Lactobacillus caseiShirota intervention modulates the esophageal microbiome composition in Barrett’s esophagus

Lactobacillus casei Shirota intervention modulates the esophageal microbiome composition in Barrett’s esophagus | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Lactobacillus casei Shirota intervention modulates the esophageal microbiome composition in Barrett’s esophagus Yonne Peters , Laura Ferrando , Chengliang Zhou , Rene te Morsche , Britt van der Leeden , Renske Cremers , Phuc Dat Le , Leander van Dijk , Ruud WM Schrauwen , Adriaan C Tan , Rachel S. van der Post , Peter van Baarlen , Peter D. Siersema , View ORCID Profile Annemarie Boleij doi: https://doi.org/10.1101/2025.05.12.25327438 Yonne Peters 1 Department of Gastroenterology and Hepatology , Radboudumc, Nijmegen, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Laura Ferrando 2 Host-Microbe Interactomics, Wageningen University and Research , Wageningen, The Netherlands 3 Istituto di Ricerca Genetica e Biomedica (IRGB) , Cagliari, Italy Find this author on Google Scholar Find this author on PubMed Search for this author on this site Chengliang Zhou 4 Department of Pathology , Radboudumc, Nijmegen, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Rene te Morsche 1 Department of Gastroenterology and Hepatology , Radboudumc, Nijmegen, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Britt van der Leeden 1 Department of Gastroenterology and Hepatology , Radboudumc, Nijmegen, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Renske Cremers 4 Department of Pathology , Radboudumc, Nijmegen, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Phuc Dat Le 4 Department of Pathology , Radboudumc, Nijmegen, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Leander van Dijk 1 Department of Gastroenterology and Hepatology , Radboudumc, Nijmegen, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ruud WM Schrauwen 5 Department of Gastroenterology and Hepatology , Bernhoven Hospital, Uden, the Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Adriaan C Tan 6 Department of Gastroenterology and Hepatology, Canisius Wilhelmina Hospital , Nijmegen, the Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Rachel S. van der Post 4 Department of Pathology , Radboudumc, Nijmegen, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Peter van Baarlen 2 Host-Microbe Interactomics, Wageningen University and Research , Wageningen, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Peter D. Siersema 1 Department of Gastroenterology and Hepatology , Radboudumc, Nijmegen, The Netherlands 7 Department of Gastroenterology and Hepatology, Erasmus MC University Medical Center , Rotterdam, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Annemarie Boleij 4 Department of Pathology , Radboudumc, Nijmegen, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Annemarie Boleij For correspondence: Annemarie.Boleij{at}radboudumc.nl Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract Objective Esophageal adenocarcinoma (EAC) and its precursor, Barrett’s esophagus (BE), are associated with a pro-inflammatory, Gram-negative-dominated esophageal microbiome. We investigated whether Lactobacillus casei Shirota (LcS) consumption could shift the microbiome towards a more Gram-positive profile in BE patients. Design In a single-arm intervention study, 23 BE patients used LcS twice daily for 4 weeks. Endoscopic biopsies from normal squamous epithelium (NSE) and metaplastic columnar epithelium (MCE), both before and after LcS-intervention were analyzed using 16S rRNA gene sequencing for microbiome composition, digital droplet PCR for Gram-positive to negative ratio, and fluorescence in situ hybridization to visualize Eubacteria and Firmicutes. Results LcS intervention increased Gram-positive Firmicutes in MCE in situ (p<0.01) while the overall abundance of Eubacteria was unaffected. Analysis at DNA level showed an increased Gram-positive to Gram-negative ratio post-LcS. The abundance of Gram-negative Proteobacteria lowered from 74% pre-LcS to 52% post-LcS, while the abundance of Gram-positive Firmicutes, including the genus Lactobacillus , increased from 20% pre-LcS to 31% post-LcS. Overall microbiota diversity significantly increased post-LcS (p=9.9778e-07). LcS intervention also resulted in an increased abundance in the BE associated taxa Prevotella and Haemophilus in both NSE as MCE. Conclusion LcS consumption significantly altered esophageal microbiome composition in BE patients, increasing Gram-positive taxa and overall diversity. These findings underscore the potential of probiotic-based therapeutic strategies aimed at EAC prevention. The concurrent rise in BE-associated taxa warrants careful consideration and further personalized studies to maximize benefits and minimize unintended consequences for optimal outcomes in BE patients. What is already known on this subject? Epidemiological studies point to esophageal microbiota as a risk factor for BE. Gram-positive bacteria are closely associated with the normal distal esophagus, while Gram-negative bacteria ( Veillonella, Prevotella, Haemophilus, Neisseria , and Fusobacterium ) are increased in BE and EAC. LcS has been shown to have potent anti-tumor & anti-metastatic effects on colon and gastric cancer cells and to suppress chemically-induced carcinogenesis in animals. What are the new findings? The microbiota of both normal squamous epithelium and post-LcS samples show a higher microbiota diversity, indicating greater richness and evenness in the distal esophagus after LcS intervention. LcS intervention led, at the phylum level, to a significant increase in the relative abundance of health-associated, Gram-positive Firmicutes, increasing from 22% to 32% (*** p ≤ 0.005). Gram-negative Proteobacteria showed a reduction from 72.0% to 54% (*** p ≤ 0.005). Although LcS intervention led to an increase in Gram-positive Firmicutes, including Lactobacillus , it also resulted, in both normal squamous epithelium and metaplastic columnar epithelium, in an increased abundance of bacterial taxa associated with BE and EAC, including the genera Prevotella and Haemophilus . How might it impact on clinical practice in the foreseeable future? Our results suggest that the esophageal bacterial composition in BE patients can be modified by consumption of dairy products containing probiotics. Manipulation of microbiota aimed at altering microbiota composition to include higher abundances of health-associated Gram-positive taxa may provide a novel way for disease prevention and therapeutic intervention. Introduction The incidence of esophageal adenocarcinoma (EAC) has been rising rapidly in Western countries over the past few decades( 1 ). Because EAC is frequently detected at an advanced stage, patients with EAC have a dismal prognosis with a five-year survival rate of less than 20%( 2 ). The only known precursor of EAC is Barrett’s esophagus (BE), with BE patients having a 30-125 fold increased risk of developing EAC( 3 ). BE is characterized by the replacement of normal squamous epithelium (NSE) in the distal esophagus with metaplastic columnar epithelium (MCE). This metaplastic change is largely attributed to gastroesophageal reflux disease (GERD), affecting globally about 15-20% of the general population( 4 ), resulting in injury of the squamous esophageal mucosa. However, not all patients with severe GERD develop BE( 5 ). While GERD is the main risk factor for BE, BE pathogenesis is complex and multifactorial. There is increasing evidence that the esophageal microbiome differs in patients with and without BE and may play a role in BE and EAC development( 6 ). Once thought to be minimal, the esophageal microbiome is now recognized as having a diverse and stable bacterial population( 7 ). In healthy individuals, the esophagus is predominantly colonized by carbohydrate-degrading, short-chain fatty-acid (SCFA)-producing Gram-positive bacteria, especially taxa of the genus Streptococcus ( 8 – 10 ). In contrast, BE is characterized by an increase in the relative abundance (RA) of disease-associated Gram-negative bacteria( 3 , 4 )(taxa from the genera Fusobacterium , Veillonella , Prevotella, Haemophilus, Neisseria, and Campylobacter ( 11 )) and a decrease in Gram-positive bacteria, relative to healthy individuals. This shift in BE suggests that a link might exist between the ratio of Gram-positive to Gram-negative taxa, and EAC development ( 12 , 13 ). A hypothetical shift in Gram-positive to Gram-negative taxa ratio aligns well with the recently discovered competition model between two major bacterial groups or “guilds”, one guild of mainly Gram-positive bacterial taxa specialized in carbohydrate fermentation and production of the SCFA butyrate, and the other guild characterized by overrepresentation of mainly Gram-negative taxa associated with disease and antibiotic resistance, that distinguish human disease-from control cases( 14 ). The relative increased abundance of disease-associated, often Gram-negative taxa observed in GERD may thus contribute to the inflammatory environment associated with BE and potentially influence its progression to EAC. Probiotic administration has shown promise in modulating gut microbiome composition in gastrointestinal conditions. While research on probiotics in the context of BE is limited, studies in related conditions show interesting insights. For instance, probiotic consumption of Gram-positive taxa, such as members of carbohydrate-degrading and SCFA-producing genera Lactobacillus , Bifidobacterium and Streptococcus , may improve GERD symptoms( 15 ). Probiotics may help restore bacterial balance by increasing the abundance of Gram-positive species, potentially counteracting the shift towards Gram-negative, frequently disease-associated taxa, and thus, fitting the abovementioned “two-competing-guilds” model correlating with health or disease. In vitro studies using a BE model have demonstrated that probiotic consumption can be associated with substantially lower expression of key biomarkers associated with progression of BE to EAC. Of particular interest is Lactobacillus casei strain Shirota (LcS), frequently used in probiotic dairy products( 16 ), which has demonstrated potent anti-tumor, anti-metastatic, and anti-proliferative effects in various cancer models, including gastro-intestinal cancer( 17 – 20 ). Although the specific impact of probiotics on the esophageal microbiome in BE patients requires further investigation, these preliminary findings indicate potential for manipulation of esophageal microbiota composition to improve BE management and EAC prevention. We hypothesized that consumption of probiotic LcS by BE patients might result in an increase of Gram-positive taxa and a decrease of Gram-negative disease-associated taxa in the esophageal microbiome. To test this hypothesis, we invited BE patients undergoing surveillance endoscopies to consume a probiotic drink containing LcS twice daily for 4 weeks. The goal of our study was to measure and monitor changes in bacterial composition following LcS intervention in MCE and NSE of BE patients, to unravel potential implications in BE pathogenesis and propose novel EAC prevention strategies. Methods Study design We performed a single-arm, interventional pilot study to evaluate the ability of changing the esophageal microbiota by ingestion of a fermented milk drink containing LcS in patients with BE with confirmed MCE with intestinal metaplasia. We analyzed the microbial composition of biopsies obtained from NSE and BE regions (MCE) before and after use of LcS to identify potential alterations in mucosal microbiota composition. In addition, the ability of LcS to colonize the esophagus and its impact on the Gram-positive to Gram-negative ratio was investigated by DNA sequence profiling of bacteria and fluorescent in situ microscopy analysis of biopsy sections. The study was in accordance with the Declaration of Helsinki, the code of conduct for Health Research, and was approved by ethics committee CMO Arnhem Nijmegen (NL59072.091.16) and registered in the Netherlands Trial Register (NL-OMON43164). All the participants provided informed written consent. Participants Study participants who had been referred for a surveillance upper endoscopy for BE were recruited from two hospitals (Bernhoven Hospital, Uden, the Netherlands and Radboud university medical center, Nijmegen, the Netherlands). Individuals aged 18 years or older with a Barrett segment of at least 2 cm with histologically proven columnar-lined epithelium (metaplasia) without dysplasia, were eligible to participate. Exclusion criteria included probiotic or antibiotic use within the last 3 months before baseline, infection of the oral cavity, vegetarian or gluten-free diet, lactose intolerance, immunodeficiency disorders, bleeding disorders, Helicobacter pylori infection, previous gastric or esophageal surgery, and other coexistent esophageal diseases (e.g. varices or reflux esophagitis). Intervention Patients received a fermented probiotic drink (Yakult: 65ml; Yakult Nederland BV, Amstelveen, the Netherlands) containing a minimum of 6.5·10 9 colony-forming units (CFU) LcS/bottle twice-daily for four weeks. Other Yakult ingredients were water, skimmed milk powder, glucose/fructose syrup, sugar, maltodextrin, and flavorings. Fourteen fresh bottles of Yakult were delivered by a courier service to the participants’ home addresses every week. Patients were asked to be fasting 15 minutes before and after drinking the bottle. Compliance was assessed by a patient diary and registration of the remaining unopened bottles by the courier service. During the intervention period, patients were not allowed to take other probiotics or antibiotics. Patients receiving antibiotic therapy were excluded from the study. Sampling and analysis procedures The primary outcomes were (i) the effect of LcS on the Gram-positive to Gram-negative ratio in the esophagus, and (ii) the effect on the diversity and composition of the microbiota in NSE and MCE epithelium. Secondary outcomes were the impact of LcS on endoscopic and histologic inflammation. The additional methods concerning sampling procedures, tissue processing and scoring, quantitative PCRs, microbiota analysis and statistical analysis can be found in Supplemental methods in Supplemental files . Results Patient enrollment and baseline characteristics A total of 31 patients were enrolled and underwent baseline endoscopy. Of these, 25 patients who met inclusion criteria and had the necessary number of study biopsies taken started the 4-week Yakult intervention. Twenty-three patients completed the study, including the second endoscopy ( Figure 1 ). Baseline characteristics are shown in Table 1 . Analysis performed on patient samples are listed in Supplemental table S1. Most patients were male (73.9%), with a median age of 68 years (IQR 59–71). Median BE segment length was Circumferential (C) 2 cm and Maximum (M) 4 cm (IQR C0–5, M3–7). All patients were on acid suppression therapy with either proton pump inhibitors (PPIs) or H2 receptor antagonists. No patients reported reflux symptoms at baseline and endoscopic evaluation showed no signs of inflammation in any of the patients. Histopathological evaluation of clinical FFPE biopsies confirmed presence of MCE with intestinal metaplasia in the BE segment without dysplastic changes in all patients at baseline. Download figure Open in new tab Figure 1. Study population View this table: View inline View popup Download powerpoint Table 1. Patient characteristics Clinical evaluation Self-reported adherence to Yakult regimen was high, with 96% of patients reporting >90% compliance (1 diary missing). No serious adverse events were reported during the study period. Most common minor side effects were diarrhea (n=2) and mild bloating (n=1). Following the 4-week Yakult intervention, the second endoscopy revealed no significant changes in endoscopic features or clinical characteristics compared to baseline. The absence of initial reflux symptoms or endoscopic inflammation made it not possible to evaluate any potential improvements due to Yakult consumption. Histopathological evaluation and In situ detection of bacteria Histopathological evaluation of the endoscopically guided Methacarn fixed study biopsies, intended for microbial in situ bacterial evaluation, were scored for presence of MCE and inflammation. In 68% and 59% of BE segment study biopsies MCE with intestinal metaplasia was detected pre- and post-LcS intervention, respectively. Minimal or moderate chronic inflammation was observed in 63% and 47% of MCE biopsies pre- and post-LcS intervention, respectively (p>0.05; Table 1 ). Histologic inflammation was not observed in any of the NSE biopsies. We evaluated the in situ presence of Eubacteria, Gram-positive Firmicutes, and Gram-negative Bacteroidetes and Gammaproteobacteria using fluorescence microscopy. Representative images of histology, Fluorescent in situ hybridization (FISH) for Eubacteria and Firmicutes are shown in Figure 2 for MCE, with corresponding controls and NSE biopsies in Supplemental Figure S1 and S2 . No differences were observed in the number of Eubacteria signals per mm apical region in both MCE (median 2.19, and 2.93), and NSE biospies (median 1.35 and 0.96) pre- and post-LcS, respectively. A significant increase in Firmicutes signals post-LcS was observed per mm apical region for MCE biopsies (median 0.32 vs 1.67; ** p < 0,01 Wilcoxon Signed Rank test). A similar trend was observed in NSE biopsies, but this was not significant (median 0.4 vs 0.86) ( Supplemental Figure S3 ). The Gram-negative bacterial taxa Bacteroidetes and Gammaproteobacteria were detected in a minimal number of samples at low abundance pre- and post-LcS. Download figure Open in new tab Figure 2. FISH detection of bacteria in MCE biopsies pre- and post-LcS intervention. Representative H&E staining and corresponding FISH images of Eubacteria (cyan) and Firmicutes signals (green) detected in MCE biopsies of 1 case with high Eubacteria and Firmicutes presence pre-LcS intervention (A) and post LcS intervention (B) at 5x, 20x en 100x zoom. Nuclei are visible in magenta (DAPI stain). Gram-positive to Gram-negative ratio in MCE and NSE biopsies pre- and post LcS intervention Our working hypothesis was that the consumption of Gram-positive LcS probiotics would lead to an increase in the RA of Gram-positive taxa and a reduction in the RA of Gram-negative taxa. The Gram-positive to Gram-negative ratio measured with droplet digital PCR (ddPCR), a quantitative PCR method that counts DNA target copies in nanoliter-sized droplets, showed a higher RA of Gram-negative bacteria in both NSE and MCE regions pre-LcS ( Supplemental Figure S4A ). Post-LcS intervention, the Gram-positive to Gram-negative ratio increased from 0.42 to 1.02 (*** p ≤ 0.005) in NSE regions and 0.48 to 1.11 (P>0.05) in MCE regions, covering 90% and 75% of the pairs respectively ( Supplemental Figure S4B ). We were unable to confirm specific colonization of the esophagus by the LcS strain in neither NSE nor MCE biopsies after twice daily consumption. General characteristics of esophageal microbiota in BE-patients at baseline To assess whether the intake of LcS could alter esophageal microbiota of BE patients, we compared the microbial composition, alpha diversity and RA between MCE and NSE biopsies. At the phylum level, BE patients showed a high abundance of Gram-negative Proteobacteria (55.1%), followed by Gram-positive Firmicutes (23.5%), Actinobacteria (4.6%) and Bacteroidetes (3.5%). The remaining taxa included Fusobacteria, Epsilonproteobacteria, and Patescibacteria. Among the Proteobacteria, the most common genus was Mesorhizobium (32.1%), followed by Xanthobacteraceae (12.2%%) (specifically Bradyrhizobium ) and Sphingomonas (3.5%) ( Supplemental Figure S5A ). Other common taxa included members of the Gram-positive Firmicutes such as Streptococcus (16.6%) and Rothia (Actinomycetota) (3.0%) and less abundant taxa such as the Gram-positive genus Staphylococcus (2.7%), and the Gram-negative genera Prevotella and Reyranella (both around 2%) ( Supplemental Figure S5B ). The Shannon index, a standard measure of diversity that considers both the number of taxa and their proportional abundance, was significantly higher in NSE compared to MCE at the genus level ( p = 2.0e-06) ( Figure 3A ). To test the hypothesis that BE is associated with a higher RA of Gram-negative taxa, we compared the RA of the Gram-negative phylum Proteobacteria and the Gram-positive phylum Firmicutes between NSE and MCE biopsies. At the phylum level, no significant differences were observed between RA of Proteobacteria (NSE= 66.3% vs MCE= 62.8%) and Firmicutes (NSE=26.0% vs RA MCE=25.5%) in MCE vs NSE biopsies. In addition, we performed a partial-RDA analysis for tissue origin (MCE vs NSE) and corrected this for the covariates LcS-intervention and patients because these could at least partially explain variation in microbiota RA. The tissue origin MCE or NSE, contributed 25.5% to the total variation in bacterial RA ( p = 0.002), showing that the bacterial composition differed significantly between NSE and MCE of the esophagus ( Figure 3B ). The genera at highest differential RA in NSE included Staphylococcus , Chitinophaga , Reyranella , Hephaestia , Pseudolabrys , (RDA values 0.70-0.94). In contrast, the genera Rothia , Acinetobacter, Actinomyces, and Granulicatella , were at higher RA in MCE (RDA values −0.48 to −0.38; Figure 3C and 3D ). Download figure Open in new tab Figure 3. RDA and RA reveal the most discriminative genera in MCE vs NSE. A) Differences in the Shannon α-diversity index of microbial communities at genus level between esophageal locations (NSE and MCE) B ) Partial Redundancy analysis (RDA) of genera adjusted for patients and LcS-intervention of oesophagal region samples; the x-axis separates NSE from MCE and explains 25.5 % of the microbial composition differences observed; microbial community composition sampled from the two regions in the oesophagus was significantly different ( p = 0.002). The top 10 most discriminative genera are indicated with black arrows. The direction of arrows correlates with location, and arrow lengths with correlation strength. C ) The relative abundance (RA) of the most discriminative genera displayed as heatmap. D ) Boxplots show RA of the most discriminative genera. ** p ≤ 0.01, *** p ≤ 0.005 Multiple Linear Regression adjusted with Covariates: treatment and patients. Higher bacterial diversity in BE and squamous epithelium post-LcS intervention Next, we evaluated specific changes in microbial diversity comparing pre- and post-LcS biopsies from NSE and MCE regions. Administration of LcS increased bacterial richness in both NSE and MCE esophageal locations, with significant differences observed at the genus level ( p = 2.8e-05) ( Figure 4A , 4B , Supplemental Table S3 ). Multivariate PERMANOVA based on Bray–Curtis distances revealed distinct microbial communities at the genus level that occurred at significantly differential RAs between NSE and MCE ( p = 0.001) ( Figure 4C ), and between pre- and post-LcS ( Supplemental Table S4 ). Principal component analysis (PCA) corroborated these findings, showing that nearly 60% of the variation was captured by the first and second principal component (PC1&2) ( Supplemental Figure S6 ). Both the two esophageal regions (NSE vs MCE) and the intervention (pre- vs post-LcS) contributed statistically significant to the separation of microbiota (MCE vs NSE, p = 0.001; pre-LcS vs post-LcS, p = 0.001, Supplemental Table S3 ). The genera that contributed most to the differences in microbiota composition between NSE and MCE regions included Prevotella , Megasphaera , and Actinomyces , the principal discriminating genera in MCE. In contrast, bacteria belonging to the genera Staphylococcus , Reyranella , and Chitinophaga were more dominant in NSE ( Supplemental Figure S6 ). Download figure Open in new tab Figure 4. Differences in α-diversity and b-diversity of MCE vs NSE pre- and post-LcS intervention. Differences in the Shannon α-diversity index of microbial communities at genus level: A ) before and after administration of LcS (pre-LcS and post-LcS) B ) pre-LcS and post-LcS for each esophageal region. C ) Principal coordinate analysis (PCoA) visualizing differences in microbiota composition at genus level associated with sampled esophageal regions and pre- or post-LcS intervention sampling time points. PcoA was generated using Bray–Curtis distance at genus composition level. The experimental groups were distinct by esophageal tissue origin (NSE vs MCE) and for intervention (pre-vs post-LcS). LcS intervention increased specific Gram-positive taxa and reduced specific Gram-negative taxa The administration of LcS led to a significant increase in the RA of Gram-positive Firmicutes at the phylum level, showing an increase from 22% to 32% in both NSE and MCE biopsies (Tukey’s HSD: *** p ≤ 0.005, p<0.05, respectively). Gram-negative Proteobacteria showed a reduction from 72.0% to 54% (Tukey’s HSD:** p ≤ 0.01 for both NSE and MCE) ( Figure 5A ). Among Firmicutes, the RA of the genus Lactobacillus had increased from 0.01% to 0.03% (Tukey’s HSD: *** p ≤ 0.005 for MCE only) ( Figure 5B ). The significant increase in Firmicutes, and reduction in Proteobacteria was only observed in patients included at the Radboudumc hospital and not at the Bernhoven s i te (Supplemental Figure S7) . These findings corroborate the findings from the Gram-positive to Gram-negative ratio assessed with ddPCR and the in situ increased detection of Firmicutes post-LcS. Download figure Open in new tab Figure 5. RDA analysis and RA identify the most discriminative genera pre- and post LcS intervention. A ) The relative abundance (RA) of the phyla Firmicutes and Proteobacteria before and after LcS intervention. B) RA of the most discriminative genera Lactobacillus , Mesorhizobium in NSE and Klebsiella in MCE biopsies pre-versus post-LcS intervention C ) Partial-RDA of genera grouped for NSE and MCE toghether comparing pre-with post-LcStissue of origin (MCE vs NSE) and intervention (pre-vs post-LcS) separately. The RDA1 axis separates pre-LcS from post-LcS and explains 6.5 % of observed differences in bacterial composition. Bacterial community composition changed significantly due to intervention with LcS ( p = 0.002). The top 10 most distinctive genera are represented with black arrows. Arrow directions correlate with esophageal location, arrow lengths with correlation strength. D ) RA of the most discriminative genera displayed as heatmap. ( E ) Rank correlation analysis using Linear Discriminant Analysis (LDA) Effect Size (LEfSe) was performed to compare microbial features, candidate biomarkers, at genus level between esophageal regions (NSE and MCE) and ( F ) before and after intervention with LcS. Phylum with LEfSe scores >2.5 or <−2.5 and an FDR-corrected p < 0.05 were considered significant. ** p ≤ 0.01, *** p ≤ 0.005 Multiple Linear Regression adjusted with Covariates: esophageal regions and patients. The impact of LcS intervention on microbiota composition at the genus level was assessed using partial-RDA, adjusted for patients and tissue origin (MCE vs NSE phenotype; detailed Methods in supplement) ( Figures 5C and D ). Partial-RDA revealed that the intervention (LcS consumption) explained 7.5% variation in microbiota composition of the esophageal microbiota pre- and post-LcS intervention. Post-LcS intervention, genera that contributed strongest to differences in microbiota composition in the esophageal tissue origin included Lactobacillus , Rothia , Streptococcus , Veillonella , and Klebsiella ( Figures 5C and D ). The genera contributing most to the differential microbiota composition across the NSE and MCE regions was investigated. In the NSE region, LcS consumption led to a significant reduction in Gram-negative Mesorhizobium , from 41% to 25% (**** p ≤ 0.001) ( Figure 5B ). Although LcS intervention had led to a decrease in Gram-negative Proteobacteria, it also resulted in an increase in the taxa Prevotella and Haemophilus , in both the NSE and MCE regions. Members of the genus Klebsiella also showed a significant increase in MCE biopsies(**p<0.01), but remained at low RA ( Figure 5B , Supplemental Figure S7 ). Next, we employed Linear discriminant analysis Effect Size (LEfSe), specifically designed for biomarker discovery rather than multivariate analysis of RA, across sampling regions. LEfSe determines the taxa most likely to explain differences in microbiota composition between NSE and MCE by coupling standard tests for statistical significance with additional Linear Discriminant Analysis (LDA) tests, to improve biological consistency and impose a given effect size( 21 ). LEfSe was used to identify taxa associated with BE by comparing microbiota composition between NSE and MCE biopsies, as well as to identify (biomarker) taxa associated with impact of LcS consumption. LefSe analysis corroborated our previous findings, uncovering Firmicutes as a biomarker post-LcS intervention (LDA score= 4.66, p ≤ 0.005, Table S4 ). Members of the phyla Proteobacteria (Pseudomonadota) and Fusobacteria (Fusobacteriota) were listed as enriched candidate biomarkers pre-LcS intervention ( Supplemental Figure S6, Table S4 ). According to LEfSe analysis, members of the genera Staphylococcus , Reyranella , and Chitinophaga were biomarkers associated with NSE regions, while members of the genera Streptococcus, Rothia and Prevotella_7 were designated as post-LcS intervention biomarkers ( Figure 5E and F ). Discussion Our study highlights significant differences in bacterial composition of NSE and MCE in BE patients, accounting for 25.5% of the observed variation in bacterial composition. LcS use led to notable shifts in the esophageal microbiota composition, including increased microbial diversity in both epithelial regions and a significant increase in the Gram-positive/Gram-negative ratio. Specifically, we observed a marked increase in the RA of Gram-positive Firmicutes (from 22% to 32%) alongside a reduction in Gram-negative Proteobacteria (from 72% to 54%). While Lactobacillus abundance increased significantly post-LcS intervention, taxa previously associated with BE and EAC, such as Prevotella ( 22 ), also showed increased abundance in both epithelial regions. These findings suggest that although LcS modulates the esophageal microbiota toward a more diverse and potentially beneficial composition, undesired increases in RA of disease-associated taxa warrant further investigation into clinical significance. Our finding that within the same individual, esophageal squamous and metaplastic epithelium exhibit substantially different bacterial compositions underscores the importance of the local epithelial environment in shaping the esophageal microbiome. Higher bacterial diversity, especially of Gram-positive taxa, were features of healthy esophageal squamous epithelium, whereas Gram-negative bacteria appeared to be abundant in metaplastic epithelium. This observed shift from Gram-positive to Gram-negative predominance in BE is of clinical relevance. The outer membrane of Gram-negative bacteria possess lipopolysaccharide (LPS), potent inducers of inflammation, that may contribute to the metaplasia-dysplasia-carcinoma sequence observed in BE( 12 ). Furthermore, certain Gram-negative species found in BE, such as Campylobacter concisus , produce toxins that damage epithelial cells and potentially contribute to carcinogenesis ( 23 ) ( 24 ). More generally, progression from healthy normal squamous epithelium in the esophagus to BE-associated metaplastic columnar epithelium and subsequently to EAC is characterized by an increased RA of Gram-negative bacterial species ( 12 ) including disease-associated species from the genera Campylobacter and Fusobacterium ( 25 ) ( 26 ) ( 27 ). Conversely, Gram-positive bacteria, particularly certain Streptococcus and Lactobacillus species, of which we assayed the strain L. casei Shirota, may play protective roles in esophagus through production of bacteriocins, short-chain fatty acids (SCFAs) from the breakdown of complex carbohydrates, and competition with pathogenic species ( 7 ). The SCFAs lactate and acetate modulate immune response and host tolerance, and contribute to competitive capacity of Gram-positive bacteria against pathogenic, often Gram-negative, microorganisms ( 28 ) ( 29 ). These contrasting ecological properties of Gram-negative and Gram-positive taxa align with the recently discovered model of two competing guilds, one mainly containing Gram-negative taxa that include common disease-associated species and lineages, and another one containing Gram-positive taxa associated with anaerobic fermentation, butyrate production and health ( 14 ). Interestingly, we found that Gram-negative Mesorhizobium , overrepresented in patients with GERD ( 30 , 31 ) and at high RA in squamous epithelium of our patients, significantly decreased after LcS consumption. In the metaplastic esophageal region, we observed increase RA of typical intestinal taxa like Klebsiella and Prevotella , possibly driven by gastro-esophageal reflux. The high glucose content in probiotic Yakult drink, may stimulate growth of pro-inflammatory bacteria and decrease capacity of mucosal tissues to regulate epithelial integrity and immunity ( 32 ). Increased RA of Prevotella , a taxon associated with dysbiosis and cancer ( 27 ), warrants further attention, as previous studies have linked Prevotella to inflammatory conditions and tissue damage through the production of pro-inflammatory mediators( 33 , 34 ). Homolactic fermentation of glucose by LcS and other Gram-positive bacteria, such as Streptococcus , potentially have a dual effect: modulating host immunity via lactate and acetate, and decreasing pH( 35 , 36 ). While RA of the genus Lactobacillus increased significantly following LcS intervention, its overall RA remained low (0.01% to 0.03%); increased RAs of Gram-positive Rothia and Streptococcus contributed strongly to the significant increase in Firmicutes. In this study, we were unable to confirm colonization with LcS using an LcS specific assay, suggesting that its direct colonization may not be the primary mechanism of action. To optimize clinical treatment, supplementation of LcS in drinks with low glucose content together with acid-inhibiting agents like proton pump inhibitors (PPIs), might enhance probiotic benefits including reducing RAs of disease-associated Gram-negative bacteria. The findings of our study highlight clinical implications regarding the role of the esophageal microbiome in BE. First, microbial composition within metaplastic Barrett’s epithelium may serve as biomarker to identify patients at higher risk of progression to dysplasia or EAC. Specifically, increased abundance of taxa such as Proteobacteria and Prevotella was associated with inflammation and dysbiosis, possibly indicative of disease progression. Higher abundance of Leptotrichia (phylum Fusobacteria) was proposed by others as candidate biomarker of neoplastic esophageal mucosa( 22 ). Changes in microbiota composition contributing to, or resulting from carcinogenic processes have positioned microbiome composition, especially RAs of Gram-positive- and Gram-negative taxa, as biomarker for disease progression and therapeutic targets ( 37 ). The observed effects of LcS intervention on microbiome diversity and Gram-positive/Gram-negative ratio suggest potential of manipulating microbiota composition in managing BE. By enhancing microbial diversity and improving balance between Gram-positives and Gram-negatives, LcS-based therapies could mitigate inflammation and support epithelial integrity, reducing EAC risk. In a BE organoid model, L-lactate production by Streptococcus and Lactobacillus reduced EAC proliferation and modulated immune and inflammatory responses( 36 ). Therapeutic modulation of the esophageal microbiota, through probiotics like LcS or other targeted interventions, thus represents a promising adjunctive strategy for BE management, complementing current approaches aimed at halting or reversing disease progression. These findings align with emerging evidence linking carefully designed microbiome-targeted interventions (for example, probiotic formulations low in glucose) to improved gastrointestinal health and cancer prevention( 38 ). This study included a thorough microbiome analysis using 16S rRNA sequencing, ddPCR, and FISH, providing a comprehensive view of the esophageal microbiota in BE patients. Studying squamous and metaplastic epithelium within the same subjects offered valuable insights into personalized, region-specific microbial differences. Furthermore, the within-subject design allowed for robust assessment of changes induced by LcS intervention. Still, limitations should be considered when interpreting the results. The relatively small sample size may limit generalizability of the findings. We noted differences in microbiome composition between patients included in different hospitals, underscoring that a more diverse study population is necessary to generalize conclusions. The intervention duration of four weeks, while sufficient to observe some changes, may not fully capture long-term effects of probiotic consumption on the esophageal microbiome. Additionally, the lack of a control group without probiotic consumption makes it challenging to distinguish between LcS intervention effects and potential confounding factors or natural fluctuations over time. Future research directions could address these limitations and expand our understanding of the esophageal microbiome in BE. Studies with larger sample sizes will provide greater statistical power to detect subtle microbial composition shifts. Longer intervention periods could incorporate multiple clinical outcome measurements, possibly including follow-up to assess BE progression to EAC, to help determine whether microbiome composition predicts EAC development in BE patients. If such predictive patterns are identified, research could focus on whether modulating the microbiome through targeted interventions could slow or even, prevent progression to EAC. Finally, mechanistic studies to elucidate the underlying processes driving microbial shifts in BE and their potential role in disease progression, including impact of specific bacterial (toxic) metabolites and host immune responses, are needed. In conclusion, LcS consumption led to an increase in Gram-positive taxa and microbial diversity together with a decrease in Gram-negative taxa in BE. The concurrent rise in specific disease-associated taxa that thrive on simple sugars such as Prevotella , Haemophilus and Campylobacter suggested that formulation of probiotic drinks low in simple sugars is desired. Our findings underscore the potential of microbiome modulation, by stimulation of health-associated Gram-positive SCFA-producing taxa such as Lactobacillus and Streptococcus , as a possible therapeutic strategy in BE management and EAC prevention. Competing interests and funding PDS received unrestricted grants from Pentax, Fuji Film, Norgine, MicroTech, Magentiq Eye, AstraZeneca, Sanofi, and in the advisory board of Sanofi (The Netherlands). The study was partly funded by Yakult Europe B.V. for an amount of 40.000 euro. Yakult Europe B.V. did not have any input in the design, execution or interpretation of the outcome of the study. Patient & public involvement Patients or the public were not involved in the design of the study as the study protocol was designed in 2017 and patient or public involvement was at that time not needed. Data Availability All data produced in the present study are available upon reasonable request to the authors and microbiome data are available online at ENA under accession number PRJEB89339 and will become available when accepted for publication. https://www.ebi.ac.uk/ena/browser/view/PRJEB89339 Footnotes ↵ Δ Shared first authorship ↵ & shared last authorship Abbreviations used in this paper LcS Lactobacillus case Shirota preLcS before administration of LcS postLcS after administration of LcS BE Barrett’s esophagus; EAC esophageal adenocarcinoma NSE normal squamous epithelium MCE metaplastic columnar epithelium RA relative abundance CI confidence interval HGD high-grade dysplasia IQR interquartile range SD standard deviations References 1. ↵ Arnold M , Laversanne M , Brown LM , Devesa SS , Bray F . Predicting the Future Burden of Esophageal Cancer by Histological Subtype: International Trends in Incidence up to 2030 . 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