1.0GreenGate Genomicshttps://greengategenomics.com/deadminhttps://greengategenomics.com/de/author/root_u6xgdbc7/rich600338<blockquote class="wp-embedded-content" data-secret="iG2Ed1izJi"><a href="https://greengategenomics.com/de/deep-biosphere/">Deep Biosphere</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://greengategenomics.com/de/deep-biosphere/embed/#?secret=iG2Ed1izJi" width="600" height="338" title="„Deep Biosphere“ – GreenGate Genomics" data-secret="iG2Ed1izJi" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script> /*! This file is auto-generated */ !function(d,l){"use strict";l.querySelector&&d.addEventListener&&"undefined"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!/[^a-zA-Z0-9]/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret="'+t.secret+'"]'),o=l.querySelectorAll('blockquote[data-secret="'+t.secret+'"]'),c=new RegExp("^https?:$","i"),i=0;i<o.length;i++)o[i].style.display="none";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute("style"),"height"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):"link"===t.message&&(r=new URL(s.getAttribute("src")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener("message",d.wp.receiveEmbedMessage,!1),l.addEventListener("DOMContentLoaded",function(){for(var e,t,s=l.querySelectorAll("iframe.wp-embedded-content"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute("data-secret"))||(t=Math.random().toString(36).substring(2,12),e.src+="#?secret="+t,e.setAttribute("data-secret",t)),e.contentWindow.postMessage({message:"ready",secret:t},"*")},!1)))}(window,document); //# sourceURL=https://greengategenomics.com/wp-includes/js/wp-embed.min.js </script>https://greengategenomics.com/wp-content/uploads/2023/06/DeepBiosphere_FeatureImages.png640400Specifically adapted laboratory and bioinformatic workflows allowed the reconstruction of microbial distribution patterns down to a depth of 230 m across this, difficult to work with, low biomass environment. Metagenomic genome recovery allowed the detection and characterization of CO2 utilizing methangenic and chemolithotrophic mcirroganismans. Statistical evaluation provided insights into microbial co-occurrence patterns and bio-geo interactions.