Meta­ge­n­om­ics

Ima­gine a pile of beau­ti­ful books in front of you. Now ima­gine they have been cut into small snip­pets, each con­tain­ing in­di­vidual words and sen­tence frag­ments. You are now given the task of bring­ing or­der to this chaos. The best way to start would be to search for keywords. If the snip­pet says "Ham­let", it prob­ably be­longs to Shakespeare’s work of the same name. And if "new speak" or "Big Brother" comes up, you’re prob­ably deal­ing with George Or­well’s 1984. "Muggles" and "Hog­warts" would clearly point to the Harry Pot­ter series. In this way, you can dig through the pile of pa­per, piece by piece, and try to sort and re­as­semble the snip­pets. If sev­eral cop­ies of the same book have been cut up dif­fer­ently, this makes things a bit easier. Over­lap­ping text frag­ments will give you ad­di­tional clues as to the cor­rect com­pos­i­tion of the texts.

Meta­ge­n­om­ics is­n’t all that dif­fer­ent. In­stead of books, re­search­ers work with the gen­omes of mi­cro-or­gan­isms that they cut up and re­as­semble. The snip­pets are frag­ments of the gen­ome or "se­quence seg­ments". Com­puters can help to as­semble the in­di­vidual parts. There are now ex­cel­lent al­gorithms for deal­ing with such a task. Some se­quence seg­ments are also already known and stored in data­bases. These can help to as­sign cer­tain se­quences to groups of or­gan­isms or func­tions.

With the help of meta­ge­n­om­ics, it is pos­sible to ana­lyse an en­vir­on­mental sample (i.e. a mix­ture of the most di­verse or­gan­isms as they live to­gether in the en­vir­on­ment) and find out which or­gan­isms live in this en­vir­on­ment as well as which genes – and thus meta­bolic path­ways, in­ter­ac­tions, and de­fence strategies – pre­dom­in­ate. This dis­tin­guishes meta-ge­n­om­ics from clas­sical mi­cro­bi­o­lo­gical meth­ods, which spe­cific­ally search for in­di­vidual or­gan­isms (groups) for which the gen­ome se­quences are known. Bioin­form­at­ics refers to the meth­ods used to bring or­der to the meta­ge­n­omic ana­lyses and data.

Meta­ge­n­omic meth­ods also al­low us to identify mi­croor­gan­isms – re­gard­less of whether they can be cul­tured in the labor­at­ory – and thus to study the dy­nam­ics in pop­u­la­tions over days and even years. We can thus gain in­sight into the com­plex­ity and change of the com­munit­ies our mi­cro­scopic co-in­hab­it­ants. However, meta­ge­n­om­ics of­ten can­not stand alone; without clas­sical mi­cro­bi­o­logy, we would be un­able to in­ter­pret the res­ults.

The molecular ecology of algal blooms

For ex­ample, we use meta-ge­n­om­ics to study the de­grad­a­tion of algal blooms in the North Sea: every year in spring, when the days get longer and the sun­light in­creases, many phyto­plank­ton spe­cies mul­tiply rap­idly – and their pop­u­la­tion grows ex­po­nen­tially. These algal blooms are of global im­port­ance for the car­bon cycle. Dur­ing pho­to­syn­thesis, the small al­gae con­vert car­bon di­ox­ide into sugar com­pounds and oxy­gen. Within a few weeks, the al­gae run out of nu­tri­ents, and pred­at­ors spread. The al­gae bloom then col­lapses. The bac­teria then mul­tiply en masse. They de­com­pose the re­main­ing algal bio­mass, and the bound car­bon is largely re­leased in the pro­cess. However, these pro­cesses are still not well un­der­stood. Which mar­ine bac­teria grow when? How do they pro­cess the algal bio­mass and re­lease the car­bon? What pro­cesses are be­hind this?