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γ with a growth-rate–independent tr
γ with a growth-rate–independent translation speed (1). This interpretation
is consistent with the observation that the slope is
changed in mutants with slow ribosomes, with a strong correlation
between the inverse slopes and the corresponding
translation speeds measured in vitro (11). Nevertheless, that
interpretation stood in contradiction to direct measurements in
E. coli that indicate a dependence of the translation speed on
growth rate (23–25) (Fig. 1B). Our discussion of the fourcomponent
model above (Eq. 9) shows that the growth law of
Fig. 1A is consistent with a growth-rate–dependent translation
speed, with the modified interpretation that the slope in Fig. 1A
be identified with a growth-rate–independent maximal translation
speed, γmax (Eq. 6). The modified interpretation remains
consistent with the slope-speed correlation for the slow ribosome
mutants. In fact, the need for such modified interpretation is also
obtained by asking for a functional form of γ(λ) that is compatible
with the linear relation between ribosome concentration and
growth rate. This argument, which is made in SI Text, leads to a
Michaelis–Menten-type dependence of the translation speed on
growth rate (Eq. 9 without the nonlinear term, included as the
black line in Fig. 1B with parameters given in Table S1).
Quantitative phenomenology provides a powerful approach for
predicting physiological responses to a variety of perturbations
(11) and for uncovering regulatory links within their physiological
context (33). However, our present study indicates that care must
be taken when assigning a mechanistic interpretation to the empirical
parameters appearing in such models. Coarse graining can
bring into focus relations that are not apparent in rich datasets;
nevertheless, coarse graining is a projection of the underlying
dynamics of the system, and different (and, possibly, mutually
contradictory) mechanistic models may be consistent with a particular
set of phenomenological relations.
Concluding Remarks. In this study, we have derived an explicit
model for proteome partitioning that accounts for the fact that
an increase of the translation speed incurs a cost to the cell in the
form of required protein such as elongation factors and tRNA
synthetases. This fraction of the total protein mass that is devoted
to the maintenance of the translation speed is ultimately
governed by the slow diffusion of the large ternary complexes
in a crowded cytoplasm. Furthermore, the analysis resolves the
apparent discrepancy between a very successful phenomenological
framework for understanding the interdependence of
cell growth and gene expression based on the linear relation
between ribosome concentration and growth rate (which is
naturally interpreted as reflecting a constant translation speed)
on the one hand and the measured growth rate dependence of
the translation speed on the other hand. We have shown that
a growth-rate dependence of the translation speed is consistent with
the phenomenological approach and results in only a modified interpretation
of the parameters.
The limitation of the Michaelis constant for ternary complex–
ribosome binding by slow diffusion points toward a key role for
molecular crowding in proteomic resource allocation and cell
growth. In bacterial cells, the degree of crowding (or the water
content of a cell) can be varied via the osmolarity of the growth
is consistent with the observation that the slope is
changed in mutants with slow ribosomes, with a strong correlation
between the inverse slopes and the corresponding
translation speeds measured in vitro (11). Nevertheless, that
interpretation stood in contradiction to direct measurements in
E. coli that indicate a dependence of the translation speed on
growth rate (23–25) (Fig. 1B). Our discussion of the fourcomponent
model above (Eq. 9) shows that the growth law of
Fig. 1A is consistent with a growth-rate–dependent translation
speed, with the modified interpretation that the slope in Fig. 1A
be identified with a growth-rate–independent maximal translation
speed, γmax (Eq. 6). The modified interpretation remains
consistent with the slope-speed correlation for the slow ribosome
mutants. In fact, the need for such modified interpretation is also
obtained by asking for a functional form of γ(λ) that is compatible
with the linear relation between ribosome concentration and
growth rate. This argument, which is made in SI Text, leads to a
Michaelis–Menten-type dependence of the translation speed on
growth rate (Eq. 9 without the nonlinear term, included as the
black line in Fig. 1B with parameters given in Table S1).
Quantitative phenomenology provides a powerful approach for
predicting physiological responses to a variety of perturbations
(11) and for uncovering regulatory links within their physiological
context (33). However, our present study indicates that care must
be taken when assigning a mechanistic interpretation to the empirical
parameters appearing in such models. Coarse graining can
bring into focus relations that are not apparent in rich datasets;
nevertheless, coarse graining is a projection of the underlying
dynamics of the system, and different (and, possibly, mutually
contradictory) mechanistic models may be consistent with a particular
set of phenomenological relations.
Concluding Remarks. In this study, we have derived an explicit
model for proteome partitioning that accounts for the fact that
an increase of the translation speed incurs a cost to the cell in the
form of required protein such as elongation factors and tRNA
synthetases. This fraction of the total protein mass that is devoted
to the maintenance of the translation speed is ultimately
governed by the slow diffusion of the large ternary complexes
in a crowded cytoplasm. Furthermore, the analysis resolves the
apparent discrepancy between a very successful phenomenological
framework for understanding the interdependence of
cell growth and gene expression based on the linear relation
between ribosome concentration and growth rate (which is
naturally interpreted as reflecting a constant translation speed)
on the one hand and the measured growth rate dependence of
the translation speed on the other hand. We have shown that
a growth-rate dependence of the translation speed is consistent with
the phenomenological approach and results in only a modified interpretation
of the parameters.
The limitation of the Michaelis constant for ternary complex–
ribosome binding by slow diffusion points toward a key role for
molecular crowding in proteomic resource allocation and cell
growth. In bacterial cells, the degree of crowding (or the water
content of a cell) can be varied via the osmolarity of the growth
0/5000
γ with a growth-rate–independent translation speed (1). This interpretation
is consistent with the observation that the slope is
changed in mutants with slow ribosomes, with a strong correlation
between the inverse slopes and the corresponding
translation speeds measured in vitro (11). Nevertheless, that
interpretation stood in contradiction to direct measurements in
E. coli that indicate a dependence of the translation speed on
growth rate (23–25) (Fig. 1B). Our discussion of the fourcomponent
model above (Eq. 9) shows that the growth law of
Fig. 1A is consistent with a growth-rate–dependent translation
speed, with the modified interpretation that the slope in Fig. 1A
be identified with a growth-rate–independent maximal translation
speed, γmax (Eq. 6). The modified interpretation remains
consistent with the slope-speed correlation for the slow ribosome
mutants. In fact, the need for such modified interpretation is also
obtained by asking for a functional form of γ(λ) that is compatible
with the linear relation between ribosome concentration and
growth rate. This argument, which is made in SI Text, leads to a
Michaelis–Menten-type dependence of the translation speed on
growth rate (Eq. 9 without the nonlinear term, included as the
black line in Fig. 1B with parameters given in Table S1).
Quantitative phenomenology provides a powerful approach for
predicting physiological responses to a variety of perturbations
(11) and for uncovering regulatory links within their physiological
context (33). However, our present study indicates that care must
be taken when assigning a mechanistic interpretation to the empirical
parameters appearing in such models. Coarse graining can
bring into focus relations that are not apparent in rich datasets;
nevertheless, coarse graining is a projection of the underlying
dynamics of the system, and different (and, possibly, mutually
contradictory) mechanistic models may be consistent with a particular
set of phenomenological relations.
Concluding Remarks. In this study, we have derived an explicit
model for proteome partitioning that accounts for the fact that
an increase of the translation speed incurs a cost to the cell in the
form of required protein such as elongation factors and tRNA
synthetases. This fraction of the total protein mass that is devoted
to the maintenance of the translation speed is ultimately
governed by the slow diffusion of the large ternary complexes
in a crowded cytoplasm. Furthermore, the analysis resolves the
apparent discrepancy between a very successful phenomenological
framework for understanding the interdependence of
cell growth and gene expression based on the linear relation
between ribosome concentration and growth rate (which is
naturally interpreted as reflecting a constant translation speed)
on the one hand and the measured growth rate dependence of
the translation speed on the other hand. We have shown that
a growth-rate dependence of the translation speed is consistent with
the phenomenological approach and results in only a modified interpretation
of the parameters.
The limitation of the Michaelis constant for ternary complex–
ribosome binding by slow diffusion points toward a key role for
molecular crowding in proteomic resource allocation and cell
growth. In bacterial cells, the degree of crowding (or the water
content of a cell) can be varied via the osmolarity of the growth
is consistent with the observation that the slope is
changed in mutants with slow ribosomes, with a strong correlation
between the inverse slopes and the corresponding
translation speeds measured in vitro (11). Nevertheless, that
interpretation stood in contradiction to direct measurements in
E. coli that indicate a dependence of the translation speed on
growth rate (23–25) (Fig. 1B). Our discussion of the fourcomponent
model above (Eq. 9) shows that the growth law of
Fig. 1A is consistent with a growth-rate–dependent translation
speed, with the modified interpretation that the slope in Fig. 1A
be identified with a growth-rate–independent maximal translation
speed, γmax (Eq. 6). The modified interpretation remains
consistent with the slope-speed correlation for the slow ribosome
mutants. In fact, the need for such modified interpretation is also
obtained by asking for a functional form of γ(λ) that is compatible
with the linear relation between ribosome concentration and
growth rate. This argument, which is made in SI Text, leads to a
Michaelis–Menten-type dependence of the translation speed on
growth rate (Eq. 9 without the nonlinear term, included as the
black line in Fig. 1B with parameters given in Table S1).
Quantitative phenomenology provides a powerful approach for
predicting physiological responses to a variety of perturbations
(11) and for uncovering regulatory links within their physiological
context (33). However, our present study indicates that care must
be taken when assigning a mechanistic interpretation to the empirical
parameters appearing in such models. Coarse graining can
bring into focus relations that are not apparent in rich datasets;
nevertheless, coarse graining is a projection of the underlying
dynamics of the system, and different (and, possibly, mutually
contradictory) mechanistic models may be consistent with a particular
set of phenomenological relations.
Concluding Remarks. In this study, we have derived an explicit
model for proteome partitioning that accounts for the fact that
an increase of the translation speed incurs a cost to the cell in the
form of required protein such as elongation factors and tRNA
synthetases. This fraction of the total protein mass that is devoted
to the maintenance of the translation speed is ultimately
governed by the slow diffusion of the large ternary complexes
in a crowded cytoplasm. Furthermore, the analysis resolves the
apparent discrepancy between a very successful phenomenological
framework for understanding the interdependence of
cell growth and gene expression based on the linear relation
between ribosome concentration and growth rate (which is
naturally interpreted as reflecting a constant translation speed)
on the one hand and the measured growth rate dependence of
the translation speed on the other hand. We have shown that
a growth-rate dependence of the translation speed is consistent with
the phenomenological approach and results in only a modified interpretation
of the parameters.
The limitation of the Michaelis constant for ternary complex–
ribosome binding by slow diffusion points toward a key role for
molecular crowding in proteomic resource allocation and cell
growth. In bacterial cells, the degree of crowding (or the water
content of a cell) can be varied via the osmolarity of the growth
Sedang diterjemahkan, harap tunggu..
γ dengan kecepatan terjemahan pertumbuhan tingkat independen (1). Interpretasi ini
konsisten dengan pengamatan bahwa kemiringan yang
berubah dalam mutan dengan ribosom lambat, dengan korelasi yang kuat
antara lereng terbalik dan sesuai
kecepatan terjemahan diukur in vitro (11). Namun demikian, bahwa
penafsiran berdiri dalam kontradiksi langsung pengukuran di
E. coli yang menunjukkan ketergantungan kecepatan penjabaran
tingkat pertumbuhan (23-25) (Gambar. 1B). Diskusi kita tentang fourcomponent
model di atas (Persamaan. 9) menunjukkan bahwa hukum pertumbuhan
Gambar. 1A konsisten dengan terjemahan pertumbuhan tergantung tingkat
kecepatan, dengan interpretasi dimodifikasi bahwa kemiringan pada Gambar. 1a
diidentifikasi dengan terjemahan maksimal pertumbuhan tingkat independen
kecepatan, γmax (Persamaan. 6). Interpretasi dimodifikasi tetap
konsisten dengan korelasi kemiringan kecepatan untuk ribosom lambat
mutan. Bahkan, kebutuhan untuk interpretasi dimodifikasi tersebut juga
diperoleh dengan meminta bentuk fungsional γ (λ) yang kompatibel
dengan hubungan linier antara konsentrasi ribosom dan
tingkat pertumbuhan. Argumen ini, yang dibuat di SI Teks, mengarah ke
ketergantungan Michaelis Menten-tipe dari kecepatan penjabaran
tingkat pertumbuhan (Persamaan. 9 tanpa jangka nonlinear, termasuk sebagai
garis hitam pada Gambar. 1B dengan parameter yang diberikan dalam Tabel S1 ).
fenomenologi kuantitatif memberikan pendekatan yang kuat untuk
memprediksi respon fisiologis terhadap berbagai gangguan
(11) dan untuk mengungkap Link peraturan dalam fisiologis mereka
konteks (33). Namun, studi kami ini menunjukkan bahwa perawatan harus
diambil ketika menetapkan interpretasi mekanistik ke empiris
parameter yang muncul dalam model tersebut. Kembang kayu Kasar dapat
membawa ke dalam hubungan fokus yang tidak jelas dalam dataset kaya,
namun, kembang kayu kasar adalah proyeksi yang mendasari
dinamika sistem, dan berbeda (dan, mungkin, saling
bertentangan) model mekanistik mungkin konsisten dengan tertentu
set hubungan fenomenologis.
Penutup. Dalam studi ini, kami telah diturunkan eksplisit
model untuk proteoma partisi yang bertanggung jawab atas fakta bahwa
peningkatan kecepatan penerjemahan menimbulkan biaya ke sel dalam
bentuk protein yang diperlukan seperti faktor elongasi dan tRNA
sintetase. Ini sebagian kecil dari total massa protein yang dikhususkan
untuk pemeliharaan kecepatan penerjemahan pada akhirnya
diatur oleh difusi lambat dari kompleks terner besar
dalam sitoplasma ramai. Selain itu, analisis menyelesaikan
Perbedaan yang terlihat antara fenomenologis sangat sukses
kerangka kerja untuk memahami saling ketergantungan
pertumbuhan sel dan ekspresi gen berdasarkan hubungan linier
antara konsentrasi ribosom dan tingkat pertumbuhan (yang
secara alami ditafsirkan sebagai mencerminkan kecepatan konstan terjemahan)
pada satu tangan dan diukur ketergantungan laju pertumbuhan
kecepatan penerjemahan di sisi lain. Kami telah menunjukkan bahwa
ketergantungan pertumbuhan laju kecepatan penerjemahan konsisten dengan
pendekatan fenomenologis dan hasil hanya dalam interpretasi dimodifikasi
parameter.
Keterbatasan dari konstanta Michaelis untuk complex- terner
ribosom mengikat oleh titik-titik difusi lambat ke arah peran kunci untuk
crowding molekul dalam alokasi sumber daya proteomik dan sel
pertumbuhan. Dalam sel-sel bakteri, tingkat berkerumun (atau air
isi sel) dapat divariasikan melalui osmolaritas pertumbuhan
konsisten dengan pengamatan bahwa kemiringan yang
berubah dalam mutan dengan ribosom lambat, dengan korelasi yang kuat
antara lereng terbalik dan sesuai
kecepatan terjemahan diukur in vitro (11). Namun demikian, bahwa
penafsiran berdiri dalam kontradiksi langsung pengukuran di
E. coli yang menunjukkan ketergantungan kecepatan penjabaran
tingkat pertumbuhan (23-25) (Gambar. 1B). Diskusi kita tentang fourcomponent
model di atas (Persamaan. 9) menunjukkan bahwa hukum pertumbuhan
Gambar. 1A konsisten dengan terjemahan pertumbuhan tergantung tingkat
kecepatan, dengan interpretasi dimodifikasi bahwa kemiringan pada Gambar. 1a
diidentifikasi dengan terjemahan maksimal pertumbuhan tingkat independen
kecepatan, γmax (Persamaan. 6). Interpretasi dimodifikasi tetap
konsisten dengan korelasi kemiringan kecepatan untuk ribosom lambat
mutan. Bahkan, kebutuhan untuk interpretasi dimodifikasi tersebut juga
diperoleh dengan meminta bentuk fungsional γ (λ) yang kompatibel
dengan hubungan linier antara konsentrasi ribosom dan
tingkat pertumbuhan. Argumen ini, yang dibuat di SI Teks, mengarah ke
ketergantungan Michaelis Menten-tipe dari kecepatan penjabaran
tingkat pertumbuhan (Persamaan. 9 tanpa jangka nonlinear, termasuk sebagai
garis hitam pada Gambar. 1B dengan parameter yang diberikan dalam Tabel S1 ).
fenomenologi kuantitatif memberikan pendekatan yang kuat untuk
memprediksi respon fisiologis terhadap berbagai gangguan
(11) dan untuk mengungkap Link peraturan dalam fisiologis mereka
konteks (33). Namun, studi kami ini menunjukkan bahwa perawatan harus
diambil ketika menetapkan interpretasi mekanistik ke empiris
parameter yang muncul dalam model tersebut. Kembang kayu Kasar dapat
membawa ke dalam hubungan fokus yang tidak jelas dalam dataset kaya,
namun, kembang kayu kasar adalah proyeksi yang mendasari
dinamika sistem, dan berbeda (dan, mungkin, saling
bertentangan) model mekanistik mungkin konsisten dengan tertentu
set hubungan fenomenologis.
Penutup. Dalam studi ini, kami telah diturunkan eksplisit
model untuk proteoma partisi yang bertanggung jawab atas fakta bahwa
peningkatan kecepatan penerjemahan menimbulkan biaya ke sel dalam
bentuk protein yang diperlukan seperti faktor elongasi dan tRNA
sintetase. Ini sebagian kecil dari total massa protein yang dikhususkan
untuk pemeliharaan kecepatan penerjemahan pada akhirnya
diatur oleh difusi lambat dari kompleks terner besar
dalam sitoplasma ramai. Selain itu, analisis menyelesaikan
Perbedaan yang terlihat antara fenomenologis sangat sukses
kerangka kerja untuk memahami saling ketergantungan
pertumbuhan sel dan ekspresi gen berdasarkan hubungan linier
antara konsentrasi ribosom dan tingkat pertumbuhan (yang
secara alami ditafsirkan sebagai mencerminkan kecepatan konstan terjemahan)
pada satu tangan dan diukur ketergantungan laju pertumbuhan
kecepatan penerjemahan di sisi lain. Kami telah menunjukkan bahwa
ketergantungan pertumbuhan laju kecepatan penerjemahan konsisten dengan
pendekatan fenomenologis dan hasil hanya dalam interpretasi dimodifikasi
parameter.
Keterbatasan dari konstanta Michaelis untuk complex- terner
ribosom mengikat oleh titik-titik difusi lambat ke arah peran kunci untuk
crowding molekul dalam alokasi sumber daya proteomik dan sel
pertumbuhan. Dalam sel-sel bakteri, tingkat berkerumun (atau air
isi sel) dapat divariasikan melalui osmolaritas pertumbuhan
Sedang diterjemahkan, harap tunggu..
Bahasa lainnya
Dukungan alat penerjemahan: Afrikans, Albania, Amhara, Arab, Armenia, Azerbaijan, Bahasa Indonesia, Basque, Belanda, Belarussia, Bengali, Bosnia, Bulgaria, Burma, Cebuano, Ceko, Chichewa, China, Cina Tradisional, Denmark, Deteksi bahasa, Esperanto, Estonia, Farsi, Finlandia, Frisia, Gaelig, Gaelik Skotlandia, Galisia, Georgia, Gujarati, Hausa, Hawaii, Hindi, Hmong, Ibrani, Igbo, Inggris, Islan, Italia, Jawa, Jepang, Jerman, Kannada, Katala, Kazak, Khmer, Kinyarwanda, Kirghiz, Klingon, Korea, Korsika, Kreol Haiti, Kroat, Kurdi, Laos, Latin, Latvia, Lituania, Luksemburg, Magyar, Makedonia, Malagasi, Malayalam, Malta, Maori, Marathi, Melayu, Mongol, Nepal, Norsk, Odia (Oriya), Pashto, Polandia, Portugis, Prancis, Punjabi, Rumania, Rusia, Samoa, Serb, Sesotho, Shona, Sindhi, Sinhala, Slovakia, Slovenia, Somali, Spanyol, Sunda, Swahili, Swensk, Tagalog, Tajik, Tamil, Tatar, Telugu, Thai, Turki, Turkmen, Ukraina, Urdu, Uyghur, Uzbek, Vietnam, Wales, Xhosa, Yiddi, Yoruba, Yunani, Zulu, Bahasa terjemahan.
- C
- kok tidak di balas
- semua kenangan di estico, yang aku lalui
- Sekolah ini merupakan sekolah yang berna
- C
- Tempat ini adalah tempat yang saya angga
- mempunyai keinginan belajar yang tinggi
- Karena saya tidak punya pulsa
- I love you
- Sebab saya tidak punya pulsa
- I love you
- Tolong
- have a desire to learn
- Tolong
- Bagaimana kabar dan keadaanmu sekarang?
- Strain
- Sekolah ini merupakan sekolah yang berna
- Sayang aku hanpond nya rusak jadi sement
- daun sirih, jeruk nipis, dan garam1. dau
- Amor vou tomar banho para e me arrumar p
- Bagaimana kabar dan keadaanmu sekarang?
- dear had lunch in college.
- semua kenangan di estico, yang aku lalui
- Mengejar sebuah kesetian dan menepati se
