Analisis identifikasi mikroorganisme

1. Analysis of your 16s and 18s
rRNA

6. STRUKTUR RIBOSOM
• Ribosom adalah komplek molekul yang
berperan dalam sintesis (pembentukan)
protein
• Pada prokariot, ribosom terletak di
sitoplasma
• Pada eukariot, ribosom terletak di
sitoplasma dan permukaan retikulum
endoplasma (RE)

7. • Ribosom tersusun atas
rRNA (ribosomal RNA)
dan protein
• Terdiri atas 2 unit yaitu sub
unit besar dan kecil

9. Struktur Ribosom Prokariot

10. • Pada eukariot (di sitosol):
– Sub unit besar berukuran 40S  terdiri dari
18S rRNA + 33 macam protein
– Sub unit kecil berukuran 60S  terdiri dari 5S
rRNA + 28S rRNA + 5,8S rRNA + 49 macam
protein
• Apabila kedua sub unit ini bergabung
membentuk sub unit 80S

11. Struktur Ribosom Eukariot

12. • Pada prokariot :
– Sub unit besar berukuran 50S  terdiri dari
23S rRNA + 5S rRNA + 34 macam protein
– Sub unit kecil berukuran 30S  terdiri dari
16S rRNA + 21 macam protein
• Apabila kedua sub unit ini bergabung
membentuk sub unit 70S

15. Why we use 18S rRNA
• it is highly conserved intra-species
(similarities close to 100%) and assist
in species-level analyses

16. DNA sequencing
• Most current sequencing projects use the
chain termination method
– Also known as Sanger sequencing, after its
inventor
• Based on action of DNA polymerase
– Adds nucleotides to complementary strand
• Requires template DNA and primer

17. Chain-termination sequencing
• Dideoxynucleotides
stop synthesis
– Chain terminators
• Included in amounts
so as to terminate
every time the base
appears in the
template
• Use four reactions
– One for each base:
A,C,G, and T
3’ ATCGGTGCATAGCTTGT 5’
5’ TAGCCACGTATCGAACA* 3’
5’ TAGCCACGTATCGAA* 3’
5’ TAGCCACGTATCGA* 3’
5’ TAGCCACGTA* 3’
5’ TAGCCA* 3’
5’ TA* 3’
Sequence reaction products
Template

18. Sequence detection
• To detect products of
sequencing reaction
• Include labeled
nucleotides
• Formerly, radioactive
labels were used
• Now fluorescent labels
• Use different fluorescent
tag for each nucleotide
• Can run all four reactions
in same lane
TAGCCACGTATCGAA*
TAGCCACGTATC*
TAGCCACG*
TAGCCACGT*

20. 16S rRNA Sequensing
Bioinformatics

21. Sequence separation
• Terminated chains need
to be separated
• Requires one-base-pair
resolution
– See difference between
chains of X and X+1
base pairs
• Gel electrophoresis
– Very thin gel
– High voltage
– Works with radioactive
or fluorescent labels
–
+
C A G T C A G T

22. Sequence reading of
radioactively labeled reactions
• Radioactive labeled
reactions
– Gel dried
– Placed on X-ray film
• Sequence read from
bottom up
• Each lane is a different
base
A T C G
+
–

23. Capillary electrophoresis
• Newer automated
sequencers use very
thin capillary tubes
• Run all four
fluorescently tagged
reactions in same
capillary
• Can have 96
capillaries running at
the same time
96–well plate
robotic arm and syringe
96 glass capillaries
load bar

24. Sequence reading of
fluorescently labeled reactions
• Fluorescently labeled
reactions scanned by
laser as a particular
point is passed
• Color picked up by
detector
• Output sent directly to
computer

25. Summary of chain termination
sequencing

26. Sequence databases
• What is a database?
– An indexed set of records
– Records retrieved using a query language
– Database technology is well established
• Examples of sequence databases
– GenBank
• Encompasses all publicly available protein and
nucleotide sequences
– Protein Data Bank
• Contains 3-D structures of proteins

27. The biological importance of
sequence alignment
• Sequence alignments assess the degree
of similarity between sequences
• Similar sequences suggest similar function
– Proteins with similar sequences are likely to
play similar biochemical roles
– Regulatory DNA sequences that are similar
will likely have similar roles in gene regulation
• Sequence similarity suggests evolutionary
history
– Fewer differences mean more recent
divergence

28. Sequence alignment
• Sequence alignments
search for matches
between sequences
• Two broad classes of
sequence alignments
– Global
– Local
• Alignment can be
performed between
two or more
sequences
QKESGPSSSYC
VQQESGLVRTTC
Global alignment
Local alignment
ESG
ESG

29. The algorithmic problem of aligning
sequences
• Comparison of similar
sequences of similar
length is
straightforward
• How does one deal
with insertions and
gaps that may hide
true similarity?
• How does one
interpret minimal
similarity?
QQESGPVRSTC
QKGSYQEKGYC
QQESGPVRSTC
RQQEPVRSTC
QQESGPVRSTC
QKESGPSRSYC

30. Methods of sequence alignment
• Graphical methods
• Dynamic-programming methods
• Heuristic methods

31. A practical example of sequence
alignment

32. BLAST results

33. Detailed BLAST results

34. A pairwise alignment with MASH-1
• HASH-2, a human homolog of MASH-1
– “+” indicates conservative amino acid substitution
– “–” indicates gap/insertion
– XXXX… shows areas of low complexity