From the depths of the ocean to the lining of the human gut, almost every environment on Earth is home to a unique community of microorganisms referred to as a microbiome. Within these communities, unrelated microorganisms can exchange genetic information through a process known as horizontal gene transfer. For example, genes linked to antibiotic resistance are often transferred between different microorganisms, which can create increasingly drug resistant microbes and has important implications for human health.

Horizontal gene transfer has been studied for almost 100 years, but examining it directly is challenging because, almost by definition, it requires studying a community of microbes rather than one microbe in isolation. As such, researchers are looking for simple models of microbial communities that can be easily manipulated in experiments.

Bonham et al. have now turned to the outer surface of cheese, also known as cheese rind, to better understand horizontal gene transfer. As a model system, the cheese rind microbiome is relatively simple to work with because cheese rind is easy to replicate in the laboratory, and the microbes growing on cheese can be grown on their own or in combinations with other microbes. By comparing the genetic material of 165 cheese-associated bacteria to one another, Bonham et al. identified over 4,000 genes that were shared between the bacteria, including several large clusters of genes that were shared by many species.

Many of the identified genes (about 23% to be precise) appear to help the microorganisms acquire nutrients that are known to be in short supply on the surface of cheese surface, including iron. Bacteria typically use specialized molecules called siderophores to scavenge for iron and uptake systems to carry the iron-bound siderophore back into the cell. Notably, only the genes associated with the uptake systems were found in some of the shared gene clusters. This finding suggests that horizontal gene transfer has allowed some microbes to “cheat” and take up iron-bound siderophores without expending energy to produce the siderophores themselves.

Using the cheese rind microbiome as a model system, it becomes possible to explore how horizontal gene transfer works in more detail than before. A better understanding of this process can then be applied to other important microbiomes, including those where genes conferring antibiotic resistance are commonly exchanged.

Great strides have been made in characterizing the composition of microbiomes, and in understanding their importance in the ecology of natural systems, in agriculture and in human health. However, despite these advances, the forces that shape the diversity, structure, and function of microbiomes remain poorly understood (Widder et al., 2016). Investigating these underlying mechanisms in situ is difficult, as observational and sequenced-based analysis rarely enables causal conclusions (Nemergut et al., 2013). Replicating microbial communities in vitro is also an enormous challenge, because of high levels of diversity and the difficulties in establishing pure cultures of most bacterial species. These obstacles significantly hamper our ability to move from observations of microbial diversity to the molecular mechanisms shaping key processes such as species interactions and microbial evolution.

Horizontal gene transfer (HGT) is a major force in microbial evolution and can lead to the wholesale acquisition of novel functions. In some cases, these novel functions can have significant adaptive consequences, such as in the transfer of antibiotic resistance genes (Ochman et al., 2000). HGT also allows rapid adaptation to new niches (Wiedenbeck and Cohan, 2011), as ecologically relevant genes may be acquired by species not previously adapted to a particular niche (Tasse et al., 2010; Hehemann et al., 2010). The movement of microbes to new environments has been shown to increase both the rate and impact of HGT, and HGT is most frequent for genes under positive selection (Niehus et al., 2015). In moving to a new environment, microbes can face novel abiotic conditions (temperature, moisture, salinity, pH, and nutrients) and novel biotic challenges and opportunities resulting from the presence of microbial neighbors.

Evaluating HGT within the context of microbial communities could provide new insights concerning the extent, mechanisms, and ecological impact of this important process. Advances in genome sequencing have begun to provide a glimpse into HGT within environmentally, medically and economically important microbiomes (McDaniel et al., 2010; Andam et al., 2015). For example, extensive gene sharing has been observed throughout the commensal human microbiome, including sharing of genes that enable nutrient acquisition from novel food sources (Hehemann et al., 2010; Smillie et al., 2011), and pathogenicity islands and antibiotic resistance genes in pathogenic microbes (McCarthy et al., 2014; Hiramatsu et al., 2001; Forsberg et al., 2012). There is evidence of extensive HGT in other natural habitats, such as soil (Coombs and Barkay, 2004; Heuer and Smalla, 2012) and aquatic environments (McDaniel et al., 2010; Frischer et al., 1994). Although these studies offer valuable insights into the frequency and potential impact of genes that can be transferred in microbial communities, the complexity of these systems makes difficult any further examination of the effects of these HGT events on their evolution and ecology.

The microbial communities of fermented foods experience strong selection as a result of growing in novel, human-made environments. Previous work has demonstrated that HGT can be a major driver of adaptation in food systems and other human-managed environments (Andam et al., 2015; Rossi et al., 2014). Prior analysis of microbial species from cheese has revealed several instances of HGT in this environment. Lactic acid bacteria (LAB) such as Lactobacillus and Lactococcus, which are used in the initial fermentation of milk, are known to harbor antibiotic resistance genes and may be reservoirs for transfer to pathogenic enterococci (Wang et al., 2006; Mathur and Singh, 2005) and other pathogenic microbes. Other food-associated bacteria may also contribute to antibiotic resistance gene transfer (Cocconcelli et al., 2003; Delorme, 2008; Flórez et al., 2005). In yogurt, another dairy ferment using LAB, HGT of metabolic genes has been observed between protocooperative species L. bulgaricus and S. thermophilus (Li et al., 2013; Liu et al., 2009). Sequencing of Penicillium species isolated from the cheesemaking environment identified HGT of large genomic islands between these key fungal inhabitants of cheese (Cheeseman et al., 2014; Ropars et al., 2015; Gibbons and Rinker, 2015).

During the aging of traditional styles of cheese in caves or aging rooms, bacteria and fungi form a multi-species biofilm called the rind (Button and Dutton, 2012). We have previously shown that these communities can be used to examine community-based processes, such as succession and interspecies interactions, within an experimentally tractable system (Wolfe et al., 2014; Kastman et al., 2016). Given that biofilms such as these are densely populated, and microbes in cheese rinds are under strong selection to obtain limited nutrients (e.g. free amino acids, iron) as well as tolerate cell stress (Monnet et al., 2015), we predicted that HGT might be widespread in cheese rind microbiomes and therefore might provide a useful experimental model for HGT within microbial communities.

We sought to determine the diversity, distribution, and functional content of HGT in bacterial species isolated from cheese rinds. Specifically, we predicted that (1) HGT would be widespread, (2) HGT genes would be enriched for functions related to survival in cheese environment, and (3) there would be uneven distribution of HGT events across taxa. We analyzed the genomes of newly isolated and sequenced cheese-associated bacterial species (31 genomes) and those available in public databases (134 additional genomes). We present data which suggest that there is extensive HGT in cheese-associated bacteria. The regions of DNA identified appear to encode a number of functions which would be expected to provide adaptive advantages within the cheese environment. In particular, we identified three large multi-gene islands that are shared within multiple Actinobacteria, Proteobacteria, and Firmicutes species. These genomic regions are not related, but appear to have analogous functions involving iron acquisition, and are widely distributed in geographically distant cheeses. This work provides foundational knowledge in an experimentally tractable system in which future work could help to provide insight into the role of HGT within microbiomes.

In this paper, we provide evidence of extensive horizontal gene transfer in cheese-associated bacteria. Many of the transferred regions are large multi-gene islands, and are shared by numerous species. Genes involved in nutrient acquisition, especially iron and lactate, are particularly abundant, suggesting that HGT may provide a selective advantage in the iron- and sugar-limited environment of cheese. The largest HGT we identified appears to be an active ICE and is found in a starter culture, raising the possibility that we are observing contemporary processes that may have ongoing importance. These data support previous studies that show HGT is an important factor in the evolution of microbial communities (Wiedenbeck and Cohan, 2011) and suggest that cheese rind communities may provide a useful model for studying this process in greater detail.

For this study, we focused on bacterial members of the cheese microbiome, but many cheeses also contain numerous fungal species. Indeed, HGT has been previously documented in cheese-associated Penicillium species (Cheeseman et al., 2014). HGT between bacteria and fungi has also been documented in other environments, although it is thought to be rare (Keeling and Palmer, 2008). Evaluating bacterial-fungal gene transfer in cheese could provide additional insights into the extent and importance of gene exchange in microbial communities. Further sequencing of bacterial genomes from cheese could also continue to reveal HGT.

We were able to show that ActinoRUSTI in G. arilaitensis JB182 is likely contained within an integrative and conjugative element, although many other mechanisms for transfer are likely at play. Indeed, the appearance of phage-related genes, transposases, and other mobile elements in many HGT groups suggests that we are observing the results of multiple methods for mobilizing DNA.

Our method for identifying HGT does not permit determination of the direction of gene flow, and indeed it seems likely that the original sources of many of these genetic elements are not present in our dataset. In some cases, we can infer a possible origin, such as the Brevibacterium strain in a starter culture that may be the source of RUSTI in multiple cheese species around the world. However, this does not permit identification of where this species acquired them. Further characterization of cheese-associated microbes, as well as those found in dairy farms or in cheese caves may provide a more complete picture, but the evidence that at least some of these genetic elements are found in human pathogens and ocean-dwelling bacteria suggests that genes are shared across diverse environments.

Although previous studies demonstrated that iron is limiting for Glutamicibacter, Brevibacterium, and Corynebacterium species growing on cheese (Monnet et al., 2012, 2010), the preponderance of siderophore and other iron acquisition genes we observed being horizontally transferred suggests that the same is true across bacterial phyla. Limiting iron is a deliberate strategy on the part of mammalian hosts to block the growth of infectious microbes, and this strategy influences the composition of milk because of the presence of lactoferrin (Ellison, 1994). Interestingly, convergent strategies for acquiring iron are used by pathogens and by cheese-associated microbes and we observe that in some cases these disparate species appear to have shared genes through horizontal transfer. The presence of these same genes in a microbe found in ocean habitats suggests that these genes have broad utility for the common challenge of iron limitation.

We have yet to demonstrate the functional consequences of these genes on individual species or on the community as a whole. Given that iron is limiting in cheese, and that ActinoRUSTI genes are upregulated in response to other species (Figure 4C), it is likely that these genes are functional and may play a role in competition. The prevalence of siderophore import, but not siderophore synthesis pathways suggests that species may cheat by scavenging the biosynthetic products of others (Cordero et al., 2012).

The identification of widespread sharing of genes in cheese microbial communities could have important implications. In particular, the possibility that a starter culture is the source of mobile gene elements suggests that the genomic content, rather than just specific species, must be considered when designing microbial supplements. In addition to starter cultures used for fermented foods, living microbial supplements (‘probiotics’) are increasingly being adopted in agriculture (Verschuere et al., 2000; Chaucheyras-Durand and Durand, 2010) and for a wide range of human health conditions (Cuello-Garcia et al., 2015; Onubi et al., 2015; (IBS Dietetic Guideline Review Group on behalf of Gastroenterology Specialist Group of the British Dietetic Association) et al., 2016), and even as cosmetics (Whitlock et al., 2016). The need to screen for clinically relevant elements such as antibiotic resistance genes is widely recognized (Sanders et al., 2010), but other mobile gene elements from these organisms may also enter native microbial populations with unknown consequences.

Although we and others have observes a large number of HGT events in microbial species across a diverse range of environments (McDaniel et al., 2010; Smillie et al., 2011; Ravenhall et al., 2015), the biotic and abiotic conditions that affect this frequency, and what effects HGT may have on the community remain unclear. A model system to study HGT in a community context is particularly important, as sequence-based characterization of complex communities has particular limitations when it comes to HGT. Further, even if complete characterization in situ were possible, many microbial communities are difficult to experimentally manipulate in vitro.

By contrast, cheese rind-associated bacteria are readily isolated and cultured, and model communities may enable identification of features of microbial communities and their environments that alter frequency and extent of HGT. The cheese rind model system provides an opportunity to observe HGT as it happens and to investigate how community composition affects the frequency of transfer and the persistence of genes. The in vitro cheese system enables experimental manipulation to investigate the role of community composition in driving HGT. Further, as many gene products may only have survival benefits in the context of community competition and cooperation, investigating the role of RUSTI and other horizontally transferred genes on microbial growth in the context of their natural community is critical. Having an experimentally tractable microbial community will allow us to test these ideas under controlled conditions in the laboratory and generate predictions about how these processes work in more complex natural systems. Many species of cheese-associated bacteria have close relatives in the soil, on skin, in the ocean, making insight from this system potentially applicable to diverse environments. In addition, horizontal acquisition of iron-uptake genes has been documented in numerous environments including the oceans and in human pathogens (Gyles and Boerlin, 2014; Richards et al., 2009), suggesting that the specific processes occurring in cheese may also be generally informative across systems. Understanding the extent of HGT in the cheese microbiome is the first step towards addressing how the movement of genes shapes, and is shaped by, a microbial community. Using cheese rinds as a model system could help elucidate the factors that influence the frequency of HGT, how it impacts competition and cooperation, and helps shape a microbiome.

1. 1. Bonham KS
   2. Wolfe BE
   3. Dutton RJ

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2. 1. Bonham KS
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1. 1. Wolfe BE
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   (2014) shotgun metagenomic data from cheese rinds used in Figure 4

   Publicly available at MG-RAST (accession no: 4524487.3).

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2. 1. Wolfe BE
   2. Dutton RJ

   (2014) shotgun metagenomic data from cheese rinds used in Figure 4

   Publicly available at MG-RAST (accession no: 4524500.3).

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3. 1. Wolfe BE
   2. Dutton RJ

   (2014) shotgun metagenomic data from cheese rinds used in Figure 4

   Publicly available at MG-RAST (accession no: 4524498.3).

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4. 1. Wolfe BE
   2. Dutton RJ

   (2014) shotgun metagenomic data from cheese rinds used in Figure 4

   Publicly available at MG-RAST (accession no: 4524496.3).

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   (2014) shotgun metagenomic data from cheese rinds used in Figure 4

   Publicly available at MG-RAST (accession no: 4524502.3).

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   (2014) shotgun metagenomic data from cheese rinds used in Figure 4

   Publicly available at MG-RAST (accession no: 4524495.3).

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   (2014) shotgun metagenomic data from cheese rinds used in Figure 4

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   (2014) shotgun metagenomic data from cheese rinds used in Figure 4

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   (2014) shotgun metagenomic data from cheese rinds used in Figure 4

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    (2014) shotgun metagenomic data from cheese rinds used in Figure 4

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13. 1. Wolfe BE
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    (2014) shotgun metagenomic data from cheese rinds used in Figure 4

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14. 1. Wolfe BE
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Author details

1. Kevin S Bonham

   Division of Biological Sciences, University of California, San Diego, San Diego, United States

   Contribution

   KSB, Conceptualization, Investigation, Writing—original draft, Writing—review and editing

   Competing interests

   The authors declare that no competing interests exist.

   "This ORCID iD identifies the author of this article:" 0000-0003-3200-7533

2. Benjamin E Wolfe

   Department of Biology, Tufts University, Medford, United States

   Contribution

   BEW, Conceptualization, Investigation, Writing—review and editing

   Competing interests

   The authors declare that no competing interests exist.

3. Rachel J Dutton

   1. Division of Biological Sciences, University of California, San Diego, San Diego, United States
   2. Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, San Diego, United States

   Contribution

   RJD, Conceptualization, Investigation, Writing—original draft, Writing—review and editing

   For correspondence

   rjdutton@ucsd.edu

   Competing interests

   The authors declare that no competing interests exist.

   "This ORCID iD identifies the author of this article:" 0000-0002-2944-2182

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