Category: ProxiMeta

Bacterial pathogens have their own nemesis, and mimicking it can help solve the global AMR crisis

image of the globe surrounded by images of plants and viruses

 

Decades of antibiotic use – and abuse – are triggering a global rise in antibiotic resistance and limiting the usefulness of these life-saving drugs. In a nod to the adage, “The enemy of my enemy is my friend,” a solution may lie with bacteria’s oldest adversary: phages, the viruses that prey upon them. Our team at Phase Genomics is harnessing groundbreaking new metagenomic data and AI to tap into the evolutionary innovations of phages – and to eradicate dangerous microbial pathogens with surgical precision.

 

The need could not be greater. Fewer new antibiotics are hitting the market. The UN estimates that by 2050, worldwide deaths from antibiotic-resistant “superbugs” will overtake deaths from cancer.  Early 20th century scientists explored deploying phages to cure bacterial infections, an idea that has been recently resurrected. Phages are a staggeringly diverse class of bacteria-killers. By one estimate there are 1031 of them on this planet right now, vastly more than all living organisms combined. But using phages to cure infections has its own drawbacks: Mass production is difficult since phages only grow in bacteria, which can be difficult to culture, and it turns out bacteria have a barrage of defenses against intact viruses, imparting resistance against them.

 

While phages present one opportunity to help us stave off a return to the pre-penicillin past, we can also use their anti-bacterial weapons to launch a new arsenal rooted in synthetic biology. Phages produce proteins called lysins to destroy their hosts’ cell walls. These proteins have evolved over millennia to specifically target the phages’ hosts. They can be purified and used as precision antimicrobials, molecules that specifically kill the target bacteria without the collateral damage and resistance brought about by traditional wide-spectrum antibiotics.

 

Our team has used our unique genome sequencing technology to build the world’s largest catalog of the genomes of phages and the microbes that they attack – including the sequences of lysin proteins that they make. We’re harnessing this catalog to design, synthesize, and perfect lysin-based therapeutics that can attack bacterial pathogens safely, effectively, and with a surgical precision that today’s antibiotics lack.

 

Lysins hold tremendous advantages over traditional antibiotics. Antibiotics take out swathes of bacteria in our microbiomes that are essential for good health, leaving us more vulnerable to future infections – like the dreaded C. difficile – as well as to immune dysregulation. Yet most lysins target only the phage’s host species and its close relatives. And though antibiotic resistance spreads rapidly via plasmids, bacteria struggle to evolve resistance to exogenously introduced lysins.

 

Our collective knowledge of lysins to date comes largely from isolated experiments on phages or small-scale genomic studies. To deploy lysins as a life-saving solution, we need detailed knowledge of the intricate and intimate interactions between phages and bacteria. Phase Genomics has led this effort by building a vast catalog containing hundreds of thousands of phage genomes from different microbial environments. Our proprietary ProxiMeta technology employed for these experiments preserves unique information about essential ecological interactions in these microbiomes, including the host bacterial species that specific phages target. Thanks to this large and growing catalog of phage-microbe interactions, for many pathogenic bacteria, we can find specific lysins that could turn its cell walls into Swiss cheese.

 

We are using this foundational knowledge to build the first foundry for lysins. With support from the Bill and Melinda Gates Foundation, Phase Genomics is collaborating with Lumen Bioscience to design, grow, and purify lysins identified by our catalog. This proving ground will serve as the foundation for a future pipeline for lysin design – augmented by machine learning to hone target specificity, perfect performance and even create entirely new lysins with a desired target specificity. To make a custom-designed lysin against almost any bacteria, we would need to find a phage – and its lysin – that attacks it. This approach to lysin research and discovery has applications even beyond medicine, such as critically needed environmental remediation.

 

Our goal to develop therapeutic lysins would upend the existing paradigm for treating bacterial infections. Today, medical professionals have a shrinking pool of imperfect antibiotics that cut a swathe through our microbiomes to take out the bacterial bad guys. With lysins on the shelf as an option, we would be taking away this machete, and replacing it with a scalpel.

 

Better together: long-range and long-read DNA sequencing methods close age-old blindspots in microbiome research

 

Since its debut, next-generation sequencing has not rested on its laurels. Improved sequencing platforms have reduced error and lengthened reads into the tens of thousands of bases. The debut of ultra-long-range sequencing methods that are based on proximity ligation (aka Hi-C) has brought a new order-of-magnitude into reach by linking DNA strands with their neighbors before sequencing.

Rapid progress in this field has birthed genome-resolved metagenomics, the sequencing and assembly of genomes from environmental samples to study ecosystem dynamics. But metagenomic experiments often undersample microbial diversity, missing rare residents, overlooking closely related organisms (like bacterial strains), losing rich genetic data (like viruses and metabolite gene clusters), and ignoring host-viral or host-plasmid interactions.

 

A revolution within a revolution

New sequencing platforms and methods can reform metagenomics from within. Phase Genomics has been a leader in genome-resolved metagenomics with its ProxiMeta™ platform, which leverages a method that physically connects DNA molecules inside cells before sequencing to generate highly complete genomes for novel bacteria and viruses. Boosting proximity-fueled methods with long-read platforms, such as the PacBio® Sequel® IIe system that can yield HiFi reads of up to 15,000 base pairs with error rates below 1%, could stretch its potential even further.

In a study published in Nature Biotechnology, a team — led by Dr. Timothy Smith and Dr. Derek Bickhart at the U.S. Department of Agriculture and Dr. Pavel Pevzner at the University of California, San Diego — employed both PacBio HiFi sequencing and ProxiMeta in a deep sequencing experiment to uncover record levels of microbial diversity from a fecal sample of a Katahdin lamb. Combined, PacBio HiFi sequencing and ProxiMeta eased assembly, recovered rare microbes, resolved hundreds of strains and their haplotypes, and revealed hundreds of novel plasmid and viral interactions.

 

Deeper diversity

The team constructed SMRTbell® libraries to generate HiFi data, and ProxiMeta™ libraries to generate long-range sequencing data. The two datasets allowed them to assemble contigs and create draft genomes without manual curation.

Researchers compared the breadth and depth of HiFi data-derived metagenome-assembled genomes, or MAGs, to control MAGs from assemblies of the same sample made using long, more error-prone reads. HiFi data yielded 428 complete MAGs from bacteria and archaea — a record number from a single sample. HiFi data also generated more low-prevalence MAGs, capturing a larger slice of the community’s diversity by picking up more genomes from less common residents.

 

The hidden actors

But no assembly method could be considered “complete” if it overlooked viruses, the most numerous members of virtually all ecological niches on Earth. These tiny players shape microbial communities in ways scientists are still trying to understand. For example, as agents of horizontal gene transfer, they help spread antibiotic resistance genes. And conversely, they have recently grown in popularity as a means to kill resistant bacteria in our ever-waging war against antibiotic resistance.

Phase Genomics’ ProxiPhage™ tool can already assemble high-fidelity viral genomes from microbial communities, even using only short-read sequencing data. But the new study shows that having HiFi helps considerably. The team identified 424 unique viral-host interactions, including 60 between viruses and archaea, which is a more than 7-fold increase over control samples. In total, the HiFi library included nearly 400 viral contigs, more than half of which came from a single family that infects bacteria and archaea. The ability to connect viruses with their microbial hosts in vivo is a unique property of Phase Genomics’ technology.

 

HiFi family trees

The long-range ProxiMeta libraries contained information that yielded more than 1,400 complete and 350 partial sets of gene clusters from archaea and bacteria for synthesizing metabolites such as proteasome inhibitors — the most uncovered to date. These clusters likely help some of these microbes colonize the gut. HiFi data picked up about 40% more clusters than control MAGs, illustrating just how much data is lost when long reads aren’t also highly accurate reads.

The team also used the HiFi-based MAGs to trace lineages within the community. They computationally resolved 220 MAGs into strain haplotypes, based largely on variations within single-copy genes. One MAG had 25 different haplotypes, which are likely strains of the same genus or species.

ProxiMeta ultra-long-range sequencing also linked nearly 300 HiFi-assembled plasmids to specific MAGs — revealing the species that hosted them in vivo. One plasmid, for example, was found in bacteria from 13 different genera. Long-range data also identified the first plasmids associated with three archaea, including Methanobrevibacter and Methanosphaera.

 

What’s around the bend?

This study has lessons beyond one lamb’s gastrointestinal tract. It shows decisively that the discovery power innate to long-range sequencing methods like ProxiMeta are greatly enhanced when wedded to high-accuracy sequencing methods like HiFi. Together, the two generate increasingly sophisticated metagenome assemblies for biologists to interrogate.

Applied to other environmental samples, this platform could illuminate the diversity and complexity of other microbial communities — from the bottom of the sea to mountain peaks, and within the body of every human being. It could probe pressing issues of our day, such as disease, soil health, and antibiotic resistance, a scourge whose spread and potential solutions — such as phage therapy — can only be forged through a thorough understanding of microbial diversity, interactions, and ecology.

100 Publications

 

 

Over 100 scientific papers have been published using Phase Genomics technology!

 

Since our founding in 2015, we have sought to bring transformative change to research, industry, and the clinic by building and providing cutting-edge genomic solutions to scientists all over the globe. Now, in 2021, we are happy to look back at the accomplishments made by those using our kits, services, and software.

 

Our team of researchers, computational scientists, and bioinformaticians have refined our ProxiMeta and Proximo Platforms (as well as many other products) to construct platinum genomes, master the microbiome, and expand our knowledge of the human genome and epigenomics. From potatoes to people, cassava to cannabis, bison to basenjis, our molecular tools and software have been used to drive genomic discoveries across many scientific fields. We encourage you to take a look at the fascinating collection of articles we have compiled here that explore more research using our technology.

 

Over the years, we have also helped break records and make headlines as researchers use our platforms to make breakthroughs in science.

 

A Question Hidden in the Platypus Genome: Are We the Weird Ones?

-The New York Times

Phase Genomics Releases Platform for Discovering New Viruses in Microbiome Samples

-BusinessWire

Precision Medicine Looks beyond DNA Sequences

-Genetic Engineering and Biotechnology News

 

We are grateful to all the researchers who have been working with us to accomplish these feats. Together, we can drive innovation and continue to make advances in genomic science. We will continue to work on ways to add applications and support current research, making it easier to get high-quality data and comprehensive reports.

 

Follow us on social media (Twitter, LinkedIn, YouTube) or subscribe to our quarterly newsletter (Phasebook) to receive updates on our technology and highlights from the latest in genomics.

Unlock the Virome with ProxiPhage

viruses moving through a net

 

Metagenomic studies are illuminating the diverse array of microbiomes that exist from the ocean floor to our gastrointestinal tracts. Understanding these microbial communities is essential to understanding modern health and the environment; however, outdated lab techniques are laborious, costly, and fail to create a complete picture of the microbiome. This article, posted by Ivan Liachko, describes how advancements in biotechnology are facilitating exciting discoveries with recent tools developed to capture phage and other mobile genetic element dynamics within microbiome samples.

Continue reading to discover how ProxiPhage, a recent addition to the ProxiMeta platform, is helping scientists answer questions relating to microbiome composition dynamics, prophage prevalence, frequency of transient infections, spread of antibiotic resistance, and more.

https://www.linkedin.com/pulse/unlocking-virome-proximity-guided-metagenomics-new-frontier-liachko/

 

 

Better together: long-range and long-read DNA sequencing methods, combined, reach record heights in microbiome discovery

Microbiome plate and Phase Genomics logo. Reads "Breaking records in microbiome discovery"

 

Click here for an updated blog post.

 

Since its debut, next-generation sequencing has not rested on its laurels. Improved sequencing platforms have reduced error and lengthened reads into the tens of thousands of bases. The debut of long-range sequencing methods that are based on proximity ligation (aka Hi-C) has brought a new order-of-magnitude into reach by linking DNA strands with their neighbors before sequencing.

 

This progress has birthed high-resolution metagenomics, the sequencing and assembly of genomes from environmental samples to study ecosystem dynamics. But metagenomic experiments often undersample microbial diversity, missing rare residents, overlooking closely related organisms (like bacterial strains), losing rich genetic data (like metabolite gene clusters), and ignoring host-viral or host-plasmid interactions.

 

A revolution within a revolution

 

New sequencing platforms and methods can reform metagenomics from within. Long-read platforms, such as the PacBio® Sequel® IIe system, now yield HiFi reads of up to 15,000 base pairs with error rates below 1%. In addition, Phase Genomics created ProxiMeta™ kits to generate proximity-ligated long-range sequencing libraries, which preserve associations between DNA strands originating in the same cell.

 

In a study posted May 4 to bioRxiv, a team — led by Dr. Timothy Smith and Dr. Derek Bickhart at the U.S. Department of Agriculture and Dr. Pavel Pevzner at the University of California, San Diego — employed both PacBio HiFi sequencing and ProxiMeta in a deep sequencing experiment to uncover record levels of microbial diversity from a fecal sample of a Katahdin lamb. Combined, PacBio HiFi sequencing and ProxiMeta eased assembly, recovered rare microbes, resolved hundreds of strains and haplotypes, and preserved hundreds of plasmid and viral interactions.

 

HiFi family trees

 

The team constructed SMRTbell® libraries to generate HiFi data, and ProxiMeta kits to generate long-range libraries. The two datasets, along with the metaFlye and ProxiMeta algorithms, allowed them to assemble contigs and create draft genomes without manual curation.

 

Researchers compared the breadth and depth of HiFi data-derived metagenome-assembled genomes, or MAGs, to control MAGs from assemblies of the same sample made using long, error-prone reads. HiFi data yielded more complete MAGs — 428 versus 335 — from more bacteria and archaea. HiFi data also generated more low-prevalence MAGs, capturing a larger slice of the community’s diversity by picking up more genomes from less common residents.

 

The HiFi MAGs also contained more than 1,400 complete and 350 partial sets of gene clusters for synthesizing metabolites such as proteasome inhibitors, which likely help some of these microbes colonize the gut. HiFi data picked up about 40% more of such clusters than control MAGs, illustrating just how much data is lost when long reads aren’t also highly accurate reads.

 

The team also used the HiFi MAGs to trace lineages within the community. They computationally resolved 220 MAGs into strain haplotypes, based largely on variations within single-copy genes. One MAG had 25 different haplotypes, which are likely strains of the same genus or species.

 

ProxiMeta’s long-range discoveries

 

The ProxiMeta-generated libraries added flesh to these MAG frames skeletons by unveiling additional rich biological information. Long-range sequencing linked nearly 300 HiFi-assembled plasmids to specific MAGs — revealing the species that hosted them. One plasmid, for example, was found in bacteria from 13 different genera. Long-range data also identified the first plasmids associated with two archaea, Methanobrevibacter and Methanosphaera.

 

Long-range sequencing illuminated the viral burden in this community. The HiFi library included nearly 400 viral contigs, more than half of which came from a single family of viruses that infect both bacteria and archaea. The team identified 424 unique viral-host interactions, including 60 between viruses and archaea, which is a more than 7-fold increase over controls.

 

What’s around the bend?

 

This study has lessons beyond one lamb’s gastrointestinal tract. It shows decisively that the highly accurate long reads generated by HiFi sequencing ideal partners for Hi-C-derived methods like ProxiMeta — together generating increasingly sophisticated metagenome assemblies for biologists to interrogate.

 

Applied to other environmental samples, this platform could illuminate the diversity and complexity of other microbial communities — from the bottom of the sea to mountain peaks, and within the stomach of every human being. It could probe pressing issues of our day, such as antibiotic resistance, soil health, or how microbes can break down pollutants. These endeavors will not just fuel the engines of scientific inquiry. Broader use of this method could generate new insights into pressing problems of our times, including antibiotic resistance.

Choose This Year’s Metagenomics Award Winner

Congratulations to Dr. Ben Tully on winning this year’s Project ProxiMeta: 2019 Metagenomics Award! Read more about his project, 4. The Complete Hydrothermal Microbial Metal Metabolism

This summer, researchers from across the U.S. sent in short proposals for a chance to win a full-service ProxiMeta™ microbiome workup for a sample of their choice. ProxiMeta combines shotgun metagenomics with in vivo proximity ligation (Hi-C) and necessary bioinformatic tools to help researchers assemble high-quality microbial genomes directly from complex microbiome samples.

 

 

HOW TO VOTE

Each project was assessed by a panel of scientists for scientific merit, novelty, impact, and feasibility, and four finalists were selected. Cast your vote on Twitter for your favorite project.

 


 

THE FINALISTS

1. The Gut Microbiome as a Risk Factor for Arsenic-Induced Cancer

Twitter Name: Gut & As-Induced Cancer

It is estimated that ~200 million people worldwide are exposed to arsenic concentrations exceeding current safety standards. Our collaborators have recently demonstrated that mice and human microbiomes can protect mice from arsenic toxicity. While human stool supplementation fully restores protection to arsenic in germ-free mice, researchers were only able to isolate one microbe, Faecalibacterium prausnitzii, that successfully conferred protection to both parent and infant mice. These results are huge because arsenic poses the highest lifetime risk for developing cancer in humans.We will investigate the role of arsenic-transforming bacteria within the gastrointestinal (GI) microbiome as another possible risk factor.

In nature, arsenic-reducing microorganisms are well known for their ability to generate more toxic arsenic products called arsenites, which are typically formed in anaerobic environments like the gut. Past research indicates that ingested arsenic may also be transformed into the toxic product arsenite by gut microbes thus increasing the risk for the host. On the other hand, arsenite-oxidizing microbes may also provide a benefit to the host by lowering arsenite concentrations. The ability of the microbiome to transform arsenic is determined by its genetic composition, therefore ProxiMeta sequencing technology will allow us to immediately analyze our collaborators rodent stool samples for genetic clues regarding this mysterious protection. Our project goals are to expand on this knowledge by: (1) characterizing the genetic basis for protection to arsenic provided by the microbiome (2) identifying, and then isolating, the bacteria-harboring arsenic transforming genes involved in protection.

We predict that differences in the gut metagenome composition will explain the incidences in arsenic susceptibility within a population or even at the family level. This project will provide important insight regarding how gut microbes contribute to cancer and may lead to novel therapies and probiotics that could target the microbiome of arsenic-exposed individuals.


2. Evaluating Antimicrobial Resistance in Backyard Poultry Environments

Twitter: AMR in Backyard Poultry

Approximately 13 million rural, urban, and suburban US residents reported owning backyard poultry (BYP) in 2014, and interest in BYP ownership is nearly four times that amount. BYP ownership has risen recently due to product quality, public health, ethical, and animal welfare concerns of commercial operations. However, BYP ownership and disease treatment is largely under-regulated, unlike commercial poultry production. Lack of regulation poses public health concerns of transmission of antimicrobial resistant (AMR) bacteria, such as AMR strains of Salmonella, Mycoplasma gallisepticum, and Escherichia coli commonly associated with BYP. BYP owners (2014 survey) were largely uninformed about poultry diseases and treatments but were interested in learning more on disease management.

The combination of a lack of regulation and public information warrants further research into the bacterial communities of BYP and their environments. Cloacal and environmental swabs were collected as part of a 2018 citizen science study where BYP owners reported current and historical poultry antibiotic usage. We propose to conduct shotgun metagenomic sequencing and proximity ligation using the ProxiMeta platform, allowing for increased detection of full-length AMR gene alleles compared to that revealed by short-read sequencing. The combination of PacBio reads with HiC intercontig ligation analysis allows for identification of potential gene transfer events of AMR genes within communities and potential dissemination throughout the environment.

This analysis is especially important considering the public health concerns of AMR persistence in backyard environments. Additionally, investigation of lytic and prophage presence would allow investigation of phage-mediated bacterial regulation that would not be possible with short-read sequencing alone. ProxiMeta analysis of these samples would provide the most comprehensive insight of AMR presences and persistence in BYP environments to date. These findings will be critical for new regulation and disease management for the increasing number of BYP flocks, which currently pose a potential health risk.


3. Unraveling the Metagenomics of Contamination

Twitter: Steel Site Contamination

We propose a metagenome characterization of contaminated Munger Landing sediment located in the St. Louis River, Duluth, MN USA. Seasonal samples are already collected and stored; of which one will be sequenced. Munger landing, is located downstream from the U.S. Steel Superfund site and contaminants include PAHs, dioxins, PCBs, and heavy metals.

Soil condition is integral to high productivity and ecosystem balance at all trophic levels. Human activities erode soil condition through agriculture, mining, sewage outflows and/or chemical/waste disposal into waterways. These practices alter the chemical structure of the soil and break down the microbial community processes responsible for ensuring the balance of biogeochemical cycling patterns in the soil. We hypothesize the activity of these pathways involved in cycling of nitrogen, phosphorus and carbon are altered in contaminated soil systems.

Metagenomic profiling of Munger Landing will provide data to examine microbes, metabolic pathways, and contaminant-processing genes present in the community that can be characterized further using qRTPCR. This project will be presented within a community college microbiology course module. Curriculum utilizing real-world data and the sequencing technology from Phase Genomics will teach students experimental design, troubleshooting, hypothesis testing, data analysis and how to communicate the broader impacts of a study to society, the field of environmental microbiology or conservation.

In the future, this data will assist in designing a longitudinal metagenomic and metatranscriptomic study to assess the ability of remediation to ‘recover’ bacterial community function at the Munger Landing site; slated to start in 2020-2021 as compared to two uncontaminated control sites. Ten sites, slated for remediation, have been identified as having high chemical and heavy metal contamination for the St. Louis River Estuary. The Munger Landing project will establish a workflow that can be applied to other contaminated sites.


4. The Complete Hydrothermal Microbial Metal Metabolism

Twitter: Hydrothermal Microbiome

Hydrothermal vents replenish the oceans with much-needed micronutrients, spewing iron, magnesium, nickel, and other metals from the earth’s crust. These metal micronutrients are used as biological cofactors for organisms throughout the marine food chain. Boiling, sterile hydrothermal fluids quickly cool and are colonized by highly specialized microorganisms that begin to cycle the metal species mixing with the seawater. Though regularly sampled, rarely have hydrothermal plumes been tracked through the water column to establish how microbial colonization occurs through time and space. We lack understanding regarding the replicability of colonization to what extent stochastic processes shape microbial community structure.

While on station at the East Pacific Rise hydrothermal vent field, size-fractionated samples (0.2, 3.0 and 5.0-μm) were collected in the hydrothermal plume emanating from Bio Vent. Samples fluids were collected from the source through the first 1-km of dispersal – the key distance for colonization – and this effort was repeated over the course of 10-days – to determine the replicability of natural colonization events. The application of standard metagenomics sequencing and microbial genome reconstruction through binning would provide novel insight into the cycling of metals within the plume but the use of cross-linked DNA techniques would deliver an unprecedented understanding of how strain diversity impacts colonization and how microbes interact with extrachromosomal elements in the environment.

While some microbes are poised to take advantage of reduced metal species for lithotrophic growth, microbes from the water column that become entrained in the plume will need metal-resistance adaptations to alleviate stress from the elevated metal concentrations present. Metal-resistance genes dispersed through the viral and plasmid pools are essential elements for understanding the functioning of the microbial community in this globally important source of metals to the oceans and effective interpretation of the community can only be achieved through cross-linked DNA metagenomic techniques.

*All finalists projects are owned by verified researchers at U.S. academic institutions.


 

RESOURCES

 

Project ProxiMeta: 2019 Metagenomics Award

Win a Free Proximity-Ligation Metagenomics Project

Win a chance to collaborate with Phase Genomics on a metagenomics research project. The grand prize winner will receive a full-service ProxiMeta Metagenome Deconvolution project, including proximity-ligation and shotgun library prep, sequencing, and analysis. Characterize a microbial community of your choice and assemble hundreds of bacterial and eukaryotic genomes, associate plasmids and phage with hosts, and discover novel microbial life.

Submit your proposal by August 8, 2019 The four project finalists will be announced on September 5, 2019 via Twitter based on scientific merit, novelty, and impact. After a week of public voting, the project with the most votes will be named the 2019 Metagenomics Award winner and will receive a full ProxiMeta service project.

With ProxiMeta, you can explore the microbiome with confidence. Only high-quality microbial genomes can provide true insights into the dark matter of the microbiome. Submit your proposal for the 2019 Metagenomics Award today!


KEY DATES

8 August                                      Deadline for Entries

4 September                               Finalists Announced

5-12 September                          Vote for Projects @PhaseGenomics Twitter

12 September                             2019 Metagenomics Award Announcement

 


Help Us Choose the Winner!

We need your help choosing which project to sequence! Below are our four finalists, read through the project proposals and choose your favorite; voting is open to the public and will take place on Twitter September 5, 2019 for one week.


1. The Gut Microbiome as a Risk Factor for Arsenic-Induced Cancer

It is estimated that ~200 million people worldwide are exposed to arsenic concentrations exceeding current safety standards. Our collaborators have recently demonstrated that mice and human microbiomes can protect mice from arsenic toxicity. While human stool supplementation fully restores protection to arsenic in germ-free mice, researchers were only able to isolate one microbe, Faecalibacterium prausnitzii, that successfully conferred protection to both parent and infant mice. These results are huge because arsenic poses the highest lifetime risk for developing cancer in humans.We will investigate the role of arsenic-transforming bacteria within the gastrointestinal (GI) microbiome as another possible risk factor.

In nature, arsenic-reducing microorganisms are well known for their ability to generate more toxic arsenic products called arsenites, which are typically formed in anaerobic environments like the gut. Past research indicates that ingested arsenic may also be transformed into the toxic product arsenite by gut microbes thus increasing the risk for the host. On the other hand, arsenite-oxidizing microbes may also provide a benefit to the host by lowering arsenite concentrations. The ability of the microbiome to transform arsenic is determined by its genetic composition, therefore ProxiMeta sequencing technology will allow us to immediately analyze our collaborators rodent stool samples for genetic clues regarding this mysterious protection. Our project goals are to expand on this knowledge by: (1) characterizing the genetic basis for protection to arsenic provided by the microbiome (2) identifying, and then isolating, the bacteria-harboring arsenic transforming genes involved in protection.

We predict that differences in the gut metagenome composition will explain the incidences in arsenic susceptibility within a population or even at the family level. This project will provide important insight regarding how gut microbes contribute to cancer and may lead to novel therapies and probiotics that could target the microbiome of arsenic-exposed individuals.


2. Evaluating antimicrobial resistance in backyard poultry environments

Approximately 13 million rural, urban, and suburban US residents reported owning backyard poultry (BYP) in 2014, and interest in BYP ownership is nearly four times that amount. BYP ownership has risen recently due to product quality, public health, ethical, and animal welfare concerns of commercial operations. However, BYP ownership and disease treatment is largely under-regulated, unlike commercial poultry production. Lack of regulation poses public health concerns of transmission of antimicrobial resistant (AMR) bacteria, such as AMR strains of Salmonella, Mycoplasma gallisepticum, and Escherichia coli commonly associated with BYP. BYP owners (2014 survey) were largely uninformed about poultry diseases and treatments but were interested in learning more on disease management.

The combination of a lack of regulation and public information warrants further research into the bacterial communities of BYP and their environments. Cloacal and environmental swabs were collected as part of a 2018 citizen science study where BYP owners reported current and historical poultry antibiotic usage. We propose to conduct shotgun metagenomic sequencing and proximity ligation using the ProxiMeta platform, allowing for increased detection of full-length AMR gene alleles compared to that revealed by short-read sequencing. The combination of PacBio reads with HiC intercontig ligation analysis allows for identification of potential gene transfer events of AMR genes within communities and potential dissemination throughout the environment.

This analysis is especially important considering the public health concerns of AMR persistence in backyard environments. Additionally, investigation of lytic and prophage presence would allow investigation of phage-mediated bacterial regulation that would not be possible with short-read sequencing alone. ProxiMeta analysis of these samples would provide the most comprehensive insight of AMR presences and persistence in BYP environments to date. These findings will be critical for new regulation and disease management for the increasing number of BYP flocks, which currently pose a potential health risk.


3. Unraveling the metagenomics of contamination

We propose a metagenome characterization of contaminated Munger Landing sediment located in the St. Louis River, Duluth, MN USA. Seasonal samples are already collected and stored; of which one will be sequenced. Munger landing, is located downstream from the U.S. Steel Superfund site and contaminants include PAHs, dioxins, PCBs, and heavy metals.

Soil condition is integral to high productivity and ecosystem balance at all trophic levels. Human activities erode soil condition through agriculture, mining, sewage outflows and/or chemical/waste disposal into waterways. These practices alter the chemical structure of the soil and break down the microbial community processes responsible for ensuring the balance of biogeochemical cycling patterns in the soil. We hypothesize the activity of these pathways involved in cycling of nitrogen, phosphorus and carbon are altered in contaminated soil systems.

Metagenomic profiling of Munger Landing will provide data to examine microbes, metabolic pathways, and contaminant-processing genes present in the community that can be characterized further using qRTPCR. This project will be presented within a community college microbiology course module. Curriculum utilizing real-world data and the sequencing technology from Phase Genomics will teach students experimental design, troubleshooting, hypothesis testing, data analysis and how to communicate the broader impacts of a study to society, the field of environmental microbiology or conservation.

In the future, this data will assist in designing a longitudinal metagenomic and metatranscriptomic study to assess the ability of remediation to ‘recover’ bacterial community function at the Munger Landing site; slated to start in 2020-2021 as compared to two uncontaminated control sites. Ten sites, slated for remediation, have been identified as having high chemical and heavy metal contamination for the St. Louis River Estuary. The Munger Landing project will establish a workflow that can be applied to other contaminated sites.


4. The Complete Hydrothermal Microbial Metal Metabolism

Hydrothermal vents replenish the oceans with much-needed micronutrients, spewing iron, magnesium, nickel, and other metals from the earth’s crust. These metal micronutrients are used as biological cofactors for organisms throughout the marine food chain. Boiling, sterile hydrothermal fluids quickly cool and are colonized by highly specialized microorganisms that begin to cycle the metal species mixing with the seawater. Though regularly sampled, rarely have hydrothermal plumes been tracked through the water column to establish how microbial colonization occurs through time and space. We lack understanding regarding the replicability of colonization to what extent stochastic processes shape microbial community structure.

While on station at the East Pacific Rise hydrothermal vent field, size-fractionated samples (0.2, 3.0 and 5.0-μm) were collected in the hydrothermal plume emanating from Bio Vent. Samples fluids were collected from the source through the first 1-km of dispersal – the key distance for colonization – and this effort was repeated over the course of 10-days – to determine the replicability of natural colonization events. The application of standard metagenomics sequencing and microbial genome reconstruction through binning would provide novel insight into the cycling of metals within the plume but the use of cross-linked DNA techniques would deliver an unprecedented understanding of how strain diversity impacts colonization and how microbes interact with extrachromosomal elements in the environment.

While some microbes are poised to take advantage of reduced metal species for lithotrophic growth, microbes from the water column that become entrained in the plume will need metal-resistance adaptations to alleviate stress from the elevated metal concentrations present. Metal-resistance genes dispersed through the viral and plasmid pools are essential elements for understanding the functioning of the microbial community in this globally important source of metals to the oceans and effective interpretation of the community can only be achieved through cross-linked DNA metagenomic techniques.

 

 


 

RESOURCES

Hi-C Technology Links Antimicrobial Resistance Genes to the Microbiome

 

Antibiotic resistance is a rapidly growing global health threat as bacteria share and spread resistance genes via plasmids and other mobile genetic elements. Several teams of researchers applied a new method to understand which microorganisms house genes for antibiotic resistance within complex microbiome communities.
Read the paper, Linking the Resistome and Plasmidome to the Microbiome.

 

ANTIMICROBIAL RESISTANCE ON THE RISE

 

According to the World Health Organization, antimicrobial resistance (AMR) in microbial pathogens is expected to take 10 million lives by 2050 if there are no new pharmaceutical or technological advancements dedicated to combating this pressing problem. For almost a century, medicine has made remarkable impact on human life by using antibiotics to treat infections, but this has led to a very concerning overuse problem, stoking an arms race between antibiotics and the pathogens they target. The CDC points out that at least 30% of antibiotic prescriptions are unnecessary and there is a massive contribution to antibiotic overuse in the food and agriculture industry where each year 130,000 tons of antibiotics are given to food animal livestock. Both of these problems correlate with the rise of AMR.

 

Though there are naturally occurring antibiotic-resistant bacteria, there are two mechanisms by which bacteria can acquire antimicrobial resistance genes (ARGs) and become resistant: 1) through spontaneous genetic mutations and/or 2) by acquiring genetic material from other microbes via plasmids, viruses, or other means of horizontal gene transfer. Due to the evolutionary pressure exerted on microbes by antibiotic overuse, pathogens resistant to these antibiotics within our body, hospitals, and the environment become reservoirs of transmittable AMR genes that can rapidly spread and accumulate within a single microbe contributing to the emergence of multidrug-resistant microbes commonly known as superbugs.

 

PROXIMITY-LIGATION (HI-C) LINKS ARG AND PLASMIDS TO THEIR HOSTS

 

One of the biggest obstacles faced by scientists when studying AMR is the inability to determine which microbes are carrying and spreading specific ARGs. Because these genes often travel on mobile elements, they can move dynamically between different species and can therefore be found in numerous organisms without one clear parental host. When attempting to sequence the DNA of a mixed microbial sample, all the DNA is purified from all the cells at the same time and the host-plasmid connection is severed, making it nearly impossible to determine where each mobile element came from or if they were shared among several species. In this newly published paper, researchers highlight a novel method for linking ARGs and other mobile genetic elements to their hosts directly from microbiome samples using the latest version of the proximity-ligation (Hi-C) data analysis tool, ProxiMeta Hi-C.

 

Phase Genomics CEO, Dr. Ivan Liachko, describes how our Hi-C platform solves one of microbiologists’ greatest problems pertaining to the linking of plasmids with their hosts.

 

Hi-C utilizes in vivo proximity-ligation which can assemble complete genomes down to the strain-level directly from mixed-population samples as well as physically links plasmids/ARGs to their host. This method is particularly useful for researchers studying the “dark-matter” of the microbiome because the method does not require culturing nor a priori information about a sample.

 

USING HI-C TO TRACK ARGs IN THE MICROBIOME

 

Lead author Thibault Stalder from the University of Idaho used the ProxiMeta Hi-C kit on a complex microbiome wastewater community, a suspected AMR reservoir, to learn more about which bacteria carry ARGs. After the Hi-C library was sequenced, Phase Genomics used the data to inform contig clustering of hundreds of genomes, most of which are novel, with our cloud-based software – ProxiMeta. Using the genome clusters found by ProxiMeta, the Hi-C linkages of each ARG-, plasmid-, and integron-bearing contigs to each genome were measured to determine which species physically hosted the relevant mobile elements.

 

ProxiMeta was able to cluster contigs into >1000 genome clusters and search for over 30 groups of ARGs, plasmids, and integrons which speed up the adaptive process of newly integrated ARGs (Figure 1, circle plot). For each of these genes, we inferred hosts (Figure 2). Moreover, these organisms generally belonged to families known to host each known gene (marked with an “X” in Figure 2), supporting the accuracy of the analysis. In the future, this information will allow us to track the spread of AMR in complex communities consisting of many diverse organisms.

 

Microbiome Antibiotic Resistance Genes and Plasmids

Figure 1: Hi-C linkage between ARGs, plasmid markers, and integrons among clusters belonging to Alpha, Beta, Gamma and Delta Proteobacteria.

 

Over 200 genome clusters had strong Hi-C links to ARGs, of which 12 had high-quality assemblies. These resultant genomes include both gram positive and gram-negative bacteria and most belonged to species that were previously unsequenced. ARGs were mostly linked to genome clusters belonging to the Gammaproteobacteria, Betaproteobacteria and Bacteroidetes (Figure 2, below).

 

Microbiome Antibiotic Resistance Genes AMR and Plasmids

Figure 2: Normalized Hi-C links between ARGs, plasmids, and families of bacteria.

 

 

FUTURE DIRECTIONS

 

This method can be useful for researchers not only studying the microbiome, but the virome as well. Phages, or viruses, also distribute genetic information amongst bacteria to influence host biology, much like plasmids. Several previous studies showed that in vivo proximity-ligation can be used to link phages with their hosts directly from mixed complex samples, much like was done with plasmids and AMR genes in this study. This information could be crucial to labs and companies that are now engineering phages that could replace the widespread use of antibiotics and combat AMR.

 

This year, antibiotic resistant bugs have infected more than 2 million people globally; 23,000 of those individuals will die because of our inability to fight these superbugs. By using ProxiMeta Hi-C to better understand the genomics of microbial communities suspected to be AMR reservoirs, researchers can identify ARG carriers down to the strain-level and quantify how prevalent these genes are. With further exploration, this tool could one day offer a new solution to limit the spread of these genes and reverse the trend of increasing antibiotic resistance and save lives.

 

BRING A HI-C KIT INTO YOUR LAB TODAY

 

Phase Genomics offers a wide variety of proximity-ligation products and services including Hi-C preparation kits and a range of different cloud-based bioinformatic analysis platforms. Power your microbiome research with ProxiMeta Hi-C and our easy Hi-C kits; assemble hundreds of complete genomes for novel, unculturable microbes, and associate plasmids with hosts directly from raw microbiome samples using ProxiMeta Hi-C.

Earth’s Wine Cellar: Digging into the Microbiome of Vineyards

 

Phase Genomics partnered with Browne Family Vineyards to begin to understand, the microbiome makeup of soils within different vineyards across the state of Washington. The findings were unveiled at the Pacific Science Center’s “STEM: Science Uncorked” winetasting event.

There are many different factors that contribute to soil composition, such as parent material, topography, climate, geological time, and the thousands of different and undiscovered microbes living in the soil—the least understood factor. In April of 2018, Browne Family Vineyards staff visited five of their vineyards, filled a bag with soil from each site, and sent it to Phase Genomics to analyze the microbiome in each of the soil samples.

SYMBIOSIS BETWEEN PLANTS AND MICROBES

Plants rely heavily on their microbiome to live, grow, and protect themselves from pathogens. One example of this symbiotic relationship is that plants release chemicals into the soil in order to attract microbes. These microbes bring nutrients such as nitrogen, iron, potassium, and phosphorus to the plants in exchange for sugar, which the microbes require to survive. Microbes also play an important role in nitrogen fixation, organic decay, and biofilm production to protect the plant roots from drought. It is evident that this symbiotic relationship between microbes and plants is critical to the health and survival of both, but further research into this complex community is inhibited by two main problems: It is impossible to isolate microbes in such a complex mix and most of the microbes have never been discovered before.

THE DARK MATTER OF THE MICROBIOME

Microbes live in communities where they rely on each other. This makes it difficult to isolate or culture (i.e. grow) microbes without killing them or altering their genetic makeup. Moreover, there can be millions of microbes living in a single teaspoon of soil, making these samples extremely complex environments. This causes most of the microbial world to be unknown, sometimes referred to as the “Dark Matter of the Microbiome”.

The most effective way to identify the microbes in the community is to look at the genetic makeup of the microbiome to try to classify microbial genomes present. Standard practices include sequencing of 16S (a hypervariable genomic region) and shotgun sequencing.  By combining these standard practices with Hi-C, researchers are now able to fully reconstruct genomes from a mix because Hi-C captures the DNA within each microbe to exploit key genetic features unique to each individual in the community. The Phase Genomics Hi-C kit and software, ProxiMetaTM, uses this information to capture even novel genomes straight from the sample without culturing—illuminating the dark matter of the microbiome.

THE PROCEDURE

Shotgun Sequencing Procedure and Difficulties

Figure 1: Shotgun Sequencing Procedure and Difficulties

Once the soil samples were collected from the five vineyards, Phase Genomics produced shotgun libraries to obtain DNA from all of the microbes in each sample (Figure 1)—essentially taking the soil sample, breaking open all of the microbial cells then purifying the DNA (1.A). Since DNA is fragile, most of it gets broken into smaller pieces during this process, leaving a mix of many DNA fragments from all of the microbes that were present in the original soil sample. The fragmented DNA is then sequenced and the “sequence reads” are uploaded into a database of known microbial genomes (1.B). This database then searches for matches or “hits” to see if the reads are similar to anything in the database (1.C).

A problem with relying on shotgun data is that it’s unclear which DNA fragments belong to which microbe, thus relying heavily on computational techniques and the accuracy of the reference database for classification. This results in little improvement or clarity on the makeup of the sample, again, leaving the microbiome in the dark. Though shotgun sequencing only provides a glimpse into the microbial community, this data allows scientists to differentiate the taxonomy (phyla, genera, species) of the microorganisms living in the soil.

THE RESULTS

Shotgun sequencing identified over 10,000 different species from each of the vineyard soil samples; however, it is impossible to know if this is the true number of species because only ~ 20% of the reads matched the database, indicating ~80% was either incomplete or undiscovered (see table below).

Table 1: Vineyard Read Classification
Vineyard Total Reads Percent of Reads Classified Number of Organisms Found Percent of Unknown Organisms
Canyon 19,001,222 15.95% 10,726 73.32%
Canoe Ridge 21,214,190 17.66% 11,721 55.55%
Waterbrook 19,469,954 19.6% 10,782 50.58%
Skyfall 63,850,810 16.17% 15,101 80.08%
Willow Crest 43,941,026 17.13% 13,914 71.84%

 

Moreover, of assigned reads, >50% did not match to a genus or species—hinting that many of the organisms found are novel. Without digging too deep into the microbiome analysis, it is evident that the microbial makeup is different for each of the samples. Varying levels of reads from each vineyard were able to be classified (Table 1), and among the classified reads, the vineyards have 3-4 microbes that vary in abundance in common. These microbes, such as Proteobacteria, Rhizobacteria, and Actinobacteria, generally, are very common in soil.

Proteobacteria

Proteobacteria

There are obvious differences in the biodiversity of the soil samples both in number of species and relative abundance. For example, Canoe Ridge and Waterbrook samples were >20%, Delftia, while the microbes in the other vineyards were more evenly distributed, with abundance closer to 1-5%. Interestingly, Delftia, a rod-shaped bacterium, has the ability to break down toxic chemicals and to produce gold.

Actinobacteria

Actinobacteria

There are two main components that influence microbe classification in these samples: the desired taxonomy level, and the statistical threshold, or minimum number of reads, set to define it. Much like zooming in and out, the most “zoomed out” analysis is achieved by a stringent threshold and will reveal phylum, while the most “zoomed in” analysis is achieved by a more lenient threshold and will reveal genus and species

If the data is “zoomed in” further, about 37% of the microbes in each community can be identified by genus. On average, 63% of the communities do not match to a genus at all, hinting that these microbes may have never been sequenced. The most abundant microbe genera present in these samples are Bradyrhizobium, Streptomyces, and Nocardiodes.

As discussed earlier, this data highlights the issues that are present with shotgun data and the corresponding analysis: there is still far too much that is unknown. In order to better understand these samples, we also performed Hi-C on two of the samples which will be discussed in further detail in the next section.

 

HI-C AND FINDING NOVEL GENOMES

One thing all these soil samples have in common is that they are composed of numerous novel species. To obtain more information on the microbes present in these samples, and solve the issue discussed earlier surrounding shotgun data, Hi-C was performed on two of the soil samples, Skyfall and Willow Crest. Essentially, Hi-C assigns DNA fragments from shotgun sequencing to the correct species by connecting DNA while the cells are still intact.

Hi-C enables clustering of shotgun assemblies and subsequently yields complete genomes from a microbiome, even if the genome has never been sequenced before. With complete microbe genomes, it becomes easier to classify organisms down to the strain-level—a step even further than species. By having the genome, we can essentially read a microorganism’s blueprint and learn more about its genes, evolution, and even function once the genome is annotated.

For example, preliminary data from the Willow Crest soil sample yielded 400 different genome clusters. When compared to known bacterial genomes in the RefSeq database, which aggregates all published microbial genomic data, over half of the extracted genomes are unable to be identified at a genus level and thus likely represent newly discovered bacterial organisms.

SCIENCE UNCORKED

When the microbiome data from the vineyards were presented to the public at the Pacific Science Center, two questions consistently arose: How does this influence wine taste, and how can growers select for a healthy microbiome? These very forward-thinking questions unfortunately cannot be answered—yet.

Scientists do know that soil plays a big role in plant health, and this could in part be due to the plants’ symbiotic relationship with microbes, as discussed earlier. It has also been shown that biodiversity can benefit plants because of the diverse functions individual microbes have, i.e. with more microbes, there are more potential functions being served versus 1 microbe serving one function. However, nailing down answers to these questions will take a lot of research. With emerging technologies, like Hi-C, the answers have become much more obtainable.

Though the term “microbiome” may not be household vocabulary, many of the attendees were very aware about the role that microbes play in human health, and how they influence the world around us. It goes to show that the rapid developments in the microbiome field are reaching beyond just research and becoming more tangible for the general public. Relevant stories—like looking into the microbiome of vineyards— are helping them understand the intricate concept of microbial life.

Learn more about ProxiMeta Hi-C and the microbiome by visiting our website www.phasegenomics.com and connect with us on twitter by following @PhaseGenomics

Hi-C solves the problem of linking plasmids to hosts in microbiome samples

Plasmids are hard!

Plasmids are an important part of microbial biology. Plasmid-borne genes can have serious public health consequences by conferring virulence traits or resistance to antibiotic drugs, and can be readily shared among bacterial cells through cell-cell conjugation or other means. In principle, any gene that gives bacterial cells a selective advantage is likely to be shared via plasmids among related cells. For example, so-called “epidemic resistance plasmids” have been instrumental in the rise of multi-drug resistance in pathogenic E. coli and Klebsiella pneumoniae.

However, determining the bacterial hosts of any given plasmid in a sample can be difficult. The classic approach is to isolate host and plasmid together and culture them in the lab. However, in complex samples with numerous organisms, many of which cannot be cultured readily or even where culturing may alter the selection pressure on the organisms of interest, this approach is often impossible. Alternatives like statistical metagenomic approaches also have difficulty with plasmid-host association, as plasmids do not necessarily resemble their host genomes in either abundance or nucleotide composition and single-cell sequencing approaches are expensive and have a limited range of samples and species they can be used on.

Hi-C to the rescue

Fortunately, recent developments in genomic technology have yielded some novel tools that allow us to circumvent this limitation. Hi-C is a method that allows us to measure 3-dimensional distances between sequences inside intact cells and was originally developed to model 3D folding of genomes inside cells. These structural measurements include a clear signal about which sequences originated inside the same cell simply because the cell membrane generally prevents inter-cellular sequences from coming into contact. Hi-C therefore provides direct physical evidence of DNA sequences originating from the same cell.

Phase Genomics has developed the ProxiMeta™ Hi-C metagenome deconvolution method, which is specifically optimized for metagenomic applications (Figure 1). At Phase Genomics we use ProxiMeta Hi-C to reconstruct whole genomes from a variety of complex samples such as human fecal, wastewater, soil, and co-culture communities (for more information, see our paper about ProxiMeta).

 

Figure 1. Schematic of ProxiMeta Hi-C. (a) Hi-C crosslinking junctions will form only between sequences in the same cell. (b) Proximity-ligation creates chimeric Hi-C junctions between adjacent DNA molecules which can be directly observed by paired-end sequencing. (c) clustering methods can be used to infer the starting genomes based on the Hi-C junction information. Originally published here.

 

As a necessary part of their life cycle, plasmids need to pass through their bacterial host cells to replicate. Therefore, plasmids typically form Hi-C links to their host genomes simply by virtue of being inside the same cell as their host genome. So, to find the hosts of a given plasmid,  one only needs to find these plasmid-genome links. Our analysis of metagenomic Hi-C data bears this conclusion out repeatedly through multiple publications, as described below.

Hi-C links plasmids and hosts

A pair of early publications showed that using this method we could correctly associate several plasmids with their bacterial hosts in an artificial community using and early version of the Hi-C  method.

In our more recent paper, we have demonstrated that Hi-C links between plasmids and hosts in a complex human fecal sample link described plasmids to their known hosts. Excitingly, in a single experiment we can now assemble numerous novel microbial genomes, complete with plasmid content, from a complex sample with hundreds of different species present.

An exciting finding from this complex community is that we can directly visualize how plasmids are shared between bacteria in a community (Figure 2). Recall from above that the sharing and spread of plasmids is a serious problem in the epidemiology of antibiotic resistance and infectious disease. For example, the sequence marked with “*” in Figure 2 shows substantial similarity to a plasmid called pBUN24, in addition to other plasmids with unknown hosts. It is clear that this plasmid shows contacts with a variety of genome clusters corresponding to different organisms, suggesting that all of these organisms can act as hosts for this plasmid.

 

Figure 2. Heatmap representing quantitative Hi-C links between plasmids (columns) and genome clusters (rows) in a human fecal metagenome. For scale see top right key (blue=no contact). Columns where more than one cell shows signal are possible instances of plasmid sharing. All genome cluster rows are near-complete genomes, e.g. have >90% completeness and <10% redundancy according to CheckM analysis.

 

In a more recent collaboration with Mick Watson’s group at the Roslin Institute, we applied ProxiMeta Hi-C to the cow rumen microbiome, a very complex microbial community. In this peer-reviewed paper, we were able to not only discover scores of novel genomes in this community, but also to profile plasmid-genome linkages for these genomes. Thus, Hi-C linkages of plasmids to genomes are robust even to very high complexity of the community.

Looking to the future: Plasmid Biology conference and more.

We have multiple exciting ongoing collaborations using Hi-C to understand the host range and biology of plasmids and other mobile elements; the best is yet to come! To see several examples of our Hi-C technology applied to this problem, you need only read the abstracts for the 2018 Plasmid Biology conference, August 5-10 at the University of Washington in Seattle.

We will be writing more about the uses of ProxiMeta and metagenomic Hi-C on this blog in the future, so stay tuned.

Lil BUB Aids in Discovery of New Bacteria

Published author, talk show host, movie star, musician, and philanthropist—Lil BUB has now also helped to discover novel microbial life living in her gut in collaboration with AnimalBiome, KittyBiome, and Phase Genomics. Enter to sequence your cat’s microbiome in our #Meowcrobiome twitter raffle!

 

We live in an era of discovery, especially as it relates to the microbiome and how microbial diversity influences our world, our health—and even our pet’s health. To better understand the microbial life of our feline friends, Lil BUB volunteered to sequence her gut microbiome. Thanks to a recent collaboration with AnimalBiome, KittyBiome, and Phase Genomics, Lil BUB helped discover 22 new microbes living in cats which, in time, could reveal new insights into cat health and happiness.

When KittyBiome started back in 2015 with an intent to understand the cat microbiome,  Lil BUB’s owner Mike “Dude” Bridavsky provided a sample of her poop to be analyzed. Because of Lil BUB and over 1,000 other cats, KittyBiome’s microbial census will help us identify what microbes are associated with healthy cats and work towards helping cats with Inflammatory Bowel Disease (IBD), diabetes and other ailments likely to be associated with the microbiome.

 

USING GENOMICS TO FIND MICROBES

Late last year, Phase Genomics offered to analyze samples from Lil BUB and another cat, Danny (belonging to Jennifer Gardy—a microbiologist at the University of British Columbia and science TV host), using our ProxiMeta™ Hi-C Metagenomic Deconvolution platform to obtain complete microbial genomes from their samples.  This method solves a huge problem in microbiome research—how to tell apart different species when their DNA is all mixed up in one sample (imagine a thousand jigsaw puzzles mixed together).

ProxiMeta Hi-C revealed about two hundred different species of microorganisms living in Lil BUB and Danny’s poop, many of which have never been seen before. The genome sequences of the microorganisms found in these samples were analyzed using our software and other microbiome analysis tools to measure the quality of the different assembled genomes and to see if those genomes matched any known microbes (Lil BUB’s and Danny’s data are available for free on our website). Without using our ProxiMeta Hi-C platform to extract these genomes, many of them would have been undetectable and gone unseen.

Lil BUB and Danny the Cat

Phase Genomics sequenced both Lil BUB (left) and Danny’s (right) poop samples.

 

OVER 20 NEW BACTERIAL GENOMES DISCOVERED

Lil BUB being heldTogether, Lil BUB and her buddy Danny carry 22 previously undescribed bacterial species in their guts.  Lil BUB’s poop sample had 13 species and Danny’s sample had 9 species that have never before been fully sequenced or characterized.

These new bacterial species mostly belong to the order Clostridiales, and the team is currently analyzing the genomes to better characterize them. This discovery will help continue to build a database that contains cat bacteria that are new to science, so we can better identify the contributions of the microbiome to various health conditions.

This cool discovery, made with the help of Lil BUB and Danny, highlights that there’s a  universe of undiscovered microbial life out there. If we found 22 potentially novel species in only two cats, just imagine what else is out there, and what the implications might be for new ways to support and improve the health of our pets.

 

WHO ARE OUR HERO CATS?

Lil BUB is a one of a kind critter, made famous on the Internet due to her adorable genetic anomalies. She is a “perma-kitten”, which means she will stay kitten-sized and maintain kitten-like features her entire life. She has an extreme case of dwarfism, which means her limbs are disproportionately small relative to the rest of her body. Her lower jaw is significantly shorter than her upper jaw, and her teeth never grew in so her tongue is always hanging out. Lil BUB is also a polydactyl cat, meaning she has extra toes – 22 toes total!  Lil BUB and Her Dude travel all over the country raising hundreds of thousands of dollars for animals in need.

Danny, an exotic shorthair with a face much like Grumpy Cat, is equally adorable.  He is the companion cat of one of KittyBiome’s original researchers, Jennifer Gardy, and was one of the very first cats to lend his poop profile to the KittyBiome initiative.  He is a very healthy cat and his microbial profile has helped us learn what a balanced gut in cats looks like.

WHAT’S NEXT?

Phase Genomics and AnimalBiome are eager to learn more about these newly-discovered bacterial species. They hope to work with the scientific community to analyze, identify, characterize and publish these genomes, starting with exploring their identities based on 16S rRNA and other marker genes.

HOW TO GET INVOLVED

  • Help characterize the new bacteria: If you know of a researcher, scientist or cat-lover who would like to help us, we are soliciting input on the analysis that needs to be done to properly characterize and publish these genomes. Participants who contribute in a substantive manner to the project will be co-authors on the publication. All data associated with the project will be deposited into publicly available databases and we will publish the findings in open access journals, so all pet lovers can read them. We will hold a raffle to award one lucky contributor a free Hi-C sample kit from Phase Genomics. If interested, contact us at team@animalbiome.com to learn more.
  • Name the new bacteria: We’re looking for input from the community on what we should name these 22 new bacteria, so if you have any fun ideas, please drop us an email at team@animalbiome.com. The format should follow standard practices of scientific nomenclature, so it should be constructed like this: “Clostridium _________.”
  • Submit your pet’s sample for genomic research: If you don’t win the raffle and still want your pet to contribute to scientific knowledge through the identification of new bacterial species, please contact us at team@animalbiome.com. We can provide you with the details and pricing involved for us to identify new species in your cat or dog through in depth analyses like we did for Lil BUB and Danny using the Hi-C approach pioneered by Phase Genomics, which would also result in a publication.

Improving databases of the microbiome of cats (and dogs) with new bacteria like this could help us learn more about how the gut microbiome helps support the digestive health of all pets.

ENTER YOUR CAT IN OUR TWITTER RAFFLE

Phase Genomics, AnimalBiome and KittyBiome are hosting a twitter raffle where you can enter to sequence your cat’s microbiome! All you have to do is go to either the Phase Genomics’ or AnimalBiome’s original tweet of this blog, retweet it with a picture and introduction of your cat with the hashtag #Meowcrobiome. On August 8th 2018, we will randomly draw one (1) winner whose cat poop will be scientifically analyzed by Phase Genomics with ProxiMeta Hi-C to search for novel microbes, and three (3) additional winners whose cat poop will receive a Kitty Kit to have their cat’s poop analyzed by Animal Biome to compare their cat’s gut to healthy cat guts.  Send in your cat’s poop, and you too can help discover new microbial life!

LIL BUB AND DANNY’S STORY FEATURED ON GEEKWIRE PODCAST

GeekWire discussed Lil BUB, Danny, and the new bacteria found in their poop in their weekly Week in Geek podcast. Check out the full podcast on their website (the segment begins around 22:58), or play just the segment about Lil BUB and Danny below.

 

 

New Video: From Contigs to Chromosomes

Phase Genomics CEO and Founder Ivan Liachko, Ph.D. offers an inside look at our ProxiMeta™ Hi-C and Proximo™ Hi-C technology. He explains in this 40 minute presentation how Hi-C is revolutionizing genome and metagenome assembly. Watch “From Contigs to Chromosomes” now and reach out to http://phasegenomics.com/contact-us/ with any questions.

Thanks to IMMSA for hosting this webinar.

Uncovering the microbiome: What will you do with metagenomics?

In this Nature Microbiology blog post, Mick Watson shares his journey into the depths of the rumen microbiome. Read more here to learn how Phase Genomics ProxiMeta Hi-C Metagenomic Deconvolution techniques are helping investigators advance their metagenomic research in complex samples. This study successfully assembled 913 genomes and will help to improve our understanding of the microbial population in cow rumen in an unprecedented way using these new metagenomics techniques. We look forward to seeing what else comes from Microbiome 2.0. and are proud to be a part of this impressive piece of work.

Hundreds of Genomes Isolated from Single Fecal Sample with Hi-C Kit

 

Hi-C Kit Microbiome

A Phase Genomics Hi-C kit for any sample type are now available!

Phase Genomics recently launched its ProxiMeta™ Hi-C metagenome deconvolution kit + software
product, enabling researchers to bring this powerful technology (previously only available through the ProxiMeta service) into their own labs. A new paper posted to biorxiv describes the results of employing ProxiMeta technology to deconvolute a human gut microbiome sample.

 

In the paper, ProxiMeta was used on a single human gut microbiome sample and isolated 252 individual microbial genomes or genome fragments, with 50 of these genomes meeting the “near-complete” threshold typically used as the standard according to the CheckM tool (>90% complete, <10% contaminated). Examining the tRNA and rRNA content of the genomes found 10 to meet “high-quality” and 75 to meet “medium-quality” thresholds. Additionally, 14 of the genomes represent near-complete assemblies of novel species or strains not found in RefSeq, showing that even after many years of research, there remain numerous unknown microbes in the human gut that are discoverable with new approaches.

 

ProxiMeta’s results were compared to those achieved with MaxBin, a common tool used to perform metagenomic binning based on heuristics such as shotgun read depth and tetranucleotide profiles. MaxBin was able to create 29 near-complete genomes (cf. 50 for ProxiMeta), with only 5 meeting high-quality (cf. 10) and 44 meeting medium-quality (cf. 75) thresholds based on tRNA and rRNA content. In terms of ability to construct similar sets of near-complete genomes, ProxiMeta and MaxBin constructed 27 of approximately the same genomes, with ProxiMeta constructing an additional 32 genomes that MaxBin did not, and MaxBin constructing 9 genomes that ProxiMeta did not. ProxiMeta’s assembled genomes also exhibited a much lower amount of contamination than MaxBin’s assembled genomes, with 43% of MaxBin’s assemblies exceeding the 10% contamination limit that is the typical standard for genome quality, compared to only 2% of ProxiMeta’s assemblies.

 

Other results unique to ProxiMeta include the discovery of near-complete genomes for 14 novel species or strains and various associations of plasmids with their hosts. Of the 14 novel genomes, 10 appear to be of the class Clostridia, a common group of gut microbes that are poorly characterized due to their difficulty to culture.  ProxiMeta also assigned 137 contigs containing plasmid content to a cluster and identified candidate plasmid sequences as being present across multiple, distantly related bacteria. For example, ProxiMeta placed a known megaplasmid into an assembly for Eubacterium eligens that included homologous plasmid sequences placed into several other genomes, suggesting either the presence of the megaplasmid into other species, or variants of the megaplasmid being found on other mobile elements spread through the metagenome.

 

The depth of the resulting data and results offers the opportunity to learn much more about this microbial niche and research continues to unlock new discoveries about this community. Phase Genomics is thrilled to be able to offer all researchers the same new power to dig deeper into their mixed samples than ever before, especially now with a product that puts the power of discovery in their hands.

 

To learn more about ordering our kits or services, just send us an email at info@phasegenomics.com