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Antitoxin (T-A), and clustered regularly interspaced short palindromic repeats (CRISPR) systems, for
example, are also encoded in conjugative elements suggesting that to inhibit phage replication [33,98-102] .
Plasmids can also exclude other related plasmids based on incompatibility (inc) types [47,103] . Although inc
types are not traditionally thought of as a form of MGE defense, plasmid populations can be driven into
extinction due to incompatibility [104,105] . It is, therefore, plausible that P-Ps have the greatest genetic potential
in MGE defense since they can both exclude plasmids of the same inc type and also potentially protect
bacteria against phages [106,107] .

CURRENT CHALLENGES AND SOLUTIONS
While accumulating evidence suggests that MGEs can have a profound influence on the bacterial
colonization of the infant gut, deciphering the roles and significance of different MGEs is challenging due to
the inherent genomic characteristics of MGEs. First, the genome mosaicism and large amount of unknown
open reading frames make MGEs and their functions difficult to quantify and characterize in metagenomic
creation of synthetic model bacterial communities
datasets. In particular, robust methodologies to identify and characterize novel P-Ps are urgently needed.
Second, it is technically difficult to ascertain a host for an MGE in metagenomic datasets if the MGE is
integrated into multiple sites or exists extrachromosomally, which is required for tracking its vertical and
horizontal transmission between bacterial taxa.

While finding such signals in metagenomic datasets is challenging, promising sequencing and bioinformatic
approaches are emerging. First, long-read sequencing technologies, such as PacBio and Oxford Nanopore
Technologies (ONT), provide reads long enough to cover both an MGE and an associated bacterial genome.
Additionally, ONT can provide an adaptive sequencing option that could be leveraged to selectively deplete
[108]
non-MGE DNA or amplify MGEs that are at low abundance . Using state-of-the-art bioinformatic tools
combining machine learning and homology-based approaches, such as PlasX, VirSorter, VirFinder, and
geNomad, to identify MGEs can also be used [18,109-111] .

While these technologies enable the identification of several groups of MGEs, establishing the physical
association of extrachromosomal MGEs with their hosts remains challenging. A technique called Hi-C,
which involves fixing and cross-linking DNA molecules with proximity (both chromosomal and
extrachromosomal DNA) followed by sequencing, could be used to resolve this. Moreover, microfluidics
and single-cell sequencing have been used to successfully link extracellular elements, such as phages
undergoing lytic infection and plasmids, to their hosts [112-114] .

Unfortunately, the abovementioned techniques do not provide direct evidence for the identification of P-Ps.
For example, Carjivirus communis phage was only recently confirmed to be a P-P through rigorous
experimentation . Thus, culturing remains a highly relevant technique for identifying and characterizing
[63]
MGEs, as isolating gut bacteria, phages, and other MGEs enables direct experiments in lab cultures and the
[115,116] , which could be used to unravel the ecological and
evolutionary roles of MGEs in model infant gut microbiomes. Finally, organoid and in vivo animal models
with humanized gut microbiomes could provide opportunities to incorporate host cells and immune
[117]
systems with controlled community experiments .

While this perspective focused only on a subset of MGEs, further work should also consider other smaller
MGEs, such as “hitchers”, which are genetic elements that require other MGEs to transfer horizontally
between bacterial hosts . For example, phage satellites can lower the amount of phage particles that their
[118]
helper phage produces upon lytic infection and can encode a wide array of phage defense genes [119-121] . To
fully understand the impact of MGEs in the infant gut, we must consider the whole mobilome, including