Overview of the application of microbiome in individual identification, geolocation inference, and PMI estimation
Application . | Application foundation . | Classification . | Refs. . |
---|---|---|---|
Individual identification | Strong variations in community membership between individuals, some of these variations are stable over time | Main tissue origins: skin, oral, gut, and vaginal hair | [7,55,57,59,62–64,66–68] |
The transfer of microbiomes: cohabitating individuals, direct and indirect transfer, sexual contact, single computer keys and mice, and smartphone | [7,57–60] | ||
New markers: clade-specific markers and CRISPR spacers | [62–64,66] | ||
Influencing factors: decay of microbiota traces with time and diurnal patterns of microbiota | [67,68] | ||
Geolocation inference | Microbial communities exhibit a biogeographic pattern | Molecular technologies: TRFLP, DGGE, RISA, and NGS (16S rRNA gene, 18S rRNA gene, metabarcoding, and shotgun metagenomics) | [72–80] |
Sample types: soil, shoe, dust, skin and body fluids, and gut | [60,72–79,81–85] | ||
PMI estimation | The microbiomes that drive mammalian decomposition are somewhat similar and repeatable across different hosts and environments | Animal models: mice, rat, and swine | [20,88–91,93] |
Human cadaver | [20,94] | ||
Sample types: abdomen, skin, scalp, gut, bone, and gravesoil | [20,88–91,93] | ||
External environments: aboveground, burial cadavers, freshwater, indoor, different seasons, and different sites | [20,84,85,88,90,91,93,94] |
Application . | Application foundation . | Classification . | Refs. . |
---|---|---|---|
Individual identification | Strong variations in community membership between individuals, some of these variations are stable over time | Main tissue origins: skin, oral, gut, and vaginal hair | [7,55,57,59,62–64,66–68] |
The transfer of microbiomes: cohabitating individuals, direct and indirect transfer, sexual contact, single computer keys and mice, and smartphone | [7,57–60] | ||
New markers: clade-specific markers and CRISPR spacers | [62–64,66] | ||
Influencing factors: decay of microbiota traces with time and diurnal patterns of microbiota | [67,68] | ||
Geolocation inference | Microbial communities exhibit a biogeographic pattern | Molecular technologies: TRFLP, DGGE, RISA, and NGS (16S rRNA gene, 18S rRNA gene, metabarcoding, and shotgun metagenomics) | [72–80] |
Sample types: soil, shoe, dust, skin and body fluids, and gut | [60,72–79,81–85] | ||
PMI estimation | The microbiomes that drive mammalian decomposition are somewhat similar and repeatable across different hosts and environments | Animal models: mice, rat, and swine | [20,88–91,93] |
Human cadaver | [20,94] | ||
Sample types: abdomen, skin, scalp, gut, bone, and gravesoil | [20,88–91,93] | ||
External environments: aboveground, burial cadavers, freshwater, indoor, different seasons, and different sites | [20,84,85,88,90,91,93,94] |
Note: PMI, post-mortem interval; CRISPR, clustered regularly interspaced short palindromic repeat; TRFLP, terminal restriction fragment length polymorphism; DGGE, denaturing gel electrophoresis; RISA, ribosomal intergenic spacer analysis; NGS, next-generation sequencing.
Overview of the application of microbiome in individual identification, geolocation inference, and PMI estimation
Application . | Application foundation . | Classification . | Refs. . |
---|---|---|---|
Individual identification | Strong variations in community membership between individuals, some of these variations are stable over time | Main tissue origins: skin, oral, gut, and vaginal hair | [7,55,57,59,62–64,66–68] |
The transfer of microbiomes: cohabitating individuals, direct and indirect transfer, sexual contact, single computer keys and mice, and smartphone | [7,57–60] | ||
New markers: clade-specific markers and CRISPR spacers | [62–64,66] | ||
Influencing factors: decay of microbiota traces with time and diurnal patterns of microbiota | [67,68] | ||
Geolocation inference | Microbial communities exhibit a biogeographic pattern | Molecular technologies: TRFLP, DGGE, RISA, and NGS (16S rRNA gene, 18S rRNA gene, metabarcoding, and shotgun metagenomics) | [72–80] |
Sample types: soil, shoe, dust, skin and body fluids, and gut | [60,72–79,81–85] | ||
PMI estimation | The microbiomes that drive mammalian decomposition are somewhat similar and repeatable across different hosts and environments | Animal models: mice, rat, and swine | [20,88–91,93] |
Human cadaver | [20,94] | ||
Sample types: abdomen, skin, scalp, gut, bone, and gravesoil | [20,88–91,93] | ||
External environments: aboveground, burial cadavers, freshwater, indoor, different seasons, and different sites | [20,84,85,88,90,91,93,94] |
Application . | Application foundation . | Classification . | Refs. . |
---|---|---|---|
Individual identification | Strong variations in community membership between individuals, some of these variations are stable over time | Main tissue origins: skin, oral, gut, and vaginal hair | [7,55,57,59,62–64,66–68] |
The transfer of microbiomes: cohabitating individuals, direct and indirect transfer, sexual contact, single computer keys and mice, and smartphone | [7,57–60] | ||
New markers: clade-specific markers and CRISPR spacers | [62–64,66] | ||
Influencing factors: decay of microbiota traces with time and diurnal patterns of microbiota | [67,68] | ||
Geolocation inference | Microbial communities exhibit a biogeographic pattern | Molecular technologies: TRFLP, DGGE, RISA, and NGS (16S rRNA gene, 18S rRNA gene, metabarcoding, and shotgun metagenomics) | [72–80] |
Sample types: soil, shoe, dust, skin and body fluids, and gut | [60,72–79,81–85] | ||
PMI estimation | The microbiomes that drive mammalian decomposition are somewhat similar and repeatable across different hosts and environments | Animal models: mice, rat, and swine | [20,88–91,93] |
Human cadaver | [20,94] | ||
Sample types: abdomen, skin, scalp, gut, bone, and gravesoil | [20,88–91,93] | ||
External environments: aboveground, burial cadavers, freshwater, indoor, different seasons, and different sites | [20,84,85,88,90,91,93,94] |
Note: PMI, post-mortem interval; CRISPR, clustered regularly interspaced short palindromic repeat; TRFLP, terminal restriction fragment length polymorphism; DGGE, denaturing gel electrophoresis; RISA, ribosomal intergenic spacer analysis; NGS, next-generation sequencing.
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