Which bacteria reproduce asexually

These two strands of DNA are then moved to the different poles of the cell and a transverse septum then takes place and develops in the middle region of the cell which separates the two new daughter cells and thus binary fission I completed. It is a rapid process and takes minutes to complete. Image will be uploaded soon. Conidia Formation: The formation of conidia takes place in filamentous bacteria such as Streptomyces through the formation of a transverse septum at the apex of the filament.

The part bearing the conidia is called the conidiophore and after it is detached from the mother cell, in a suitable substratum it germinates giving rise to new mycelium. This type of asexual reproduction is also called fragmentation. Budding: In this method of reproduction, the bacterial cell develops a small swelling at one side which continuously increases in size.

At the same time, the nucleus also undergoes division where one part with some cytoplasm enters the swelling and the other part remains with the mother cell. The outgrowth is called the bud and it eventually gets separated from the mother cell by a partition wall. This method of reproduction also comes under vegetative reproduction in bacteria.

Example: Rhodomicrobium vannielii. Cysts: Cysts are formed by the deposition of additional layers around the mother cell and are the resting structure during unfavourable conditions. When conditions are favourable again, the mother cell behaves like its normal self again. Past studies of the bacteria E.

But that process involves donating a single segment of DNA that didn't appear throughout the genome. Preproduction Gray and his colleagues came across an obscure s report on DNA transfer in mycobacteria and were intrigued. The team decided to look for this DNA transfer in M.

They soon noticed something funny going on. The bacterium seemed to have a totally novel way of reproducing. This article is from the online course:. Join Now. News categories. Other top stories on FutureLearn. Category: General. We take a closer look at media literacy and what makes it so important in ….

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Register to receive updates. Visit the source of this article and learn more! Small and Mighty: Introduction to Microbiology Join this course for free! Before You Go! Why Not I chose parameter values that would yield equivalent long-term population dynamics if these populations were modeled deterministically; all three scenarios have nearly identical population densities when the birth rate equals the death rate, indicating equal carrying capacities in the absence of stochasticity Fig.

The per-capita birth rate was much higher in small populations for the asexually reproducing populations than for the sexually reproducing populations Fig. However, the birth rate in the sexual populations increased as individuals became more effective at finding mates. Multiplying individual birth and death rates by population size yields population-level birth and death rates; whichever rate is larger indicates which event is more likely to occur next Fig.

Effects of mate limitation are prominent in small populations but negligible as population size increases. With CTMC models, it is also possible to calculate the probability that the next event in the model will be a birth or a death. In the simulated populations with asexual reproduction, it is highly unlikely that a death will occur when the population size is small. This probability of population decline in small populations is increased when mate limitation is present Fig.

Mate limitation decreases the individual-level birth rate at low population density top , which influences both the population-level growth rate middle and the probability that the next event in the model will be a death bottom.

Effects of mate limitation on population growth become negligible as population sizes increase, as indicated by the convergence of the three scenarios at larger populations. The effect of mate limitation is the difference between the aseuxally reproducing populations black lines and the sexually reproducing populations blue and green lines. Population growth rates are suppressed more strongly for poor mate searchers green lines than for effective mate searchers blue lines.

The dotted line in the bottom panel indicates a probability of 0. I recorded the time to extinction for simulated populations parameterized with the three mate search scenarios shown in Fig. All populations had equivalent death rates.

I used initial population sizes of 2, as this is the population size of newly colonizing taxa in the immigration simulation models. Typical model behavior showed the populations increasing in size and then fluctuating around the population size where the birth rate and the death rate were equal. Extinction occurred when population fluctuations were sufficiently large to drive the population to zero.

Asexual populations persisted longest among the three scenarios across all values for the intrinsic growth rate. Across the three mate limitation scenarios, the time to extinction increased approximately log-linearly with increasing intrinsic birth rate Fig. Averaging over 1, populations with a growth rate of 1.

In mate-limited populations, the time to extinction for effective searchers averaged 1,, while the MTE for poor searchers was Populations were simulated with different growth rates and different degrees of mate limitation; populations had either no limitation black , weak limitation due to effective searching blue , or strong limitation due to poor searching green. The MTEs for all three types of populations increased approximately log-linearly as population growth rate increased.

Populations with no mate limitation had the greatest MTE for any growth rate, and poor searchers had the most rapid extinction. Points and associated lines represent the mean and standard deviation for populations simulated with the same parameters. Assuming that a community consisted of populations with identical birth and death rates, I calculated the estimated long-term diversity for the three birth rate scenarios from the associated extinction rates Fig.

I used the same rate of immigration in each scenario. The immigration rate was a linearly decreasing function of current diversity and reached 0 when taxa were present Fig. It is possible to calculate approximate long-term diversity number of taxa by solving for the diversity level when the immigration rate equals the extinction rate equation 1.

However, the stochastic nature of the simulations means that these calculations will be inexact, because the populations never reach equilibrium. Equation 1 shows that the long-term diversity is a function of MTE. As MTE approaches infinity, the expected diversity approaches the diversity level where immigration is zero in this case, Conversely, as MTE approaches zero, the expected diversity also approaches zero. I evaluated the accuracy of this approximation by using explicit simulations of simultaneously coexisting populations using the same parameters.

The two estimates of diversity were within 1 unit taxon. Approximations using equation 1 yielded expected long-term diversities of When assuming the same immigration function gray line; left axis , mate limitation affects expected diversity by changing the time to population extinction.

A decreased time to extinction results in a greater slope for the community extinction rate black, blue, and green lines; right axis.

Expected diversity can be found by calculating the number of taxa where the immigration rate and the extinction rate intersect indicated by dotted lines. Communities are most diverse when there is no mate limitation black lines. When populations are mate limited but individuals are effective at finding mates, there is a small decrease in expected diversity blue lines.

When individuals are poor searchers, there is a dramatic decline in diversity due to more rapid extinction green lines. The time scale on which the immigration and extinction rates are shown here is the MTE of the shortest-lived populations poor searcher populations. Using a different time scale alters the y axes but does not change where the lines intersect. Although the previous diversity approximations were accurate under the assumption that taxa were identical, empirical communities contain taxa with a wide range of population sizes.

Therefore, I explored how introducing variability in growth rate and thus expected population size would influence the assembly of communities containing asexually reproducing taxa Fig.

I simulated communities containing either taxa with log-normally distributed growth rates or taxa with growth rates equal to the mean of the log-normally distributed growth rates. I recorded the resulting diversity, population size, mean growth rate of extant taxa, dominance, compositional change Bray-Curtis dissimilarity , and extinction rate calculated as 1 divided by the time between taxon extinctions of the communities.

Communities containing heterogeneous taxa showed differences from communities containing identical taxa across all of these emergent properties Fig. For both types of communities, increasing the immigration rate increased the mean diversity, with diversity saturating at high immigration rates. However, communities with heterogeneous taxa were generally lower in diversity as a result of the high extinction rates of the low-abundance taxa.

The demographics of heterogeneous communities also shifted in response to the immigration rate; at low immigration rates, the community of heterogeneous taxa was composed mainly of taxa with relatively high intrinsic growth rates and thus long times to extinction.

Therefore, changing the immigration rate also effectively altered the community-level extinction rate. Additionally, heterogeneous communities were more compositionally stable at low immigration rates, whereas communities of identical taxa were slightly more stable at higher immigration rates.

Dominance was relatively constant across immigration rates for both types of communities, although populations reached greater maximum sizes in the heterogeneous communities due to the presence of taxa with higher growth rates.

A and C Abundances of populations over time in simulated communities containing five taxa. Taxa have either heterogeneous growth rates A or identical growth rates C. B and D Diversity number of taxa present of the communities over time, with dotted lines indicating mean diversity. Most emergent properties of simulated communities change in response to changes in the immigration rate used in the model. Communities containing heterogeneous taxa black become more diverse A and slightly more compositionally stable C as immigration increases, but the average growth rate B and population size D decline and extinctions become more common E.

In populations of identical taxa gray , diversity increases more rapidly as immigration increases A , although the mean growth rate B and mean abundance D are not affected; additionally, communities become slightly less compositionally stable C , and the extinction rate saturates as a function of immigration rate E.

For both types of communities, dominance F is minimally affected by immigration rate except at very low immigration rates, where few taxa are present. The graphs show the mean values solid points plus or minus one half standard deviation shaded bars. Finally, I compared diversity, mean population size, and dominance population size of the most abundant taxon of communities containing mate-limited taxa and those with nonlimited taxa. Then, diversity and population size converged with results from communities containing asexual populations Fig.

However, the abundance of the most dominant population was minimally affected by search efficacy or reproductive method Fig.

Cells in Fig. Heatmaps show average diversity A , average abundance B , skewness of population abundances C , and dominant population size D from simulations of mate-limited communities in which populations have varying search radius units of length and search speed units of length per time.

The mate search equations assume that individuals in the population are distributed randomly at a density of N per unit volume length 3. Cells within each heatmap show the results for communities consisting of populations with the given search radius and search speed. Cell values are scaled to results from communities without mate limitation.

Thus, a value of 1 indicates results equivalent to those of nonlimited communities. The diversity A , mean abundance size B , and population size skewness C within communities containing mate-limited populations change in response to mate limitation, with stronger mate limitation corresponding to decreased diversity, larger average population size, and lower skewness. When the search radius and search speed are large, the probability of finding a mate approaches 1, and results for mate-limited and nonlimited communities converge.

The size of the most abundant population D is minimally affected by mate limitation. Communities containing the poorest mate searchers experienced the greatest declines in diversity, in comparison with the communities with asexual populations. Similarly, mean population size was Another measurement of species abundance distribution, the skewness of population abundances, showed a similar result; higher skewness indicates a greater proportion of low-abundance taxa, and skewness was near its maximum in communities with asexual taxa.

Average skewness in the distribution of population sizes was 0. However, dominance was not consistently related to mate limitation. The size of the dominant population in communities with mate-limited populations could be higher or lower than the dominant population in nonlimited communities. In mate-searching populations, the same degree of limitation could be generated with different combinations of search radius and search speed. Any combination of R and V that produces a constant value of VR 2 yields an equivalent probability of encountering a mate see equation 4.

This study presents a stochastic framework for studying the assembly of microbial communities and further shows that mate limitation influences emergent community properties, including diversity and average population size.

Mate limitation strongly suppresses birth rates when populations are small Fig. These discrepancies in birth rate lead to shorter times to extinction in taxa that must find a mate, versus those that reproduce asexually Fig.

This effect is particularly strong when populations are introduced at low density, which is a plausible scenario when considering newly established populations. In stochastic simulations, communities consisting of asexual taxa maintained greater diversity due to a longer expected persistence time for each population Fig. In the case in which immigration is a linear function of current diversity, expected diversity increases as MTE increases equation 1.

In communities containing heterogeneous taxa, the rapid turnover of small populations drove the changes in the emergent properties of diversity and mean population size Fig. When mate limitation was added to these simulations, differences in diversity and rarity were amplified, because mate limitation had especially strong negative effects on taxa with already-low growth rates Fig. Thus, mate limitation decreased the number of coexisting taxa, primarily by excluding low-abundance taxa.

Mate limitation had minimal consequences in larger populations, however, and thus the population size of the most abundant taxon was not related to reproductive method or mate search efficacy. The degree of mate limitation is a function of search ability, which is determined by search radius and search speed. As either search variable radius or speed increases, the probability of finding a mate approaches 1, indicating no limitation for the population birth rate.

In this case, simulation results for sexual populations with mate finding converge with those for populations without limitation. This is also evident when looking at per-capita and population growth curves Fig. Birth rates asymptotically reach the no-limitation case as mate searching becomes more effective.

Furthermore, this study highlights the utility of stochastic models for studying community structures. If the same populations considered in Fig. This study broadly concurs with prior models showing that Allee effects increase extinction rates 28 , — 30 , and it further demonstrates that these population-level effects alter emergent community properties.