and Clinical Symptoms Questionnaire. Clinical symptoms reported by the parents were reviewed at enrollment, visit 2 (SDAY 7) and Visit 4 (SDAY60) by the investigators.Subject demographics  were collected. Safety monitoring consisted of the collection of adverse events and serious adverse events during the study.® Advisor 8.0 , Cork, Ireland) sample size software and SAS® version 9.4  were used. Data summaries are reported as Mean ± SEM for continuous data, and n (%) for categorical data.A total sample size of 30 subjects has 80% power to detect a mean change of −0.206 in weight for age z-scores from study entry to exit, assuming a standard deviation (SD) from a previous study of 0.39, using a two-sided 5% level paired t-test. These mean difference and SD correspond to the 70th percentile of the normal distribution, that is, we expect about 70% of the infants to have a change in z-score of −0.206 or better. Based on an estimated 35% attrition rate, enrollment of 47 infants was planned. The nQueryn = 2), use of medications that may affect GI tolerance (n = 1), SDAY 60 anthropometric measurement obtained outside the window (n = 1), premature discontinuation of study product (n = 6) and lost to follow-up (n = 1). The reasons for premature discontinuation of formula were as follows: Parent reported AE (n = 1), Investigator reported AE (n = 1), Parent requested discontinuation for reason other than AE (n = 2), Non-compliance (n = 1) and Lost to follow-up (n = 1). The 36 PE subjects, 22 male and 14 female, with gestational age of 38.6 ± 0.2 weeks, were 33.2 ± 2.8 days of age at enrollment, with a mean birth weight of 3262.5 ± 101.6 g. Other subject demographics  were also collected  data. Thirty-six (76.6%) of the ITT subjects were included in the protocol evaluable (PE) cohort. Eleven (23.4%) failed one or more evaluability criteria, including consumption of non-study feeding for more than 5 days (cted see .p = 0.0078). In addition, 78%  of the infants maintained their weight for age z-scores exceeding the hypothesized percentage of 70%. The evolution of weight for age z-score throughout the study is included in Weight z-scores of infants showed a statistically significant improvement from day 1 to SDAY 60  was ranked by parents on a scale of 1 to 5 . MRSC at day 7, 30 and 60 was 2.41 ± 0.11, 2.55 ± 0.12, 2.47 ± 0.12, respectively. The predominant stool consistency was between loose/mushy to soft. The predominant stool color was brown.The average volume of study formula intake per day was 754 ± 36 mL/day at SDAY 1–7, 850 ± 44 mL/day at SDAY 28–30 and 935 ± 44 mL/day at SDAY 58–60. A mean of 27.5 ± 4.4, 29.0 ± 4.8, 32.8 ± 5.0 percent of feedings had associated spit-up/vomit at SDAY 1–7, SDAY 28–30 and SDAY 58–60, respectively. Infants had a mean of 7.9 ± 0.2 study formula feedings per day at SDAY 1–7, 7.6 ± 0.2 at SDAY 28–30 and 7.1 ± 0.2 at SDAY 58–60.n = 2), constipation (n = 6), blood in stool (n = 1), vomiting (n = 4), spit-up/gagging/reflux (n = 17), fussiness (n = 10) and rash or eczema (n = 7).At enrollment, even though the infants were currently consuming an extensively hydrolyzed formula they had the following persisting symptoms: diarrhea  demonstrated no issues with tolerance in the open feeding portion of the study [Extensively hydrolyzed formulas are commonly used in infants with persistent intolerance symptoms, and in infants with suspected or documented cow’s milk allergy or protein sensitivity. Clinical experiences with infant formula supplementation with 2′-FL has found it to be safe, well-tolerated and support growth. The study formula is presently not available in the US, but a very similar formulation of the eHF with added 2′-FL is available in international markets. A recent clinical study assessing hypoallergenicity of an extensively hydrolyzed whey-based formula with 2′-FL and lacto-he study . In addihe study ,16.Our results are in agreement with other studies which reported normal growth patterns in healthy infants consuming eHF and adequate tolerance in infants with suspected food protein allergy or intolerance ,18. The Tolerance measures such as MRSC, stool color, average volume of formula intake and percent of feedings associated with spit-up/vomit after 1 hr of feeding per day were comparable to other eHF feeding studies that did not contain 2′-FL. Interestingly, it also demonstrated parent reported improvement in symptoms in infants that were already on an eHF formula. A limitation of this study is the length of time the infants were consuming an eHF without 2′-FL before starting the study formula. Additional clinical research may reveal additional beneficial effects of 2′-FL in the allergic population.Adverse events (AEs) were observed in 15 (32%) infants in the study (ITT cohort). Most AEs were mild in severity and deemed by the investigators as not related to product. The most common reported AEs were seborrheic dermatitis (five infants), gastrointestinal reflux disease (three infants) and infantile spit-up (two infants).The results of this study demonstrate that eHF formula with added 2′-FL was well accepted enabling adequate volume to demonstrate a statistically significant improvement of weight for age z-scores. The formula was safe and well tolerated and consumption of the formula over 60 days showed improvement and resolution of persistent symptoms.


Here, we extract data from 2,242 publications that report global change manipulative experiments and build a comprehensive global database with 5,213 pairs of samples for plant production  and ecosystem carbon exchange (gross and net ecosystem productivity as well as ecosystem and soil respiration). Information on climate characteristics and vegetation types of experimental sites as well as experimental facilities and manipulation magnitudes subjected to manipulative experiments are also included in this database. This global database can facilitate the estimation of response and sensitivity of key terrestrial carbon-cycling variables under future global change scenarios, and improve the robust projection of global change‒terrestrial carbon feedbacks imposed by Earth System Models.Numerous ecosystem manipulative experiments have been conducted since 1970/80 s to elucidate responses of terrestrial carbon cycling to the changing atmospheric composition (CO Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12932843 Global land temperature has warmed by 0.87 °C over the last 136 years (1880–2015)3. However, precipitation trends are more equivocal, with an increase in the northern mid-latitudes whereas trends in other regions cannot be confidently assessed1. A consistent manifestation of ongoing climate change is the increasing number of warm days and heavy rainfall events5. Because plants are subject to regionally different co-limitations by CO2, temperature, and the availability of nitrogen and water6, global change drivers including elevated CO2, atmospheric nitrogen deposition, warming, and changing precipitation regimes can result in complex and likely regionally different effects on ecosystem carbon-cycling variables such as plant production and ecosystem carbon exchange.As a consequence of fossil fuel combustion and food production, atmospheric CO7. In the original version, only data collected from the last year when multiple measurements were taken at different years in a study have been used. This updated version releases all year’s data we collected and thus adds an additional 2,717 pairs of samples. The 12 new publications added in this updated version are from the experiments collected in the original version and do not increase the sample size19.Over the last five decades, numerous manipulative experiments have been conducted worldwide and aimed to explore the ecosystem effects of global change drivers. However, the discrepancy and diversity of observations among different ecosystem manipulative experiments have led to a great uncertainty in assessing global change‒carbon cycling feedbacks. Here, we presented a database of 5,213 pairs  of carbon-cycling variable samples extracted from 2,242 publications that reported results of global change manipulative experiments (GCMEs) over the past four decades (1973–2016). This is an updated version of a previous database  that was originally used to examine global response patterns of terrestrial ecosystem carbon cycling to single and two combined global change drivers2 enrichment and warming experiments as well as the magnitudes of experimental manipulations were also presented and accompanied with the related experimental data. Furthermore, the references for each pair of samples were added into each dataset to simplify the use and review in the future study. In summary, this database can facilitate the understanding of terrestrial ecosystem carbon cycling to multifactorial global change, and provide empirical data for Earth System Models to reduce the uncertainties in projecting global change‒terrestrial carbon feedbacks.Besides data from single- and two-factor manipulative experiments, data obtained from the few three- and four-factor experiments are critical to improve the understanding of terrestrial carbon-cycling responses under future global change scenarios. Thus, we also included data extracted from publications that reported three- and four-factor experiments in this updated version. Moreover, the facilities used in CO7. In brief, 10 databases in Web of Science  including BIOSIS Previews, Chinese Science Citation Database, Data Citation Index, Derwent Innovations Index, Inspec, KCI-Korean Journal Database, MEDLINE, Russian Science Citation Index, SciELO Citation Index, and WoS Core Collection were used for searching peer-reviewed publications that reported GCMEs. The 18 keywords for WoS title search were: global change, climate change, free-air carbon dioxide enrichment, free-air CO2 enrichment, elevated carbon dioxide, elevated CO2, elevated atmospheric CO2, CO2 enrichment, eCO2, [CO2], warming, elevated temperature, changing precipitation, increased precipitation, decreased precipitation, nitrogen deposition, nitrogen addition, and nitrogen application. Through these search, 310,177 publication records that might be relevant to our topic were found.The detailed methods of publication search and data collection were described in our related work2).Publications reported results of outdoor GCMEs which had at least three control and global change treatment plots , above- and below-ground NPP (ANPP and BNPP), total biomass, aboveground biomass (AGB), root biomass, litter mass, gross and net ecosystem productivity (GEP and NEP), and ecosystem and soil respiration (ER and SR). Data of mean values, standard deviations or standard errors, and sample sizes (number of plot replications) of these variables in the control and treatment  groups were extracted from each publication when possible. The figures were digitized using SigmaScan Pro 5.0  and the numerical values were extracted when a publication presented experimental data graphically. Data of the experiments that were conducted over less than one year/growing season were excluded in this database. However, we included short-term data from tundra studies because most of measurements in this ecosystem were performed during July-August. Overall, 5,213 pairs  of plant production and ecosystem carbon exchange samples were collected in this database, having 2,247, 2,120, 81, and 765 pairs from single-, two-, three-, and four-factor manipulative experiments, respectively  based on the site coordinate. The dataset selection in CMIP5 was “historical (simulation of recent past 1850–2005)” and the climate data averaged from 20 21, that contained historical climate data, out of the 35 global climate models available in CMIP5 were used in this study. In addition, we downloaded data of climate means at global 1 × 1° land grid cells from Princeton University (http://hydrology.princeton.edu/data/pgf/v3/) to construct global climate space. Moreover, we classified ecosystems subjected to ecosystem manipulative experiments into five typical types: forests (mature forests and tree seedlings), grasslands , tundra, wetlands , and deserts.Information on the locations and altitudes of each experimental site, site climate including mean annual temperature (MAT) and precipitation (MAP) as well as wetness index 2 enrichment and warming facilities were also extracted from the related publications reporting CO2 and warming effects on plant production and ecosystem carbon exchange. Facilities used in elevated CO2 experiments included greenhouse, open-top chamber, free-air CO2 enrichment, and tunnels. Warming experiments primarily used greenhouse, open-top chamber, soil heating cables, infrared radiator, and infrared reflector to elevate vegetation canopy and soil temperature. In addition, the manipulation magnitudes of global change drivers imposed by manipulative experiments, such as the increases in CO2 concentrations (ppm) and temperature (°C), the changes in precipitation amount (mm), and the rates of nitrogen input (g N m−2 yr−1), were also collected and added into this updated database.Information on CO22. Raw data of ecosystem carbon-cycling variables and auxiliary materials are available as .csv/.txt files including (1) _Abbreviation_.csv, (2) NPP_Dataset.csv (291 pairs of samples), (3) ANPP_Dataset.csv (457 pairs of samples), (4) BNPP_Dataset.csv (399 pairs of samples), (5) Total Biomass_Dataset.csv (312 pairs of samples), (6) AGB_Dataset.csv (993 pairs of samples), (7) Root Biomass_Dataset.csv (543 pairs of samples), (8) Litter Mass_Dataset.csv (264 pairs of samples), (9) GEP_Dataset.csv (380 pairs of samples), (10) NEP_Dataset.csv (411 pairs of samples), (11) ER_Dataset.csv (387 pairs of samples), (12) SR_Dataset.csv (776 pairs of samples), and (13) List of 2,242 publications that reported GCMEs.txt. Each of the 11 datasets contained information on coordinate, altitude, climate, and vegetation type of experimental sites as well as experimental facility and manipulation magnitude of experimental treatments, and sample pairs of data extracted from publications reporting single-, two-, three-, or four-factor GCMEs.This database was categorized by ecosystem carbon-cycling variables. All datasets were released in figshare7 and this updated version. For example, first, several senior authors checked if the extracted data were consistent with the figures or tables in the related publications. Second, whether data extracted from the different studies were from the same experiment were checked. In this updated version, the author team carefully checked all datasets and other related information  again. Given that this updated database will be made publicly available with all data and metadata, further quality checks could be made towards continuing improvement.The author team made a series of quality assurance and quality control checks for the raw data in the original version−2 yr−1) are 182–3,519 with a median of 615 , 30–5,385 with a median of 299 , and 42–3,675 with a median of 224 , respectively, in the control plots 23. In addition, a global meta-analysis has found that mean NPP are 1,088 ± 111 and 772 ± 93 g m−2 yr−1 for monoculture plantations and tropical secondary forests, respectively, younger than 18 years old as well as 969 ± 154 and 573 ± 65 g m−2 yr−1 for monoculture plantations and tropical secondary forests, respectively, 18 years and older24. Another work25 has showed that NPP of the Canadian Arctic tundra is generally below 1,000 g m−2 yr−1. Flombaum and Sala (2007)26 has estimated ANPP of the Patagonian steppe and yielded a mean ANPP of 57 g m−2 yr−1. However, a grassland biomass dynamic assessment has revealed that mean grassland ANPP and BNPP worldwide are 331 ± 101 and 745 ± 346 g m−2 yr−1, respectively27.In this updated database, the ranges of NPP, ANPP, and BNPP values 28 and a subtropical forest in Southern China 29. In terms of ANPP, the four values ranging from 2,209 to 3,383 g m−2 yr−1 and the two values greater than 5,000 g m−2 yr−1 were from four northern hardwood forests in Michigan, USA30 and a northern forest in Northern Maine, USA31, respectively. In addition, the eight BNPP values ranging from 2,325 to 3,675 g m−2 yr−1 were extracted from a study conducted in a ponderosa pine forest in California, USA32. We confirmed that all the anomalously high values of plant productivity were extracted from the related publications correctly.Given the substantially greater upper limits of plant productivity values in our database than that in several previous works−2 , 308 g m−2 , 388 g m−2 , and 95 g m−2 , respectively. The ranges of total biomass values in our study are comparable to the estimates  of total biomass of terrestrial biomes in several previous studies35. In addition, several previous AGB assessments36 have found that the ranges of AGB of terrestrial biomes are 0–137,800 g m−2. The substantially smaller AGB ranges in our database may be due primarily to the fact that our dataset of AGB has few data obtained from studies conducted in tropical forests7. Moreover, a study37 estimating forest root biomass has demonstrated that root biomass of terrestrial biomes ranges from 1,181 to 4,651 g m−2. Furthermore, a recent plant biomass database has showed that ecosystem-level root biomass and litter mass across all terrestrial biomes are ranging from 0.01 to 1,085 g m−2 and from 8 to 224 g m−2, respectively35.Data of plant biomass and litter mass are highly variable Fig. . The med37. We found that the northern hardwood forests in Michigan, USA and a Florida scrub-oak forest on the east coast of Florida, USA had great root biomass densities of 5,318 and 6,522 g m−2, respectively39. In addition, two alpine meadows showed greater root biomass densities 41 than those in forests. In terms of litter mass, two values greater than 3,000 g m−2 were obtained from a northern forest in Northern Marine, USA 31 and an Arctic tundra in Swedish Lapland 42.We further checked and confirmed our data in the datasets of root biomass and litter mass which contained some anomalously high values than that reported in two previous databases−2 s−1) are 0.02–17.47 , ‒0.06–7.67 , 0.04–9.80 , and 0.03–9.33 , respectively, in the control plots. In this study, positive and negative NEP values represent net carbon uptake and loss, respectively.Data of ecosystem carbon exchange are relatively uniform Fig. . The ran


NR3C1 glucocorticoid receptor (GR) gene is a component of the stress response system, which can be regulated by epigenetic mechanisms. NR3C1 methylation has been associated with trauma and mental issues, including depression, post-traumatic stress, anxiety, and personality disorders. Previous studies have reported that stressful events are involved in NR3C1 gene methylation, suggesting that its regulation under environmental effects is complex. The present study aimed to analyze associations involving stressors such as socioeconomic status, health conditions, and lifestyle in relation to NR3C1 methylation in adults. This study included 386 individual users of the Brazilian Public Unified Health System (SUS), and evaluated socioeconomic and health conditions, body mass index, cortisol levels, and lifestyle. Data were correlated with NR3C1 methylation, determined using DNA pyrosequencing. The results showed that alcohol consumption, overweight, and high cortisol levels were related to NR3C1 demethylation, while depression was related to its methylation. Habits, lifestyle, and health status may influence NR3C1 gene regulation via methylation, revealing the complexity of environmental impacts on NR3C1 methylation.The  It has been recently described as the "modus operandi" of environmental adaptation, and in rapid responses to exposure events, which can be passed on to future generations2. Imprinting patterns are inherited and preserved during cell division; however, extrinsic or environmental factors contribute to epigenetic changes during an individual's life5. Therefore, stressful events can result in the addition or withdrawal of epigenetic marks at specific DNA locations, resulting in altered gene expression8.DNA methylation is a widely known mechanism involved in regulating gene expression10. Increased cortisol levels have been previously related to stress and methylation13. Furthermore, other stressful events or conditions, including trauma14, early life stress17, depression19, nutritional alterations22, psychosocial stress23, and consumption of substances such as alcohol and tobacco25, can alter GR gene encoding methylation levels.Stress events in humans or animal models have been related to epigenetic changes in specific regulatory regions of the glucocorticoid receptor (GR) gene encoding, which has the function of regulating hypothalamic stress on the neuroendocrine hypothalamic–pituitary–adrenal (HPA) axis, via cortisol production26, while human studies have evaluated blood methylation events by their homology observed in different tissues with equivalent expression16.Animal studies have evaluated methylation events directly in the hypothalamusNR3C1 gene, located on chromosome 5q31–q32, with approximately 140,000 base pairs29. This gene is composed of 17 exons, eight coding exons (numbered 2–9), and nine non-coding exons, which are located in the gene promoter30. The NR3C1 promoter region contains multiple methylation-sensitive cytosine-phosphate-guanine (CpG) dinucleotide repeats32, among these, the 1F region containing 47 CpG sites34.The GR belongs to the ligand-dependent nuclear receptor transcription factor superfamily and, in humans, it is encoded by the NR3C1 promoter methylation is responsible for different GR protein levels in various tissues36, such as the heart, kidney, lung, liver, skin, and especially the hippocampus42. Although it is not expressed in T-cells, it is expressed in B-cells and dendritic cells, homologous to the hippocampus; therefore, it can be evaluated in blood under conditions involving HPA axis changes43.NR3C1 promoter methylation may indicate lower mRNA levels and GR expression44. Thus, even high levels of peripheral cortisol are unable to bind to the cognate receptor to act as an HPA axis negative feedback mechanism, which could result in abnormal responses to stress44. On the contrary, since stress factors are associated with epigenetic changes, we hypothesized that social and behavioral factors may be associated with NR3C1 gene methylation.NR3C1 promoter methylation, especially in broader and multifactorial systems. Thus, the present study aimed to analyze associations involving stressor factors such as socioeconomic status, health conditions, and lifestyle in relation to NR3C1 gene methylation in adult individuals.It is still unclear what different conditions might alter Universidade Federal do Espírito Santo Health Sciences Center (CEP/CCS/UFES), under number 1,574,160, dated 6/6/2016. Individuals participating in the study signed written informed consent forms (ICFs). All methods were carried out in accordance with the Ethics Committee of Research with Humans.This was a cross-sectional study carried out with users of the Brazilian Public Unified Health System (SUS) in a southeastern municipality (Alegre-ES), and was conducted between March 2017 and November 2018. The study population was composed of individuals living in urban and rural areas, and was approved by The Ethics Committee in Research with Humans of the 45. Marital status, age, working conditions, and education  were also analyzed.This study was made up of a convenient sample of 386 individuals aged between 20 and 59 years who were users of the Brazilian Primary Health Care Units. Based on individual SUS registration forms, data were collected through individual interviews that evaluated socioeconomic, health, and lifestyle conditions. Low-income was defined as a per capita income/day less than US$5 (5 American dollars)46.To assess habits and lifestyle features such as alcohol and tobacco consumption, in addition to leisure and physical activity, a structural questionnaire was applied based on the Research Directorate Work Coordination and Income Questionnaire for residents of households from the National Health Survey (NHS)In this evaluation, the possible responses to alcohol and tobacco consumption were: (1) currently consuming, (2) used in the past, (3) never used, and for statistical analysis, responses were dichotomized into current consumption: no/yes. In addition, regarding leisure and physical activity, the possible answers for their activity were: (1) weekly, (2) biweekly, (3) monthly, and (4) not performed, dichotomized into yes/no activity.In the same questionnaire, we addressed self-perceived health status in which the possible answers were: (1) very good, (2) good, (3) regular, (4) bad, (5) very bad, and were dichotomized into: good or very good/regular or poor health for statistical modeling.47. Values were categorized according to Gomes-Oliveira et al.48 considering normal or mild mood disorders (BDI-II < 17), and symptoms suggestive of depression (BDI-II ≥ 17).Symptoms suggestive of depression were assessed using the Beck Depression Inventory-II (BDI-II)49, which collects information for directing public policies of the Brazilian Unified Health System (SUS). Information such as weight and height were collected, and from the obtained data, body mass index (BMI) was calculated and classified according to the World Health Organization50.Anthropometric assessment was carried out by qualified professionals using the Food and Nutrition Surveillance System (SISVAN)For analysis of cortisol and vitamin D levels and DNA methylation, 10 mL of peripheral blood was collected from patients by venipuncture after fasting for at least 8 h as instructed by community health agents (CHA). In a tube containing ethylenediaminetetraacetic acid (EDTA) anticoagulant, 3 mL of the sample was transferred for molecular analysis, and 2 mL into a tube containing NaF (sodium fluoride) anticoagulant for vitamin D analysis. The remaining blood was transferred to a tube without anticoagulant but containing a separating gel to obtain serum to determine cortisol levels. The tube contents were homogenized by inversion 5–8 times, and stored in refrigerated coolers over the range of − 2 to 8 °C. Blood samples for biochemical evaluation of cortisol and vitamin D levels were transported to Hermes Pardini Laboratory, Belo Horizonte, MG, while samples for DNA extraction were transported to the Biotechnology Laboratory, at the Center for Exact, Natural and Health Sciences, at the Federal University of Espírito Santo (CCENS/UFES).17. Results were classified as follows: low cortisol: < 6.7 μg/dL; Normal CORTISOL: 6.7–22.6 μg/dL; high cortisol: serum levels > 22.6 μg/dL. At the data analysis stage, the variable was dichotomized into high cortisol (≥ 6.7 μg/dL) and not high cortisol (< 6.7 μg/dL). Vitamin D levels were classified as deficiency: < 20 ng/mL, insufficiency: 20–29 ng/mL, and sufficiency: ≥ 30 ng/mL, and for statistical evaluation, these scores were dichotomized into insufficiency: < 30 ng/mL, and sufficiency: ≥ 30 ng/mL51.Cortisol levels and vitamin D abundance were quantified by chemiluminescence, with reference values for morning cortisol levels of 6.7–22.6 μg/dL52. A NanoDrop 2000/2000c Spectrophotometer was used to verify DNA quality and concentration for further NR3C1 methylation analysis.DNA extraction was performed as described by Salazar et al.Of all samples with good DNA quality and concentration, a subsample of 285 patients was randomly assigned to undergo pyrosequencing methylation assays.Qiagen, Valencia, CA, USA), following the manufacturer’s recommendations. Pyrosequencing methylation assays were performed as previously described54.Sodium-bisulfite conversion of 1 μg of DNA was performed using the EpiTect Bisulfite Kit (Uniscience). Pyrosequencing was performed using a PSQ 96 ID Pyrosequencer  with PyroMark Gold Q96 Reagent Kit (Qiagen), according to the manufacturer's protocol. All pyrosequencing conditions are listed in Table PCR product quality was checked on 2% agarose gels using GelRed  were inserted into the multivariate Poisson regression model with robust variance. The backward method was used, and those variables with less significance  were removed one by one from the model. The procedure was repeated until all variables present in the model were statistically significant (p < 0.05). The Hosmer–Lemeshow test was used to verify the fit of the final model. The prevalence ratio (PR) with 95% confidence interval (95% CI) was used as an effect measure. For all analyses, a significance level of 5% was adopted. Statistical analyses were performed using SPSS software (v.13.0 for Windows) and Stata v.11.0.NR3C1 1F region; 198 individuals did not show any percentage of methylation detected, whereas 87 exhibited measurable percentages of methylation. The median methylation level was 0.0 (0.0–12.9%). Table Our results were obtained from a total of 285 individuals evaluated by pyrosequencing of the The average methylation index was calculated from CpG sites methylation percentages. These percentages were dichotomized into unmethylated (0% methylation) and methylated .Bivariate Poisson regression showed associations between methylation profiles and gender (p = 0.047), alcohol consumption (p < 0.001), depression (p = 0.022), body index (p = 0.017), and cortisol levels (p < 0.001) Table .Table 3BFrom variables in the Bivariate Poisson regression with values p < 0.20, the multivariate model was designed. The results showed that methylation is associated with alcohol consumption, depression, BMI, and high cortisol levels Table .Table 4M–5. In contrast, depression exhibited the opposite effect, being directly related to methylation with prevalence of 55% higher than non-depressed individuals .As observed in Table 2 = 0.0759 and, after adjustment by Hosmer and Lemeshow, showed good adherence (p = 0.99).The final model was statistically significant (p < 0.001), presenting a pseudo rNR3C1 gene methylation, such as socioeconomic aspects, health, and lifestyle.This study presents individuals with low income, low education, and predominantly of female gender. Our goal was to establish a broader assessment of factors related to NR3C1 non-methylation, while depression is related to its methylation. Argentieri et al.16 presented a series of studies that related hyper- or hypomethylation with specific CpG methylation of this gene.We have shown that alcohol consumption, overweight, and high cortisol levels are related to NR3C1 methylation. Gatta et al.24 reported hypermethylation of NR3C1 exon 1H in the prefrontal cortex of individuals with alcohol abuse disorders compared with that in a control group. However, our data showed low levels of NR3C1 1F region methylation. Corroborating our findings, Dogan et al.25 showed a relationship between alcohol consumption and decreased levels of NR3C1 methylation in a 64-patient cohort.Few studies have evaluated the relationship between methylation patterns and alcohol consumption. It was expected that alcohol as a stressor factor could stimulate the HPA axis by increasing cortisol levels and 56. Here, we showed association between alcohol consumption and NR3C1 methylation, which indicated that alcohol-mediated modulation of the HPA axis may occur through epigenetic changes.Studies have demonstrated that alcohol consumption may lead to HPA axis alterations, with glucocorticoid release modificationsNR3C1 methylation, our finding is relevant because alcohol represents a large fraction of the drugs consumed by the world population, and the epigenetic effects induced by its consumption are still little known.Although self-reporting of alcohol consumption was insufficient to control its effects on NR3C1 40–47 1F CpGs sites. Other authors have associated methylation alterations in the 1F region CpG 36–39 sites with depressive status in adolescents57 and in CpGs 36–44 on maternal exposure to gestational stress and depression in children58.Our analysis showed an association between suggestive symptoms of depression, as evaluated by Beck scores ≥ 17, with increased methylation at 59. There are also studies addressing the 1F region showing hypomethylation of CpGs 35–39 in individuals with depression19. However, the present study provides new information that individuals with depressive symptoms, and frequent use of the public health system, exhibit methylation of the NR3C1 1F region.In addition, other authors have studied the 1F region, showing hypomethylation involving CpGs 35–47, with hypomethylation specifically of CpG 43 associated with depressionNR3C1 methylation is associated with depression, in that NR3C1 gene methylation may indicate lower mRNA levels and GR expression, leading to imbalanced HPA axis modulation, which could result in abnormal responses to stress, and increase susceptibility to depression33,44.In this manner, it is possible that NR3C1 gene methylation in maternal and postnatal gestational exposure to childhood stress60.In our study, only 8 individuals presented high cortisol levels, while the others had normal or low levels, but which may not be representative.Furthermore, high cortisol levels were associated with non-methylation, but with a very low prevalence ratio Table . High le61. Excess weight is also related to chronic inflammation through NFκB pathways; however, no association between overweight and methylation status has been previously reported for the NR3C1 gene62. It is possible that hypomethylation of this region may be related to low-grade inflammation, a feature of the overweight state63.On the contrary, multivariate analysis of risk factors showed that being overweight is associated with non-methylation, with a prevalence ratio of 0.67, indicating that being overweight reduces the prevalence of methylation by 33%. Chronic stress has previously been related to increased cortisol levels, leading to weight gainNR3C1 non-methylation, whereas depression was related to methylation.Although it was a cross-sectional study, and it is not possible to establish any causal relationships, this study is relevant as it revealed a direct or inverse association between methylation, alcohol consumption, overweight, and high cortisol levels related to NR3C1 gene regulation via methylation. Relationships involving genotype, environment, and phenotypic outcomes may be more refined than previously thought, depending on specific stressful events that can result in unique clinical consequences.Thus, we suggest that habits, lifestyle, and health status may influence


Ca. Planktophila” (acI-A), “Ca. Nanopelagicus” (acI-B), and “Ca. Fonsibacter” (LD12). Due to high abundance, these genera might have a significant influence on nutrient cycling in freshwaters worldwide, and this study adds a layer of understanding to how seemingly competing clades of bacteria can coexist by having different cooperation strategies. Our synthesis ties together network and ecological theory with empirical evidence and lays out a framework for how the functioning of populations within complex microbial communities can be studied.This study examines evolutionary and ecological relationships of three of the most ubiquitous and abundant freshwater bacterial genera: “ Candidatus Planktophila” (acI-A) and “Candidatus Nanopelagicus” (acI-B) and the proteobacterial genus “Candidatus Fonsibacter” (LD12). While “Ca. Planktophila” and “Ca. Fonsibacter” had no correlation in their natural habitat, they have the potential to be complementary in laboratory settings. We also investigated the bifunctional catalase-peroxidase enzyme KatG (a common good which “Ca. Planktophila” is dependent upon) and its most likely providers in the lake. Further, we found that while ecotype and community cooperation combined may explain “Ca. Planktophila” population abundance, the success of “Ca. Nanopelagicus” and “Ca. Fonsibacter” is better explained as a community by-product. Ecotype differentiation of “Ca. Fonsibacter” as a means of escaping predation was supported but not for overcoming auxotrophies.While fastidious microbes can be abundant and ubiquitous in their natural communities, many fail to grow axenically in laboratories due to auxotrophies or other dependencies. To overcome auxotrophies, these microbes rely on their surrounding cohort. A cohort may consist of kin (ecotypes) or more distantly related organisms (community) with the cooperation being reciprocal or nonreciprocal and expensive (Black Queen hypothesis) or costless (by-product). These metabolic partnerships (whether at single species population or community level) enable dominance by and coexistence of these lineages in nature. Here we examine the relevance of these cooperation models to explain the abundance and ubiquity of the dominant fastidious bacterioplankton of a dimictic mesotrophic freshwater lake. Using both culture-dependent (dilution mixed cultures) and culture-independent  methods, we independently identified the primary cohorts of actinobacterial genera “IMPORTANCE This study examines evolutionary and ecological relationships of three of the most ubiquitous and abundant freshwater bacterial genera: “Ca. Planktophila” (acI-A), “Ca. Nanopelagicus” (acI-B), and “Ca. Fonsibacter” (LD12). Due to high abundance, these genera might have a significant influence on nutrient cycling in freshwaters worldwide, and this study adds a layer of understanding to how seemingly competing clades of bacteria can coexist by having different cooperation strategies. Our synthesis ties together network and ecological theory with empirical evidence and lays out a framework for how the functioning of populations within complex microbial communities can be studied. The stable coexistence of species is described by a continuum of interspecific symbiotic interactions from parasitism through neutralism to mutualism . The extCandidatus Fonsibacter”  to identify which pairs were significantly different; r ≥ 0.3) with cloud- or wedge-shaped distributions  of “ibacter”  were ovetophila” . Common Ca. Fonsibacter” 1° cohort network revealed a difference between the core group “Ca. Fonsibacter” and a phylotype representing a basal clade of this genus. The two groups were subsequently examined separately. The “Ca. Planktophila” 1° cohort also revealed a division between phylotypes of the “A6 tribe” and the others, as they had negative correlation to the other “Ca. Planktophila.” This suggests that the “acI-A6 tribe” plays a different ecological role than the other clades in Lake Erken and/or may need to compete with the more dominant “Ca. Planktophila vernalis” of the acI-A7 clade, its closest relative.The “r = 0.58, adjusted P value [Padj] = 0; There was a positive moderately strong correlation between the relative abundance of OTUs in the time series and relative abundance in cultures (Pearsons 10.1128/mSystems.00316-20.4TABLE S2r) of OTU abundance and prevalence (percentage of samples) in time-series (TS) and mixed-cultures (MC), P values were BH adjusted for multiple testing. Download Table S2, PDF file, 0.03 MB.Pearson correlations . While “acIV” was abundant and ubiquitous in the time series  and ° cohort . HoweverNanopelagicales were the most abundant clade in Lake Erken  and were negatively correlated with percent O2  (ke Erken  and werene acI-c . Nanopel< 0.001) .Ca. Planktophila” phylotypes was detected in the mixed cultures. The time series 1° cohort of “Ca. Planktophila” included other Actinobacteria, Armatimonadetes, Chloroflexi, Gemmatimonadetes, Alpha- and Betaproteobacteria, and Verrucomicrobia, while in the mixed cultures only Actinobacteria, Bacteroidetes, and Alpha- and Betaproteobacteria coexisted  correlations than the other genera tested. Unlike the other genera, “Ca. Planktophila” had no correlations (positive or negative) with phytoplankton in its 1° cohort , while in the mixed cultures there was a subset of these phyla with the addition of one gammaproteobacterial phylotype  ranging from 18% to 72% completeness, 27 “Ca. Planktophila” MAGs between 15% and 85% complete, and three “Ca. Fonsibacter” MAGs with completeness between 18% and 27% . Analysis of (single) gene content and complementarities across such incomplete genomes was judged pointless. We therefore investigated the presence of the katG gene in all Lake Erken metagenome contigs to reduce false-negative results caused by insufficient MAG recovery. We also examined the katG gene neighborhood, including synteny among the Nanopelagicales, as well as the homology and topology of its translated product, KatG, with translated sequences from both public data sets and our metagenomes to look for evidence on how it may affect differences in culturability among the Nanopelagicales.After years of culture efforts by multiple groups, the successful maintenance of axenic re media . Kim et re media  also seqCa. Planktophila rubra” KatG and other members of acI-A1 to A3 and “Ca. Nanopelagicus” (acI-B) MAGs, we designated the actinobacterial group  KatG had highest sequence identity with the assayed low-activity KatG from “Ca. Planktophila rubra”  which was located within a putative DNA repair region (Ca. Planktophila limnetica” (acI-A3), “Ca. Planktophila vernalis” (acI-A7), “Ca. Planktophila lacus” (acI-A4), and “Ca. Nanopelagicus limnes” (acI-B1) all have the repair cassette without katG. Lake Erken metagenomic actinobacterial group katG sequences were recovered matching “Ca. Planktophila dulcis,” “Ca. Planktophila limnetica,” and “Ca. Planktophila versatilis” , unnamed clades acI-A5 and A6, and “Ca. Planktophila vernalis” (acI-A7). No anomalous folds or residues, at least compared to the highly functioning Synechococcus version of the gene, were detected by alignment or modeling. These katG genes were all found near a tRNA , Gammaproteobacteria (Acinetobacter), Verrucomicrobia (“Candidatus Xiphinematobacter” and Cerasicoccaceae), Betaproteobacteria   .Actinobacteria [Ca. Fonsibacter” ) is the base for the initial synthesis pathway to 5-aminolevulinate, an added cost will be either three genes  or one gene (330 aa), respectively. From 5-aminolevulinate to protoheme and placement in KatG is a further seven steps by six or seven different gene products adding at least another 4,800 aa to the cost -long protein but also must include the cost for heme. Depending on whether glutamate (common in bacteria ) or glycthe cost –38. The he cost –. All non present .Ca. Planktophila” had positive correlations  together likely contribute significantly to B-vitamin production in Lake Erken.The individual (meta)genomic contributions of the betaproteobacterial lineage designated Burkholderiales-MWH-UniP1 and Ca. Nanopelagicus” dependencies are similar to those of “Ca. Fonsibacter,” except that the former could be a provider of common goods vitamins B3 and B9, while the latter could be a provider of vitamins B1 and B2, heme, and KatG. “Ca. Fonsibacter” dependencies are easily met by any of its positively correlated 1° cohort, though the strongest evidence suggests that all of its auxotrophies (except B12) could be met by the negatively correlated Stramenopiles. Synechococcus spp. are known to secrete B12  prevalence in the time series and mixed cultures supports that its occurrence in the cultures may be attributed to being present in the inocula and that the filtered lake water media were able to meet an important proportion of its metabolic needs. Conversely, the lack of correlation in either relative abundance or prevalence for the Nanopelagicales genera  in the time series compared to cultures means that there is not support for their detection being merely due to high abundance in the inocula. We infer that the other phylotypes were bigger contributors to their growth. It should be noted that negative correlations are not detectable in the mixed cultures, as the absence of a phylotype could be stochastic rather than a result of competitive exclusion. Moreover, competition that prevents growth in a given culture cannot be identified.The strong correlation between “Nanopelagicales in Lake Erken were likely more competitive in colder, darker, and oxygen-depleted waters. While Nanopelagicales have been associated with oxygen-saturated waters in some locations  event. The retention of a low-functioning KatG could be due to the criticality of the repair cassette whereby only lineages where katG is excised without disturbing the surrounding region will survive, or to the other (putative) functions of KatG, including as a detoxifier of formate and methanol. Future research assaying “actinobacterial group” KatGs for activity with other low-molecular-weight (LMW) molecules such as formate would be informative. While “Ca. Planktophila vernalis” in Lake Erken is likely katG+, questions remain as to the functionality of even these KatGs, as no heme synthesis pathways have been recorded for any Nanopelagicales, and without the heme ligand, there would be no catalytic function. Future work assaying “group B” KatGs and also showing evidence of hemophore secretion or membrane heme receptor binding would clarify this issue. It is likely that “Ca. Planktophila” and “Ca. Nanopelagicus limnes” from Lake Erken rely on Fimbriimonas, Polynucleobacter, Synechococcus, and “Ca. Fonsibacter,” while “Ca. Planktophila limnetica” and “Ca. Nanopelagicus limnes” in culture relied on a combination of Flavobacterium andAcinetobacter to detoxify environmental peroxide. This fits within the community cooperation model.Of the seven la” spp. . It is tp.  and the community detritus model. A discussion on where to draw the theoretical line for  BQH at a single gene , interconnected pathway , or associated systems  could be fruitful in light of the ubiquity and abundance of streamlined genomes in aquatic environments.The higher culturability of “ average , and celCa. Fonsibacter” is highly abundant in Lake Erken in the late summer-early autumn immediately after an algal bloom, i.e., the “clear water” phase of the lake’s cycle  and cellular membrane qualities (grazing)  versus coculture would clarify their relationships.Earlier short-term studies found that “’s cycle . Howevergrazing) , 49. Thegrazing) , 24, 50,totrophs . In LakeNanopelagicales have anabolic community cooperation and community detritus with reliance on detoxifying community cooperation as the main structuring factors. “Ca. Fonsibacter” likely escape predation via ecotype cooperation, while broadly relying on community detritus for anabolic deficits.The combination of network and other correlation analyses with review of published genomes and metagenome dependency confirmation supports that most a, suspended particulate organic matter, silicate, water color, and absorbance at 420 nm measurements. Water samples for genomic analysis were collected by gentle vacuum filtration onto 0.2-μm membrane filters . Filters were individually stored in Eppendorf tubes and transported back to the Uppsala University laboratory where they were stored at −80°C until further processing.Time series water samples were obtained from dimictic Lake Erken  in central Sweden at monthly to weekly intervals spanning a period from February 2007 to November 2015. Samples for genomic and chemical analyses were taken from the 20-m water column at 1-m intervals from the deepest point of the lake . SamplesDNA was extracted from filters using MoBio UltraClean soil DNA extraction kits  per the manufacturer’s instructions. The V3-V4 region of the 16S rRNA gene was amplified using the S-d-Bact-0341-b-S-17  forward primer and S-d-Bact-0785-b-A-21  reverse primer . Templat6 cells/ml) was used as a source of cells for inoculation of mixed cultures. This untreated lake water was diluted in 1 liter of the triple sterilized lake water (approximately 10 cells/ml). Ninety-eight 1-ml cultures were placed in sterile 50-ml Falcon tubes to allow oxygenation and incubated for 2 months under 12-h light-dark cycles at 11°C to replicate the lake conditions at the time of collection. The V3-V4 region of the 16S rRNA gene was amplified using the S-d-Bact-0341-b-S-17  forward primer and the S-d-Bact-0785-b-A-21  reverse primer (Water as both a source of growth media and culturable cells was collected from the epilimnion of Lake Erken on 8 March 2016 from the marked sample point . Dilutioe primer . One michttps://github.com/jstjohn/SeqPrep.git) (de novo and reference-based methods. Both GreenGenes (v105 13-8) and SILVA (v128) reference data sets were used (de novo sequences) to allow for differences in DNA processing and sequencing across the three data sets. Sequences from the negative control were removed from the entire data set. Samples with potential human microbiome contamination were identified and discarded from the data set due to potential effect on community metabolism. Sequences identified as eukaryotic  or archaeal were deliberately retained despite the primers not specifically being selected to amplify such sequences, as they were considered critical in the mixed-culture analyses from a community metabolism perspective. Samples were normalized using Qiimes single rarefaction to an even depth of 1,500 reads per sample for the time series and 500 reads for the mixed-culture samples. These normalized OTU tables were then used for all downstream analyses.Demultiplexed MiSeq time series and mixed-culture data, and 454 Ti time series data obtained from Lake Erken in 2008 , were prrep.git)  with defrep.git) , with deere used , 57. Seqpost hoc with the Kruskal-Wallis multiple comparison (KWmc) using the kruskal.mc test of the pgirmess package v1.6.4  false discovery rate using the psyche package v1.6.12 corr.test function and Pearsons moment r reported. Parameters with weak to moderate correlation (r >|0.3|) were plotted in R to observe monotonicity.Statistical analyses were done using R v3.3.1  in the Re v1.6.4 . Environneff (inverse Simpsons) above an average of 10 and the use of multiple methods  and pval.sparccboot scripts (two-sided test). Pearson correlations were performed using the corr.test of the psyche package using the optional P values adjustment for multiple testing of Benjamini, Hochberg, and Yekutieli false discovery rate. SPIEC-EASI correlations were analyzed using the spiec.easi package with parameters method = “mb,” sel.criterion = “stars,” lambda.min.ratio = 1e−2, nlambda = 20, and 50 repetitions. Singletons were removed from the normalized mixed-culture OTU table prior to network analysis. The reduced OTU table was analyzed with Pearsons correlation, SpiecEasi  and their 1° cohorts were extracted from the two initial networks and visualized separately. The layouts for the networks were “edge-weighted spring-embedded” with edge weights calculated from the average of the correlations. Some nodes (OTUs) were moved to the side of overlapping nodes for clarity or away from an edge if it appeared to pass through an unconnected node. Correlations between Nanopelagicales OTU and “Ca. Fonsibacter” OTU detection in the time series versus the mixed cultures were investigated by Pearson correlation of their relative abundance (log av.ra), prevalence (percent samples or cultures detected in), and relative abundance versus prevalence to determine whether detection in culture was correlated with occurrence in the lake.Correlations between OTUs in the time series and mixed cultures were retained if the correlation coefficient was greater than 0.3 absolute for Pearsons, SparCC, or Dice-Sørensen or if detected at all by SPIEC-EASI. Time series and culture networks consisting of OTU connections detected by at least two correlation methods were visualized in Cytoscape. All further statistical analyses of the networks were performed in Cytoscape except for assortativity analyses which were done in R using the igraph v1.1.2 package nominal assortativity function. Subnetworks of the identified dominant genera  2x125bp at SciLifeLab Stockholm.https://github.com/broadinstitute/picard.git). Mixed-assembly contigs were binned into putative MAGs with metabat2 v2.12.1 . NeNanopelagicales, cyanophycin. Taxa representative of either a group or closest individual genome to 1° cohort phylotypes were collated via the following NCBI taxon identifiers (IDs): Cerasicoccaceae txid2026784, Chitinophagaceae txid563835, Comamonadaceae txid80864, Comamonadaceae Acidovorax txid12916, Cytophagaceae txid2026784, Fimbriimonas txid661478, Flavobacterium txid237, Fluviicola txid2597671, Gemmatimonas txid1379270, Limnohabitans txid665874, Oxalobacteraceae (B-prot-Burkh) txid75682, Polynucleobacter txid556054, Polynucleobacter acidiphobus txid556053, Ralstonia txid48736, Roseomonas txid125216, Sediminibacterium txid1086393, Sphingomonadaceae txid41297, Stramenopiles (diatom) txid296543, Synechococcus txid1129 and txid32046, and “Ca. Xiphinematobacter” txid1704307. For actinobacterial genomes available only from IMG, the taxa were acIV acAcidi 2654587759 and 2739367537 and 2737471702 and 2737471663, actinobacterium acI-A6 SCGC AAA028-I14 2619618809, Actinomycetales actinobacterium SCGC AAA027-F04 2606217193, and actinobacterium SCGC AAA028-N15 2619618810. No genetic information was available for “Streptophyta” so a text-based reference search was conducted. No genetic information was available from the proposed Chloroflexi class Roseiflexales. Genes considered indicative or essential in a synthesis pathway were examined by search word against the taxon ID in NCBI or if in IMG then via KEGG pathway tools and BLAST. Pathways with NCBI search terms in parentheses and EC numbers used to retrieve sequences from UniProt UniRef database  “thiazole synthase” EC 2.8.1.10, riboflavin (B2) “6,7-dimethyl-8-ribityllumazine synthase” EC 2.5.1.78, niacin (B3) “nicotinate-nucleotide diphosphorylase” EC 2.4.2.19, pantothenic acid (B5) “pantoate beta-alanine ligase” EC 6.3.2.1, pyridoxal (B6) synthesis “Pyridoxamine 5′-phosphate oxidase” EC 1.4.3.5, B6 salvage “Pyridoxamine kinase” EC 2.7.1.35, biotin (B7) “Dethiobiotin synthase” EC 6.3.3.3 and “8-amino-7-oxononanoate synthase” EC 2.3.1.47, folate (B9) “Dihydrofolate reductase” EC 1.5.1.3, cobalamin (B12) “*cobyric acid synthase” EC 6.3.5.10 cobQ/cbiP, “precorrin-6A” CobF EC 2.1.1.152, and “Cobalt-precorrin-5B C(1)-methyltransferase” CbiD EC 2.1.1.195, porphyrin (heme) “Porphobilinogen deaminase” and “hydroxymethylbilane synthase” EC 2.5.1.61. Representative sequences from bacterial and archaeal domains were obtained from UniProt nr90 for each gene using the listed EC numbers, and short fragments and metagenome sequences were removed. Annotated sequences from the Lake Erken metagenomes were downloaded from IMG using the KEGG pathway function and clustered at 95%, and sequences shorter than 100 aa discarded using CD-HIT  under accession numbers ERS1884053 to ERS1884254. Mixed-culture sequences are available from ENA PRJEB35605. 454 data used in the time series are available at SRA under accession number SRR097418 (https://trace.ncbi.nlm.nih.gov/Traces/sra/?run=SRR097418)  with Taxon Object IDs 3300020141, 3300020151, 3300020159, 3300020160, 3300020161, 3300020162, 3300020172, and 3300020205. Rscripts used for correlation and network analyses are available from https://github.com/rmondav/publications.Time series MiSeq sequences were deposited in ENA (R097418) . HiSeq m


Limited research has evaluated the performance of physical education (PE) teachers. This study aimed to use person-environment fit and organizational support to evaluate PE teachers’ work performance using multilevel analysis. The relationship between person-environment fit and performance of university physical education teachers (at the person-level) and a cross-level effect on performance of university physical education teachers of perceived organizational support (at the school-level) and a moderator effect of organizational support were examined. A total of 447 PE teachers recruited from 55 universities in Taiwan were invited to participate in this survey, with a return rate of 65.74%. Using hierarchical linear modeling, the study found that person-job fit, person-organization fit, and person-supervisor fit at individual level have positive impacts on the performance of university PE teachers. As for cross-level effect, organizational support has positive impacts on the performance of university physical education teachers. However, organizational support at school level had no significant moderating effects on the relationship between person-environment fit and the performance of university physical education teachers. The implications of the findings for both university PE teachers and administrators and suggestions for future research are discussed. Today, the scarce resource for a company is no longer money. It is human ability. Despite the fact that businesses have placed considerable attention to work performance evaluation, it not until 1990 that performance evaluation began to receive proper attention, especially in the field of sports. Performance evaluation has been practiced mostly in professional settings, and some examples include performance evaluation of sports coaches , professEarly empirical studies on university PE teachers’ job performance have put much emphasis on performance evaluation. Very few have discussed factors that affect their job performance. Knowing the crucial factors affecting workers’ performance would provide useful information to assist workers and human resources to increase productivity and performance.Speaking of work performance-related factors, the environment employees surrounded is an important factor which may affect their performance. Person-environment fit (P-E fit) is one among the factors related to work performance. P-E fit is defined as the degree to which individual and environmental characteristics match . Based oAnother important factor related to work performance is organizational support. According to Eisenberger, Huntington, Hutchison, and Sowa , perceivThus, this study first aims at exploring the relationship between university PE teachers’ job performance and four dimensions  of P-E fit. Furthermore, this study will conduct a cross-level analysis to explore the impacts of the group level‘s (or school level’s) organizational support on university PE teachers’ job performance. Last but not least, this study also explores whether perceived organizational support has a moderating effect on the relationship between P-E fit and university PE teachers’ job performance.This section will review the literature of the abovementioned items and postulate hypotheses accordingly. First, we will start to examine relationships of the four dimensions of person-environment fit and performance. Second, we will examine previous studies related to organizational support and work performance. Third, we will examine the moderating effects of organizational support on the relationship of persona-environment fit to performance based on previous studies and then we will combine the theories and studies and present the research framework.Previous studies have indicated that person-environment fit (P-E fit) is an outcome of people-environment interaction. A good fit creates good behavior ,12,19. AA good match of individual skill to the job requirement is typically a decisive factor in finding a right job candidate, as this match directly affects employee and organization performance . Afsar, Hypothesis H1-1.Person-job fit will have a positive impact on university PE Teacher performance.Person-group fit (P-G) is the fit of degree between the individual and the work team they belong to . Group iFor heterogeneous studies, a work team of a group of people with various skills and experience is more effective at work . By contHypothesis H1-2.Person-group fit will have a positive impact on university PE Teacher performance.Chatman  defined Gregory, Albritton, and Osmonbekov  conducteHypothesis H1-3.Person-organization fit will have a positive impact on university PE Teacher performance.Person-supervisor fit (P-S fit), refers to the similarity between individual and supervisor personality dimensions, values, and goals . P-S fitAccording to self-categorization theory, individuals have a tendency to interact with people with similar traits and make a sense of group during socialization . When suHypothesis H1-4.Person- Supervisor Fit will have a positive impact on university PE Teacher performance.Eisenberger, Huntington, Hutchison, and Sowa  stated tSun  reportedHypothesis H2.Organizational Support will have a positive impact on university PE Teacher performance.In addition to the abovementioned study findings, organizational support as a variable is found to have direct positive influence on employees’ positive behaviors. Organizational support was also considered as a moderator variable in several studies ,44. OrgaAccording to Erdogan and Enders , organizHowever, no research has been done to explore the mediating effect of organizational support on the relationship between person-environment fit and job performance. Based on prior inferences, the present study considers organizational support as an upper-level variable, and investigates the mediating effect of organizational support on the relationship between person-environment fit and job performance. Accordingly, four hypotheses were developed as follows.Hypothesis H3-1.Organizational Support will have a positive moderating effect on person-job fit and university PE Teacher performance.Hypothesis H3-2.Organizational Support will have a positive moderating effect on person-group fit and university PE Teacher performance.Hypothesis H3-3.Organizational Support will have a positive moderating effect on person-organization fit and university PE Teacher performance.Hypothesis H3-4.Organizational Support will have a positive moderating effect on person-supervisor fit and university PE Teacher performance.Model depiction of the study hypotheses based on previous inferences are presented on The research participants were physical education teachers from 55 comprehensive universities and technical universities with at least 10 or more PE teachers. In order to have high response rate, the researcher asked one PE teacher from each university to conduct the survey. The assigned PE teacher explained the study purpose to the participants and obtained their consent before actually distributing the survey questionnaires to the participants. The assigned PE teacher left while the participants were filling out the survey. The study was reviewed and approved by National Cheng Kung University’s Institutional Review Board. Cluster sampling was used for data collection. A total of 680 survey questionnaires were sent to PE teachers from 55 universities. A total of 447 questionnaires from 55 universities were collected for data analysis, with a valid response rate of 65.74%.Some research participants took not only teaching roles but also administrative responsibilities. It was noted that 166 (37.1%) participants had to take care of administrative work while 281 (62.9%) did not. In terms of work title, 83 participants (18.6%) were instructors, 139 (31.1%) were assistant professors, 160 (35.8%) were associate professors, and 65 (14.5%) were professors or distinguished professors. Out of 447 PE teachers, 172 (38.5%) were teaching in public universities while 275 (61.5%) were teaching in private ones. There were 25 participants (5.6%) with 5-year teaching experience or less, 51 (11.4%) with 6−10 years of experience, 142 (31.8%) with 11−20 years of experience, and 229 (51.2%) with 21-year teaching experience or more. Sixty-eight participants (15.2%) were not married, and 379 (84.8%) were married.The four scales used for data analysis are presented along with demographic information below.Person-environment fit scale was a modified version of Chuang and Lin  and HuanFour questions were asked in each individual group. One of the PJFS questions reads, “Your personality traits match those required by the job.” The PGFS sample question reads, “Your emphasis on your work value match your group members’ (not including your supervisor’s).” The POFS asks “Your organization’s culture matches your personal work value”.The total variance explained by the four factors in the factor analysis was found to be 78.58%, with factor loading for each item falling between 0.58 and 0.87. The internal consistency showed that Cronbach alpha of 0.83 for PJFS, 0.88 for PGFS 0.93 for PSFS, and 0.95 for POFS. In addition, achieved Cronbach alpha of 0.94 confirmed high internal consistent reliability for this person-environment fit survey questionnaire.The results from confirmatory analysis show that all measurements fit the requirement of reliability and validity .χ2 = 48.74, df =11, χ2/df = 4.43, CFI = 0.99, GFI = 0.97, NFI = 0.98, IFI = 0.99, RMSEA = 0.09).The study used the university PE teacher performance scale created by Chang, Lin, Chia, and Yang . The scaχ2 = 27.19, df = 7, χ2/df = 3.88, CFI = 0.99, GFI = 0.98, NFI = 0.99, IFI = 0.99, RMSEA = 0.08).Based on the suggestion of Eisenberger, Stinglhamer, Vandenberghe, Sucharski, and Rhoades , and ShaPrevious studies on PE teacher performance found that position and teaching experience have significant influence on self-efficacy and job involvement . MarriagStatistical analysis was performed using SPSS 20.0 for Windows and HLM 7.0. Given the significance level of 0.05, the hypothesis testing was conducted using descriptive statistics, Pearson correlation, and hierarchical liner modeling (HLM).wg index is a measure of interrater agreement, and is typically used to determine the appropriateness of aggregating data to higher levels of analysis. A 0.70 criterion is commonly used. Rwg values equal to or greater than 0.70 demonstrate high consistency within groups and justify the aggregation within the group. In addition, Bliese [wg for organizational support was 0.76 . Each value was greater than 0.70, indicating that data combined from organizational support at an individual level can be aggregated to school levels of analysis.Klein, Dansereau, and Hall  proposed, Bliese  suggeste, Bliese , the ICCDescriptive statistics of individual-level variable and school-level variable and variable analysis (means score and standard deviation) are presented in Nine hypotheses are developed throughout the study and tested using HLM. The results are as follows:2 = 173.93, df = 54, p < 0.001), and ICC (1) is 0.215, indicating that school difference accounts for 21.5% of the total variance of PE teacher performance. As a result, HLM was employed in null model analysis and the level-1 and level-2 models are expressed in the following:A cross-level analysis was conducted to explore the impact of variables at individual level and at school level on university PE teacher performance. Chi-square test in the null model presented in Level-1 Modelij=βj0 + ijrPE teacher performance Level-2 Modelβj0=γ00 + uj0The level-1 and level-2 models of the HLM analysis are shown in the following:Level-1 Modelij = βj0 + βj1*(school typeij) + βj2*(Genderij) + βj3*(ijRANKING) + βj4*(Educationij) + βj5*(Administrative workij) + βj6*(Teaching experienceij) + βj7*(Marriageij) + βj8*(Person-Job Fit ij) + βj9*(Person-Group Fit ij) + βj10*(Person-Supervisor Fit ij) + βj11*(Person-Organization Fit ij) + ijrPE teacher performanceLevel-2 Modelβj0 = γ00 + γ01* + uj0βj1 = γ10βj2 = γ20βj3 = γ30βj4 = γ40βj5 = γ50βj6 = γ60βj7 = γ70βj8 = γ80 + γ81*βj9 = γ90 + γ91*βj10 = γ100 + γ101*βj11 = γ110 + γ111*Notice that in order to perform HLM analysis, school type, person-job fit, person-group fit, person-organization fit, and person-supervisor fit have been centered around the group mean and organizational support has been centered around the grand mean.γ20= 0.11, t = 3.32, p < 0.05) had positive significant impacts on performance, indicating that higher position results in better performance. Education  also had positive significant impacts on performance, meaning that PE teachers who have higher levels of education have higher performance.γ80= 0.13, t = 2.57, p < 0.05) positively affects teacher performance, indicating that the higher the P-J fit level, the better the teacher performance. Similar results were found with P-S fit  and P-O fit , suggesting that higher fit perceptions lead to better teacher performance. All results are shown in Concerning the impacts of P-J fit, P-G fit, P-S fit and P-O fit of university PE teachers on their performance at an individual level, the research showed that P-J fit . Teachers who received strong organizational support across various universities were more likely to have better performance. However, the moderating effect of organizational support at the school level on the relationship between P-E fit and university PE teacher performance was not found to exist. The results are presented in The cross-level analysis showed that organization support at school level has positive impacts on PE teacher performance at individual level  which also support the findings of Byrne and Hochwarter [Perceived organizational support is considered to be a resource capable of positively influencing performance by reducing stressors and encouraging commitment. According to the cross-level analysis, our study showed that organizational support had significant impacts on PE teachers’ performance  on the relationship between person-environment fit and performance. This may come without surprise since PE in oriental society is not treated with due respect. In oriental society, parents most care about children’s academic achievements, leading to deprivation of PE courses, and sometimes the courses are replaced by some academic-related subjects, leaving the PE teachers in an embarrassing situation. In particular, many of them do have well-trained skills but are not very active in engaging in academic production, and hence lack organizational support. They deserve organizations’ attention and support.There has been very little research on university PE teacher performance, let alone studies that analyze what might affect teacher performance. This current study aims to investigate the impact of P-E fit on university PE teacher performance, and four dimensions of P-E fit were all included. Data analysis with 447 PE teachers from 55 universities in Taiwan indicated that P-J fit, P-S fit, and P-O fit all had a significant positive impact on PE teacher performance. The research results also suggest that the fit of skill, value, and characteristics between an individual and organization can be an important factor affecting university PE teacher performance.Furthermore, when recruiting new PE teachers, universities should pay extra attention to whether the candidate’s professional skills and knowledge are a good match for the teaching job. Candidate’s perceptions about value and culture are to be considered, too. If candidates and organizations share the same values, candidates are more likely to stay, or quit otherwise . SimilarThe present study also investigated school-level organizational support and conducted a cross-level analysis. The findings show that organizational support positively and significantly affect university PE teacher performance; nevertheless, the moderating effect of organizational support on the relationship between P-E fit and PE teacher performance was not found.Unlike early studies that conducted analysis only at the individual level , in ordeThe findings indicate that consistency of PE teachers’ personal skills to job requirements has to be ensured in order to enhance university PE teacher performance. This consistency is especially important in Taiwan, as under Taiwan’s education system it is not easy to get rid of incompetent teachers. Prior to official recruitment, several things to consider include: the candidate’s role and responsibilities in the university and respective department, personal skills, work behaviors and attitudes, and personal values, goals and cultures. While it is important to assess a candidate’s personal qualities, it is even more important to put emphasis on matching individuals to organization’s culture, value, and goals. A good fit between organizational characteristics and individual focus has an impact on teachers’ involvement and retention. Since PE teachers in Taiwan universities typically have a close work relationship with their supervisors, it is important for supervisors to become charismatic leaders and create a work culture to improve PE teachers’ job performance.In Taiwan universities, the work content of PE teachers typically includes teaching, research, and counseling service and administrative work. It should be noted that teachers from western countries may have different areas of responsibilities, and assessment tools are constructed using different indicators; and thus, this research conclusion should be applied with caution. It is also argued that factors that affect teachers’ performance can have a different degree of impact. For instance, P-S fit perhaps has greater impacts on administrative work and student counseling services, but less impact on research performance. Therefore, it is recommended that future study can be conducted to separately analyze teaching performance, research performance, and administration and student counseling services. This approach may especially work better with universities that categorize teachers based on their areas of expertise, and should help future research better identify factors that have impacts on teaching performance and research performance. Recent research on the impacts of an innovative teaching environment on innovative teaching performance is a good example of this approach.Our results show that the three dimension of P-E fit  had positive significant impacts on university PE teachers’ performance. The cross-level analysis found organizational support had direct positive impacts on performance but there was no significant moderating (enhancing) effect on the relationship of the P-E fit to performance. Among seven individual-level control variables , position and teaching experience were reported to have a significant positive impact on teacher performance.